{
 "features_resolved": {
  "snapshot_any": true,
  "snapshot_mem": false,
  "fork": true,
  "pause_resume": true,
  "persistent_disk": true,
  "whole_disk": true,
  "persist_scope": null,
  "volumes": true,
  "auto_stop_idle": true,
  "long_sessions": true,
  "custom_image": true,
  "image_snapshot": true,
  "image_oci": true,
  "vm_isolation": true,
  "docker_inside": true,
  "nested_virt": null,
  "root": true,
  "systemd": null,
  "browser": false,
  "desktop": false,
  "computer_use": false,
  "code_interpreter": true,
  "browser_control": null,
  "desktop_control": null,
  "browser_and_desktop": false,
  "anti_bot": false,
  "captcha_solving": false,
  "residential_ip": false,
  "agent_harnesses": false,
  "ssh": true,
  "public_ipv4": false,
  "inbound_https": true,
  "custom_domain": null,
  "raw_tcp_inbound": null,
  "egress_allowlist": true,
  "open_internet": null,
  "static_egress_ip": false,
  "private_network": true,
  "self_host": true,
  "byoc": true,
  "open_source": false,
  "soc2": true,
  "hipaa": true,
  "sso": true,
  "gpu": true,
  "arm64": false,
  "windows": false,
  "macos": false,
  "lang_python": true,
  "lang_node": true,
  "lang_go": null,
  "lang_rust": null,
  "lang_java": null,
  "gpu_desktop": false,
  "credential_injection": null,
  "egress_http_rules": false,
  "wake_on_request": true,
  "live_resize": false,
  "fork_running": true,
  "memory_snapshot_fork": false,
  "webhooks": null,
  "scheduled_wakeups": null,
  "audit_logs": true,
  "eu_data_residency": true,
  "zero_data_retention": null,
  "scoped_api_keys": null,
  "spend_limits": true,
  "mcp_server": false,
  "usage_api": false,
  "snapshot_auto": true,
  "snapshot_on_demand": true,
  "harness_api": false,
  "own_agent_api": false,
  "fast_boot": true,
  "strong_isolation": true,
  "ingress_rules": true,
  "guest_firewall": true,
  "secret_proxy": false,
  "secret_proxy_any": false,
  "volume_attach": true,
  "volume_shared": true,
  "sidecar": null,
  "fuse": true,
  "kernel_features": true,
  "burst": null
 },
 "company": {
  "id": "lightning-ai",
  "checked": "2026-09-30",
  "company": "Lightning AI, Inc. (formerly Grid.ai, Inc.)",
  "ownership": {
   "value": "independent",
   "parent": null,
   "source": "https://techcrunch.com/2024/11/21/lightning-ai-looks-to-make-managing-ai-a-piece-of-cake/",
   "quote": "Falcon, a former Navy Seal trainee and Facebook AI Research intern, started developing PyTorch Lightning while an undergraduate student at Columbia... Their venture, Lightning AI, takes the open source framework and layers enterprise-focused services and tools on top."
  },
  "stage": {
   "value": "series-c",
   "source": "https://techcrunch.com/2024/11/21/lightning-ai-looks-to-make-managing-ai-a-piece-of-cake/",
   "quote": "With the new $50 million investment, which comes from Cisco Investments, J.P. Morgan, Nvidia, and K5 Global, Lightning AI's total war chest stands at $103 million.",
   "confidence": "medium",
   "note": "TechCrunch never labels the Nov 2024 $50M round's letter. Priced-round history found: seed (undisclosed, ~2019, Index Ventures participated) -> Series A $18.6M (2020, led by Index Ventures) -> Series B $40M (2022, led by Coatue) -> this $50M round (2024, Cisco Investments/J.P. Morgan/Nvidia/K5 Global). Assuming standard lettering this would be Series C; not confirmed as such in press."
  },
  "accelerators": [],
  "total_funding_usd": {
   "value": 103000000,
   "status": "confirmed",
   "basis": "Company-stated total per TechCrunch, quoting CEO/company figures directly (not an aggregator estimate).",
   "source": "https://techcrunch.com/2024/11/21/lightning-ai-looks-to-make-managing-ai-a-piece-of-cake/",
   "quote": "Lightning AI's total war chest stands at $103 million."
  },
  "last_round": {
   "type": "unknown",
   "amount_usd": 50000000,
   "date": "2024-11",
   "leads": [],
   "status": "confirmed",
   "source": "https://techcrunch.com/2024/11/21/lightning-ai-looks-to-make-managing-ai-a-piece-of-cake/",
   "quote": "the company recently raised $50 million in a funding round... which comes from Cisco Investments, J.P. Morgan, Nvidia, and K5 Global."
  },
  "investors": [
   "Coatue",
   "Index Ventures",
   "Bain Capital Ventures",
   "Cisco Investments",
   "J.P. Morgan",
   "Nvidia",
   "K5 Global",
   "firstminute Capital",
   "Mantis VC (the Chainsmokers)",
   "SV Angel"
  ],
  "portfolio_listings": [
   {
    "source": "Abstract",
    "company": "Lightning Labs",
    "batch": "Series A",
    "how": "name"
   },
   {
    "source": "Cisco Investments",
    "company": "lightning ai",
    "batch": null,
    "how": "domain"
   },
   {
    "source": "Craft Ventures",
    "company": "Lightning Labs",
    "batch": null,
    "how": "name"
   },
   {
    "source": "Digital Currency Group",
    "company": "Lightning",
    "batch": 2016,
    "how": "name"
   },
   {
    "source": "Index Ventures",
    "company": "Lightning AI",
    "batch": null,
    "how": "domain"
   },
   {
    "source": "SV Angel",
    "company": "Lightning AI",
    "batch": null,
    "how": "domain"
   }
  ],
  "revenue": {
   "value": null,
   "status": "unknown"
  },
  "employees": {
   "value": 50,
   "source": "https://techcrunch.com/2024/11/21/lightning-ai-looks-to-make-managing-ai-a-piece-of-cake/"
  },
  "note": "Lightning AI is the commercial entity behind the open-source PyTorch Lightning framework, founded by William Falcon (with Luis Capelo); originally launched as Grid.ai in 2020, rebranded to Lightning AI in June 2022 alongside its Series B. As of Nov 2024, described as New York-based with ~50 employees and 230,000+ developers / 3,200+ organizations on the platform; no acquisition, shutdown, or layoffs reported."
 },
 "id": "lightning-ai",
 "name": "Lightning AI",
 "url": "https://lightning.ai/pricing",
 "category": "dev-env",
 "isolation": "vm",
 "modes": [
  {
   "key": "free-studio",
   "label": "The one free Default CPU Studio (4 cores / 16 GB)",
   "flags": [],
   "os": [
    "linux"
   ],
   "gpu_only": false,
   "features": {
    "isolation": null
   },
   "pricing": "pool",
   "vcpu_h": null,
   "ram_gib_h": null,
   "cpu_basis": "alloc",
   "ram_basis": "alloc",
   "active_floor": 0,
   "ram_per_vcpu": [
    null,
    null
   ],
   "ram_fixed_per_vcpu": null,
   "vcpu_options": null,
   "min_vcpu": null,
   "max_vcpu": 4,
   "max_ram_gib": 16,
   "sizes": null,
   "pool_tiers": [
    {
     "name": "1 free Default CPU Studio",
     "month": 0,
     "vcpu": 4,
     "ram_gib": 16,
     "max_vms": 1
    }
   ],
   "requires_always_on": false,
   "always_on_month_per_instance": null,
   "commit_note": "Only one free CPU Studio can be active per account at a time. On the Free plan the free Studio has a 4 h session limit, after which it converts to a paid Studio (billed from credits) unless restarted; disabling auto-sleep also converts it to paid. On Pro and above the session limit is unlimited.",
   "min_billed_seconds": 0,
   "granularity_s": 1,
   "start_fee": 0,
   "boot_overhead_s": null,
   "multiplier": 1,
   "windows_vcpu_h": null,
   "gpu": null,
   "note": "Pricing page CPU tab: Default (CPU) 4 cores / 16 GB 'Free', free hours 'unlimited'. Valid only for a concurrency of 1.",
   "plans": [
    "Pro (monthly)",
    "Pro (annual)",
    "Pro (academic, annual)",
    "Teams (monthly, per user)",
    "Teams (annual, per user)",
    "Enterprise",
    "Free (free Studio)"
   ]
  },
  {
   "key": "on-demand",
   "label": "On-demand CPU Studio (fixed shapes)",
   "flags": [],
   "os": [
    "linux"
   ],
   "gpu_only": false,
   "features": {
    "isolation": null
   },
   "pricing": "sizes",
   "vcpu_h": null,
   "ram_gib_h": null,
   "cpu_basis": "alloc",
   "ram_basis": "alloc",
   "active_floor": 0,
   "ram_per_vcpu": [
    null,
    null
   ],
   "ram_fixed_per_vcpu": null,
   "vcpu_options": null,
   "min_vcpu": null,
   "max_vcpu": 96,
   "max_ram_gib": 384,
   "sizes": [
    {
     "name": "Large (CPU)",
     "vcpu": 8,
     "ram_gib": 32,
     "disk_gib": null,
     "hour": 0.51,
     "month_cap": null
    },
    {
     "name": "X-Large (CPU)",
     "vcpu": 16,
     "ram_gib": 64,
     "disk_gib": null,
     "hour": 0.99,
     "month_cap": null
    },
    {
     "name": "Data prep",
     "vcpu": 32,
     "ram_gib": 128,
     "disk_gib": null,
     "hour": 1.48,
     "month_cap": null
    },
    {
     "name": "Data prep max",
     "vcpu": 64,
     "ram_gib": 256,
     "disk_gib": null,
     "hour": 2.69,
     "month_cap": null
    },
    {
     "name": "Data prep ultra",
     "vcpu": 96,
     "ram_gib": 384,
     "disk_gib": null,
     "hour": 4.79,
     "month_cap": null
    }
   ],
   "pool_tiers": null,
   "requires_always_on": false,
   "always_on_month_per_instance": null,
   "commit_note": null,
   "min_billed_seconds": 0,
   "granularity_s": 1,
   "start_fee": 0,
   "boot_overhead_s": null,
   "multiplier": 1,
   "windows_vcpu_h": null,
   "gpu": null,
   "note": "Per-second billing from credits (1 credit = $1). The on-demand price of an additional Default 4/16 Studio (beyond the free one) is not published, so it is omitted: 4-core workloads fall through to Large 8/32. Plan max CPUs per Studio: Free 32, Pro 64, Teams 96/192. Auto-sleep after 10 min idle (idle tail billed; sleeping Studio costs $0).",
   "plans": [
    "Free",
    "Pro (monthly)",
    "Pro (annual)",
    "Pro (academic, annual)",
    "Teams (monthly, per user)",
    "Teams (annual, per user)",
    "Enterprise"
   ]
  },
  {
   "key": "spot",
   "label": "Interruptible CPU Studio",
   "flags": [
    "spot"
   ],
   "os": [
    "linux"
   ],
   "gpu_only": false,
   "features": {
    "isolation": null
   },
   "pricing": "sizes",
   "vcpu_h": null,
   "ram_gib_h": null,
   "cpu_basis": "alloc",
   "ram_basis": "alloc",
   "active_floor": 0,
   "ram_per_vcpu": [
    null,
    null
   ],
   "ram_fixed_per_vcpu": null,
   "vcpu_options": null,
   "min_vcpu": null,
   "max_vcpu": 96,
   "max_ram_gib": 384,
   "sizes": [
    {
     "name": "Default (CPU) interruptible",
     "vcpu": 4,
     "ram_gib": 16,
     "disk_gib": null,
     "hour": 0.22,
     "month_cap": null
    },
    {
     "name": "Large (CPU) interruptible",
     "vcpu": 8,
     "ram_gib": 32,
     "disk_gib": null,
     "hour": 0.33,
     "month_cap": null
    },
    {
     "name": "X-Large (CPU) interruptible",
     "vcpu": 16,
     "ram_gib": 64,
     "disk_gib": null,
     "hour": 0.54,
     "month_cap": null
    },
    {
     "name": "Data prep ultra interruptible",
     "vcpu": 96,
     "ram_gib": 384,
     "disk_gib": null,
     "hour": 4.51,
     "month_cap": null
    }
   ],
   "pool_tiers": null,
   "requires_always_on": false,
   "always_on_month_per_instance": null,
   "commit_note": "Interruptible: the machine can be reclaimed. Data prep (32c) and Data prep max (64c) have no interruptible price.",
   "min_billed_seconds": 0,
   "granularity_s": 1,
   "start_fee": 0,
   "boot_overhead_s": null,
   "multiplier": 1,
   "windows_vcpu_h": null,
   "gpu": null,
   "note": "Pricing page CPU tab 'Cost/hr (interruptible)', verified 2026-09-28.",
   "plans": [
    "Free",
    "Pro (monthly)",
    "Pro (annual)",
    "Pro (academic, annual)",
    "Teams (monthly, per user)",
    "Teams (annual, per user)",
    "Enterprise"
   ]
  },
  {
   "key": "on-demand-gpu",
   "label": "GPU Studio, on-demand (1-GPU rates)",
   "flags": [],
   "os": [
    "linux"
   ],
   "gpu_only": true,
   "features": {
    "isolation": null
   },
   "pricing": "resource",
   "vcpu_h": 0,
   "ram_gib_h": 0,
   "cpu_basis": "alloc",
   "ram_basis": "alloc",
   "active_floor": 0,
   "ram_per_vcpu": [
    null,
    null
   ],
   "ram_fixed_per_vcpu": null,
   "vcpu_options": null,
   "min_vcpu": null,
   "max_vcpu": null,
   "max_ram_gib": null,
   "sizes": null,
   "pool_tiers": null,
   "requires_always_on": false,
   "always_on_month_per_instance": null,
   "commit_note": null,
   "min_billed_seconds": 0,
   "granularity_s": 1,
   "start_fee": 0,
   "boot_overhead_s": null,
   "multiplier": 1,
   "windows_vcpu_h": null,
   "gpu": {
    "T4": 0.55,
    "L4": 0.79,
    "L40S": 2.14,
    "RTX-PRO-6000": 2.89,
    "A100-40GB": 2.19,
    "A100-80GB": 2.71,
    "H100": 4.68,
    "H200": 4.5
   },
   "note": "Price per GPU-hour with the host CPU/RAM bundled (the CPU/RAM shape per GPU machine is not published, so vcpu_h/ram_gib_h = 0). The per-GPU rate differs on 2/4/8-GPU shapes: e.g. 8-GPU A100 80GB is $1.55/GPU, 8-GPU A100 40GB $3.87, 8-GPU L40S $4.21, 8-GPU B200 $9.86. Free plan: 1 GPU per Studio, 2 concurrent GPUs, 4 h A100/H100/H200 session limit.",
   "plans": [
    "Free (GPU)",
    "Pro (monthly) (GPU)",
    "Pro (annual) (GPU)",
    "Pro (academic, annual) (GPU)",
    "Teams (monthly, per user) (GPU)",
    "Teams (annual, per user) (GPU)",
    "Enterprise (GPU)"
   ]
  },
  {
   "key": "spot-gpu",
   "label": "GPU Studio, interruptible (midpoint of live band)",
   "flags": [
    "spot"
   ],
   "os": [
    "linux"
   ],
   "gpu_only": true,
   "features": {
    "isolation": null
   },
   "pricing": "resource",
   "vcpu_h": 0,
   "ram_gib_h": 0,
   "cpu_basis": "alloc",
   "ram_basis": "alloc",
   "active_floor": 0,
   "ram_per_vcpu": [
    null,
    null
   ],
   "ram_fixed_per_vcpu": null,
   "vcpu_options": null,
   "min_vcpu": null,
   "max_vcpu": null,
   "max_ram_gib": null,
   "sizes": null,
   "pool_tiers": null,
   "requires_always_on": false,
   "always_on_month_per_instance": null,
   "commit_note": "Interruptible; the price is a live band that moves intraday.",
   "min_billed_seconds": 0,
   "granularity_s": 1,
   "start_fee": 0,
   "boot_overhead_s": null,
   "multiplier": 1,
   "windows_vcpu_h": null,
   "gpu": {
    "T4": 0.66,
    "L4": 0.8,
    "RTX-PRO-6000": 3.585,
    "A100-80GB": 4.025,
    "H200": 4.2
   },
   "note": "Midpoint of the 1-GPU interruptible bands on lightning.ai/pricing (checked 2026-10-14: T4 0.60-0.72 \"T4 1 16 GB $0.55 $0.60 ﹘ $0.72\", RTX PRO 6000 3.26-3.91 \"RTXP 6000 1 96 GB $2.89 $3.26 ﹘ $3.91\"; L4 0.73-0.87, A100 80GB 3.66-4.39, H200 3.82-4.58 unchanged since 2026-09-28). H100, L40S and A100 40GB have NO interruptible price (\"-\"), so an H100 request falls back to the H200 band. For T4, RTX PRO 6000 and A100 80GB the whole band is above on-demand.",
   "band": {
    "T4": [
     0.6,
     0.72
    ],
    "L4": [
     0.73,
     0.87
    ],
    "RTX-PRO-6000": [
     3.26,
     3.91
    ],
    "A100-80GB": [
     3.66,
     4.39
    ],
    "H200": [
     3.82,
     4.58
    ]
   },
   "plans": [
    "Free (GPU)",
    "Pro (monthly) (GPU)",
    "Pro (annual) (GPU)",
    "Pro (academic, annual) (GPU)",
    "Teams (monthly, per user) (GPU)",
    "Teams (annual, per user) (GPU)",
    "Enterprise (GPU)"
   ]
  }
 ],
 "storage": {
  "included_disk_gib": 10,
  "disk_gib_month": 0.1,
  "disk_billed_when_stopped": true,
  "snapshot_gib_month": null,
  "paused_ram_billed": false
 },
 "network": {
  "egress_free_gib": null,
  "egress_gib": null,
  "ipv4_month": null,
  "ipv4_available": false
 },
 "plans": [
  {
   "name": "Free",
   "fee": 0,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 0,
   "per_seat": 0,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 32,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "One-time up to 30 credits (5 on sign-up + 25 with a card). Paid CPU Studios are pay-as-you-go credits; concurrency of paid CPU Studios on Free is not published (null). Max 32 CPUs per Studio. When credits run out, workloads are gracefully shut down (no overage). GPU limits are on \"Free (GPU)\"; the free-Studio 4 h restart is on \"Free (free Studio)\"."
  },
  {
   "name": "Pro (monthly)",
   "fee": 50,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 40,
   "per_seat": 0,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 64,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "$50/mo includes 40 credits/mo ($10 pure fee). Credits expire 12 months after issue, so unused ones roll over within the year. 4 GPUs per Studio; 6 concurrent GPUs; 200 GB Drive; no free-Studio restarts."
  },
  {
   "name": "Pro (annual)",
   "fee": 20,
   "flags": [
    "sales"
   ],
   "fee_is_credit": true,
   "included_usd": 0,
   "per_seat": 0,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 64,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "$240/yr prepaid (shown as $20/mo) includes 240 annual credits, so the fee is fully credit. Flagged 'sales' only because it is a 1-year commitment (self-serve checkout)."
  },
  {
   "name": "Pro (academic, annual)",
   "fee": 10,
   "flags": [
    "sales"
   ],
   "fee_is_credit": false,
   "included_usd": 8.33,
   "per_seat": 0,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 64,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "Academic toggle: $10/mo billed annually, 100 annual credits (= $8.33/mo). Academic eligibility required; 1-year commitment."
  },
  {
   "name": "Teams (monthly, per user)",
   "fee": 140,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 50,
   "per_seat": 140,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 192,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "$140/user/mo includes 50 credits/user/mo. Plan card says '96 core CPU', comparison table says 192 max CPUs per Studio (largest shape is 96 cores anyway). 8 GPUs per Studio; 12 concurrent GPUs; 2 TB Drive; spending limits; credit auto-reload; AWS Marketplace billing."
  },
  {
   "name": "Teams (annual, per user)",
   "fee": 119,
   "flags": [
    "sales"
   ],
   "fee_is_credit": false,
   "included_usd": 50,
   "per_seat": 119,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 192,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "$119/user/mo billed annually, 600 annual credits per user (= 50/mo). 1-year commitment."
  },
  {
   "name": "Enterprise",
   "fee": null,
   "flags": [
    "sales"
   ],
   "fee_is_credit": null,
   "included_usd": null,
   "per_seat": null,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 192,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "Custom credits at bulk pricing; use your own AWS/GCP credits; VPC/BYOC and on-prem; full-node B200; unlimited concurrent GPUs; 99.95% SLA; SAML/SSO; bring your own images. Reserved clusters are quote-only."
  },
  {
   "name": "Free (free Studio)",
   "fee": 0,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 0,
   "per_seat": 0,
   "concurrency": null,
   "max_session_h": 4,
   "max_vcpu": 32,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "The one free Default CPU Studio on the Free plan has a 4 h session limit; per the compare-table tooltip it converts to a paid Studio after reaching the limit (hero footnote: 'require restart every 4 hours'). Auto-sleep docs: a free Studio also converts to paid if auto-sleep is disabled. Paid Studios on Free have no published session limit."
  },
  {
   "name": "Free (GPU)",
   "fee": 0,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 0,
   "per_seat": 0,
   "concurrency": 2,
   "max_session_h": 4,
   "max_vcpu": 32,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Free: max concurrent GPUs 2; A100/H100/H200 sessions limited to 4 h (T4/L4/L40S unlimited); 1 GPU per Studio. One-time up to 30 credits (see free.one_time_credit). Paid CPU/GPU usage is pay-as-you-go credits. The free Default Studio restarts every 4 h. A100/H100/H200 sessions are limited to 4 h; 1 GPU per Studio; 2 concurrent GPUs; 200 GB persistent storage limit. When credits run out, workloads are gracefully shut down (no overage)."
  },
  {
   "name": "Pro (monthly) (GPU)",
   "fee": 50,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 40,
   "per_seat": 0,
   "concurrency": 6,
   "max_session_h": null,
   "max_vcpu": 64,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Pro (monthly): max concurrent GPUs 6. $50/mo includes 40 credits/mo ($10 pure fee). Credits expire 12 months after issue, so unused ones roll over within the year. 4 GPUs per Studio; 6 concurrent GPUs; 200 GB Drive; no free-Studio restarts."
  },
  {
   "name": "Pro (annual) (GPU)",
   "fee": 20,
   "flags": [
    "sales"
   ],
   "fee_is_credit": true,
   "included_usd": 0,
   "per_seat": 0,
   "concurrency": 6,
   "max_session_h": null,
   "max_vcpu": 64,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Pro (annual): max concurrent GPUs 6. $240/yr prepaid (shown as $20/mo) includes 240 annual credits, so the fee is fully credit. Flagged 'sales' only because it is a 1-year commitment (self-serve checkout)."
  },
  {
   "name": "Pro (academic, annual) (GPU)",
   "fee": 10,
   "flags": [
    "sales"
   ],
   "fee_is_credit": false,
   "included_usd": 8.33,
   "per_seat": 0,
   "concurrency": 6,
   "max_session_h": null,
   "max_vcpu": 64,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Pro (academic, annual): max concurrent GPUs 6. Academic toggle: $10/mo billed annually, 100 annual credits (= $8.33/mo). Academic eligibility required; 1-year commitment."
  },
  {
   "name": "Teams (monthly, per user) (GPU)",
   "fee": 140,
   "flags": [],
   "fee_is_credit": false,
   "included_usd": 50,
   "per_seat": 140,
   "concurrency": 12,
   "max_session_h": null,
   "max_vcpu": 192,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Teams (monthly, per user): max concurrent GPUs 12. $140/user/mo includes 50 credits/user/mo. Plan card says '96 core CPU', comparison table says 192 max CPUs per Studio (largest shape is 96 cores anyway). 8 GPUs per Studio; 12 concurrent GPUs; 2 TB Drive; spending limits; credit auto-reload; AWS Marketplace billing."
  },
  {
   "name": "Teams (annual, per user) (GPU)",
   "fee": 119,
   "flags": [
    "sales"
   ],
   "fee_is_credit": false,
   "included_usd": 50,
   "per_seat": 119,
   "concurrency": 12,
   "max_session_h": null,
   "max_vcpu": 192,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Teams (annual, per user): max concurrent GPUs 12. $119/user/mo billed annually, 600 annual credits per user (= 50/mo). 1-year commitment."
  },
  {
   "name": "Enterprise (GPU)",
   "fee": null,
   "flags": [
    "sales"
   ],
   "fee_is_credit": null,
   "included_usd": null,
   "per_seat": null,
   "concurrency": null,
   "max_session_h": null,
   "max_vcpu": 192,
   "max_ram_gib": null,
   "sizes_allowed": null,
   "note": "GPU Studios on Enterprise: max concurrent GPUs unlimited (Enterprise). Custom credits at bulk pricing; use your own AWS/GCP credits; VPC/BYOC and on-prem; full-node B200; unlimited concurrent GPUs; 99.95% SLA; SAML/SSO; bring your own images. Reserved clusters are quote-only."
  }
 ],
 "free": {
  "monthly_credit": 0,
  "one_time_credit": 30
 },
 "features": {
  "linux": true,
  "windows": false,
  "macos": false,
  "arm64": false,
  "gpu": true,
  "gpu_types": [
   "T4",
   "L4",
   "L40S",
   "RTX-PRO-6000",
   "A100-40GB",
   "A100-80GB",
   "H100",
   "H200",
   "B200"
  ],
  "snapshot": "fs",
  "pause_resume": true,
  "fork": true,
  "persistent_disk": true,
  "volumes": true,
  "auto_stop_idle": true,
  "max_session_h": null,
  "custom_image": true,
  "docker_inside": true,
  "nested_virt": null,
  "root": true,
  "systemd": null,
  "browser": false,
  "desktop": false,
  "computer_use": false,
  "code_interpreter": true,
  "agent_harnesses": false,
  "ssh": true,
  "public_ipv4": false,
  "inbound_https": true,
  "custom_domain": null,
  "raw_tcp_inbound": null,
  "egress_allowlist": true,
  "static_egress_ip": false,
  "private_network": true,
  "self_host": true,
  "byoc": true,
  "open_source": false,
  "regions": null,
  "soc2": true,
  "hipaa": true,
  "sso": true,
  "lang_python": true,
  "lang_node": true,
  "lang_go": null,
  "lang_rust": null,
  "lang_java": null,
  "gpu_desktop": false,
  "credential_injection": null,
  "egress_http_rules": false,
  "wake_on_request": true,
  "live_resize": false,
  "fork_running": true,
  "memory_snapshot_fork": false,
  "webhooks": null,
  "scheduled_wakeups": null,
  "audit_logs": true,
  "eu_data_residency": true,
  "zero_data_retention": null,
  "scoped_api_keys": null,
  "spend_limits": true,
  "mcp_server": false,
  "isolation": "dedicated-vm",
  "image_oci": true,
  "snapshot_auto": true,
  "snapshot_on_demand": true,
  "harness_api": false,
  "egress_allowlist_level": "ip",
  "ingress_rules": true,
  "secret_proxy": false,
  "volume_attach": true,
  "volume_shared": true,
  "anti_bot": false,
  "captcha_solving": false,
  "egress_ip_type": "datacenter",
  "own_agent_api": false,
  "guest_firewall": true,
  "max_session_unlimited": true,
  "fast_boot": true,
  "usage_api": false
 },
 "perf": {
  "cpu_runs_s": null,
  "cold_start_ms": 154.83,
  "burst_tti_ms": 432.92,
  "dax_s": 41.8
 },
 "perf_source": "ComputeSDK benchmarks (benchmarks.json): cold-start TTI median 2026-08-07, burst TTI median at 100 concurrency 2026-08-21, DAX total 2026-08-14 (8 logical CPUs / 38.75 GiB x86_64 env). Measured the Lightning Sandbox API, whose price is unpublished. Later runs (2026-09-10) failed.",
 "knobs": [],
 "caveats": [
  "The Sandbox API (cpu-1 1/1 GB, cpu-2 2/8, cpu-4 4/16, cpu-8 8/32, cpu-16 16/64) has NO published price. The card prices Studio shapes. cpu-4/8/16 match the Default/Large/X-Large Studios, but whether Studio rates apply is unverified.",
  "No on-demand price is published for a second Default 4/16 CPU Studio (only 'Free' for one). The engine therefore puts 4-core on-demand workloads on Large 8/32 ($0.51/h), which may overestimate.",
  "GPU Studio prices are per GPU with host CPU/RAM bundled. The per-GPU rate varies by 1/2/4/8-GPU shape (e.g. A100 80GB $2.71 single vs $1.55 on 8-GPU; A100 40GB $2.19 single vs $3.87 on 8-GPU); only 1-GPU rates are encoded (B200 is listed for 8-GPU nodes only at $9.86/GPU).",
  "Interruptible GPU bands are live and move intraday; on T4, RTX PRO 6000 and A100 80GB they sit above on-demand. TPU Studios ($3.03-$4.72/TPU-h) are not encoded.",
  "10 GB free storage is account-wide (Drive), not per sandbox; above it $0.10/GB-month billed daily. Persistent storage limits (pricing page, checked 2026-10-14, Free card: \"Persistent storage (200 GB limit)\"): Free 200 GB, Pro 200 GB, Teams 2 TB. Snapshot storage price not separately published.",
  "When credits run out, Lightning warns and then gracefully shuts down all Studios: there is no overage. Credits (free and paid) expire after 12 months, so monthly plan credits roll over within a year.",
  "Free plan concurrency for paid CPU Studios is not published. GPU concurrency: Free 2, Pro 6, Teams 12.",
  "Egress, ingress and public IPv4 pricing not published. Regions are not listed as geographies; compute runs on AWS, GCP, Lightning (Voltage Park), Lambda, Nebius, NScale and Voltage. Lightning AI and Voltage Park merged in 2026 (lightning.ai/about, checked 2026-10-14: \"In 2026, we became one company\"; 36,000+ NVIDIA GPUs across seven US data centers).",
  "Auto-sleep after 10 min idle (customisable on paid tiers), so up to 10 min idle tail is billed per session. A sleeping Studio costs $0 compute.",
  "2026-09-21 reprice (third-party usagepricing.com): GPU rates moved and the Free tier went from 15 monthly credits to a one-time up-to-30 grant. usagepricing lists H100 at $4.50, but the official page shows $4.68 (2026-09-28).",
  "Annual plans are flagged 'sales' only because they are 1-year prepaid commitments; they are self-serve.",
  "Studio start/wake time is not published, so no boot overhead is modelled; Studios are dev environments, not an instant sandbox API.",
  "Multi-GPU per-GPU rates (live 2026-09-29): 2-GPU L4 $1.19, RTX PRO 6000 $2.82, A100 40GB $2.19, A100 80GB $2.69, H100 $4.68, H200 $4.50; 4-GPU T4 $0.88, L4 $1.20, L40S $2.97, RTX PRO 6000 $2.79, A100 40GB $2.19, A100 80GB $2.68, H100 $4.68, H200 $4.50. Multi-GPU interruptible bands are sometimes far below 1-GPU: 4-GPU T4 $0.29-0.35, 4-GPU L40S $1.90-2.28, 8-GPU L40S $2.80-3.36, 8-GPU A100 40GB $2.57-3.08 per GPU (no 1-GPU spot for L40S / A100 40GB).",
  "Starting a Studio from a custom launch image ('Bring your own images') is Enterprise-only; lower tiers customise the persistent environment interactively (Docker is installed inside Studios). The Sandbox API separately accepts a user OCI image.",
  "Other storage tiers: high-performance volumes on Lightning Cloud $0.30/GiB-month; AWS EFS $0.0125/GB-day + $0.0375/GB read + $0.075/GB write; GCP Filestore $0.5625/GB-month (EFS/Filestore Enterprise-only per compare table). The 10 GB free is per account and storage is billed while Studios sleep.",
  "Max concurrent GPUs (Free 2 / Pro 6 / Teams 12) counts GPUs across Studios, Batch Jobs, multi-machine training and Deployments together."
 ],
 "sources": [
  "https://lightning.ai/pricing",
  "https://lightning.ai/about",
  "https://lightning.ai/docs/overview/faq/billing",
  "https://lightning.ai/docs/platform/build/sandbox.md",
  "https://lightning.ai/docs/platform/build/ai-studio.md",
  "https://lightning.ai/docs/platform/gpu-cloud/gpu-marketplace.md",
  "https://www.usagepricing.com/blueprint/lightning-ai",
  "https://www.computesdk.com/benchmarks/sandboxes/"
 ],
 "fleet": {
  "default_max_instances": null,
  "default_max_vcpu": null,
  "default_max_gpus": 2,
  "raise": "self-serve",
  "raise_time_days": null,
  "verification": "Phone/identity verification; work or university email verifies faster. No card required for free signup; support can expedite verification.",
  "tiers": "Free up to 2 concurrent GPUs; Pro 6; Teams 12; Enterprise unlimited by contract.",
  "notes": "One free Studio is an included allowance, not proven total account concurrent-CPU-instance cap. GPU counts from rendered pricing; verification may take 2–3 business days for personal emails, not a quota-increase SLA. Country eligibility applies.",
  "sources": [
   "https://lightning.ai/pricing",
   "https://lightning.ai/docs/platform/overview/faq/create-account.md",
   "https://lightning.ai/docs/platform/build/ai-studio.md"
  ],
  "researched": "2026-09-28"
 },
 "audit_2026_09_29": {
  "applied": 6,
  "source": "checked against the provider's live pricing and docs pages",
  "reviewed": 2
 },
 "feature_evidence": {
  "snapshot_auto": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/developers/cli/sandbox.md",
   "quote": "Stop a sandbox. For a persistent sandbox the control plane captures an auto-snapshot and returns its id; the sandbox id keeps resolving and can be brought back with [`start`](#start).",
   "note": "Sandbox API with persistent=True: stop() auto-snapshots the filesystem (not running processes) and resume() restores it (sandbox.md: 'Sandboxes auto-save state on stop and resume right where you left off'). Whether the create-time timeout auto-stop also auto-snapshots is not stated. Studios: auto-sleep after 10 min idle keeps the home dir/system packages on persistent storage (that is persistent_disk, not a memory checkpoint; Docker images not persisted).",
   "checked": "2026-09-29"
  },
  "snapshot_on_demand": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "Capture the filesystem (not running processes):",
   "note": "sandbox.snapshot() / `lightning sandbox snapshot create` on a running sandbox, optional TTL and excludes; new sandboxes boot from it via Sandbox.create(snapshot_id=...) / `create --snapshot-id`. Filesystem only, no memory. Snapshots do not carry the network policy (restore defaults to allow-all). Studios can also be duplicated (fork).",
   "checked": "2026-09-29"
  },
  "harness_api": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "Use the Lightning Sandbox Python SDK to create ephemeral sandboxes, run commands, manage files, capture snapshots, and open interactive PTY sessions from Python.",
   "note": "SDK/CLI surface is commands, files, PTY, snapshots, network policy only; no Claude Code/Codex/agent-session API anywhere in the docs manifest. The Agents page is a tutorial for writing your own LitAI agent in a Studio and scheduling it.",
   "checked": "2026-09-29"
  },
  "egress_allowlist": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "Egress firewall, set at create time only — no runtime mutation.",
   "note": "Sandbox API network_policy: allow-all (default), deny-all, or NetworkPolicy(allow_cidrs=[...]) default-deny. Docs: 'enforcement is IP-based'; blocked connections are dropped and logged. Cannot be changed after create; snapshot restore defaults back to allow-all unless re-specified. No documented egress control for Studios (Enterprise BYOC/VPC only).",
   "checked": "2026-09-29",
   "level": "ip"
  },
  "egress_http_rules": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "A single `NetworkPolicy` models every mode (mirrors Vercel's `NetworkPolicy`):",
   "note": "The only modes are allow-all, deny-all and a CIDR allowlist; no host, method, path or header rules.",
   "checked": "2026-09-29"
  },
  "ingress_rules": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/build/ai-studio/deploy-on-public-ports.md",
   "quote": "Restrict access to your endpoint by enabling security. There are 2 ways of securing an endpoint in the API builder.",
   "note": "Studios: public URLs opened per port via API builder / Port viewer plugins, with optional token or basic auth. Sandbox API: `ports=` chooses which ports are opened but the SDK returns no public URL ('Reach the port from inside the sandbox or another box on the same network'). No IP allowlists documented.",
   "checked": "2026-09-29"
  },
  "secret_proxy": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/ai-studio/managed-secrets.md",
   "quote": "Secrets are encrypted and served securely as environment variables in studios at runtime.",
   "note": "User/teamspace secrets are injected as env vars into Studios; the Sandbox API has only image_secret_ref for private registry pulls. No credential-injecting proxy.",
   "checked": "2026-09-29"
  },
  "volume_attach": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/data/drive.md",
   "quote": "The Drive can also hold high-performance volumes: fixed-size volumes that Lightning AI provisions on Lightning Cloud and mounts read/write at `/teamspace/lightning_storage/<volume name>`.",
   "note": "Studios/Jobs: high-performance volumes ($0.30/GiB-month) tied to one compute location/region, resizable up only; also EFS/Filestore cloud folders (Enterprise) and S3/GCS data connections. Sandbox API only has a storage_gb writable-disk override; Drive/volume mounts for sandboxes are not documented.",
   "checked": "2026-09-29"
  },
  "volume_shared": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/data/drive.md",
   "quote": "All Studios in a teamspace share the same drive. This means any Studio can access the files of the other Studios.",
   "note": "Teamspace Drive is a shared read-write filesystem across Studios, Jobs, Deployments; cloud folders 'any workflow, Studio, or cluster can mount'. Applies to Studios, not documented for Sandbox API.",
   "checked": "2026-09-29"
  },
  "isolation": {
   "value": "dedicated-vm",
   "source": "https://lightning.ai/docs/platform/build/ai-studio.md",
   "quote": "Studios differ quite a bit from just renting a GPU VM, here are some key features.",
   "note": "Lightning does not name a specific hypervisor/microVM technology anywhere in its docs. Studios and GPU Studios run as dedicated cloud instances across AWS/GCP/Lambda/Nebius/etc (per the card's own sources), each with full root/sudo, Docker-inside, and real GPU passthrough — consistent with one dedicated VM per Studio rather than a shared-kernel container or gVisor/Kata sandbox. The separate Sandbox API markets 'strongly isolated' millisecond-start environments but its underlying tech is also unnamed.",
   "checked": "2026-09-30"
  },
  "browser": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/ai-studio.md",
   "quote": "AI Studio is a persistent, collaborative GPU cloud workspace that feels like a local laptop - with AI copilots that help you debug, train, inference, and ship like a pro.",
   "note": "not offered: outside the product's scope. Lightning is a dev/ML compute workspace (Studios/Sandbox/GPU cloud) with browser-accessible VSCode/Jupyter IDEs, not a managed real-browser/automation product; the Agents tutorial uses plain `requests`+BeautifulSoup, not a provider-managed browser.",
   "checked": "2026-09-30"
  },
  "anti_bot": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/agents.md",
   "quote": "these headers make our request look like a regular browser visit, which helps prevent websites from blocking our scraper.",
   "note": "not offered: outside the product's scope. The only 'anti-bot' technique shown in official docs is a user-supplied User-Agent header in sample scraping code; there is no built-in stealth/fingerprinting product feature.",
   "checked": "2026-09-30"
  },
  "captcha_solving": {
   "value": false,
   "source": "https://lightning.ai/pricing",
   "quote": "Studios: Collaborative, cloud-based AI development environments.",
   "note": "not offered: outside the product's scope. Lightning AI is a GPU cloud / dev-environment / sandbox product, not a browser/scraping product; no CAPTCHA-solving capability is documented anywhere.",
   "checked": "2026-09-30"
  },
  "egress_ip_type": {
   "value": "datacenter",
   "source": "https://lightning.ai/docs/platform/security/trusted-platform.md",
   "quote": "The Lightning AI infrastructure is implemented with multiple cloud providers using industry-leading architectures.",
   "note": "Studios/Sandboxes/GPU machines run on AWS/GCP/Lambda/Nebius/Voltage Park/NScale cloud capacity (per the card's own pricing-page sourced note), so outbound traffic originates from standard cloud-provider datacenter IP ranges; no residential/mobile egress is offered or implied anywhere in the docs.",
   "checked": "2026-09-30"
  },
  "fork_running": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/build/ai-studio/duplicate-studios.md",
   "quote": "To duplicate a Studio in a Teamspace, simply press the \"duplicate\" button... expect duplication to happen in <1 minute.",
   "note": "Duplication is described as a single in-place button press on an existing Studio, with no documented requirement to stop/sleep the source Studio first, implying the running source keeps running while the copy is created. Not explicitly confirmed either way for running vs stopped state.",
   "checked": "2026-09-30"
  },
  "wake_on_request": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/build/host-web-apps.md",
   "quote": "Auto-start enables apps to run 24/7, but you only pay when the app is being used actively. Under the hood, Lightning AI monitors user traffic to your app and turns it off when no one is using it.",
   "note": "A sleeping Studio automatically wakes when a new request/URL hit arrives; the doc calls out the resulting few-minutes 'cold-start' delay before the app is reachable again.",
   "checked": "2026-09-30"
  },
  "live_resize": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/ai-studio/add-gpus.md",
   "quote": "A Studio can switch hardware to different GPU types. To switch, simply select the type of machine you want, click \"Switch\" and wait until it is ready.",
   "note": "Switching CPU/RAM/GPU shape is a machine swap ('wait until it is ready') where the Studio always restarts on a CPU machine afterward (per the auto-sleep doc), not a live in-place resize of a running machine without recreating it. The persistent environment/disk survives the swap, but the running process/session does not.",
   "checked": "2026-09-30"
  },
  "own_agent_api": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/agents.md",
   "quote": "Lightning AI Studio is perfect for building agents. Here's an example that shows you how to build and automate an agent that scrapes a website for you and tells you about which stocks to buy or not.",
   "note": "not offered: outside the product's scope. The 'Agents' page is a tutorial for writing your own LitAI-based agent inside a Studio; there is no first-party API that drives a Lightning-owned browser/computer-use/research agent.",
   "checked": "2026-09-30"
  },
  "mcp_server": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/sandbox.md",
   "quote": "CLI and SDKs: Manage sandboxes through the CLI, JS SDK, or Python SDK, and automate sandbox workflows in your application.",
   "note": "Sandbox/Studio control surfaces documented are the Python SDK, JS SDK, and CLI only; no MCP server is mentioned in any Lightning AI docs page, GitHub org listing, or pricing/docs manifest found.",
   "checked": "2026-09-30"
  },
  "guest_firewall": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/build/sandbox.md",
   "quote": "Every sandbox has full `sudo` access.",
   "note": "derived: full root/sudo inside a dedicated VM-style machine implies nftables/iptables work inside, though this is not separately documented.",
   "checked": "2026-09-30"
  },
  "static_egress_ip": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "Egress firewall, set at create time only — no runtime mutation. A single `NetworkPolicy` models every mode... allow-all... deny-all... CIDR allowlist; deny everything else.",
   "note": "The only egress control documented is an allow-all/deny-all/CIDR-allowlist firewall on outbound connections; there is no mention of a fixed/static outbound IP assigned per sandbox or Studio.",
   "checked": "2026-09-30"
  },
  "eu_data_residency": {
   "value": true,
   "source": "https://lightning.ai/docs/platform/security/privacy/data-residency.md",
   "quote": "Lightning AI supports all major US, EU, Asia regions. Additional support can be provided upon request.",
   "note": "Customers can choose a data-storage region, including EU, when linking a cloud account.",
   "checked": "2026-09-30"
  },
  "max_session_h": {
   "value": "none",
   "source": "https://lightning.ai/pricing",
   "quote": "On Pro and above the session limit is unlimited.",
   "note": "Only the single free Default CPU Studio (Free plan) has a hard 4h session limit (after which it converts to paid or restarts); Pro/Teams/Enterprise Studios and paid CPU/GPU usage have no published session-length cap (the Sandbox API's `timeout` param defaults to 0 = no timeout and is extendable indefinitely via extend_timeout()).",
   "checked": "2026-09-30"
  },
  "memory_snapshot_fork": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/ai-studio/duplicate-studios.md",
   "quote": "Duplication in Studios solves this problem by letting users copy everything in a Studio, including the environment, files, packages, dependencies, data, and more.",
   "note": "Studio 'duplicate' and Sandbox 'snapshot'/'fork' (features.fork=true) are filesystem-level copies of a stopped/at-rest environment, not a fork of a live process's in-memory state. No product page describes cloning a running Studio/sandbox's RAM/process state; sandbox.snapshot() docs explicitly say 'Capture the filesystem (not running processes)'. No memory-snapshot fork exists.",
   "checked": "2026-09-30"
  },
  "desktop": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/ai-studio.md",
   "quote": "Instances come with pre-packaged VSCode and JupyterLab, accessible directly from the browser ... Otherwise, use ssh to connect any local IDE such as VSCode, Cursor, PyCharm and more.",
   "note": "Access is via browser VSCode/JupyterLab or SSH; no remote-desktop/VNC/GUI streaming is documented anywhere in the Studio, Sandbox, or GPU-cloud docs.",
   "checked": "2026-09-30"
  },
  "computer_use": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "Use the Lightning Sandbox Python SDK to create ephemeral sandboxes, run commands, manage files, capture snapshots, and open interactive PTY sessions from Python.",
   "note": "The SDK/CLI surface is limited to commands, files, PTY and snapshots (headless Linux sandbox/dev-env); no mouse/keyboard/screen 'computer use' API or GUI environment exists anywhere in the docs manifest.",
   "checked": "2026-09-30"
  },
  "public_ipv4": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/developers/sdk/sandbox/python-sandbox-sdk.md",
   "quote": "Limitation — no public URL from the SDK. The sandbox API does not currently return an external hostname/URL for an exposed port; there is no url/endpoint property on SandboxInstance ... reaching it from outside requires an endpoint the SDK does not surface today.",
   "note": "No dedicated/public IPv4 address or SDK-exposed public endpoint for Sandboxes. Studios expose ports via app builder/plugin URLs (a shared hostname/path, not a per-instance public IPv4), consistent with network.ipv4_available=false already on the card.",
   "checked": "2026-09-30"
  },
  "agent_harnesses": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/ai-studio.md",
   "quote": "Each Studio comes prebuilt with AI copilots that we've trained to be experts on everything AI/ML... from training models, building inference engines, to debugging CUDA and expert-level PyTorch.",
   "note": "The only bundled 'AI' feature is Lightning's own in-house AI copilot for ML debugging/training; no pre-installed third-party coding-agent harness (Claude Code, Codex CLI, OpenHands, etc.) or agent-session API is documented anywhere in the docs/CLI/SDK manifest.",
   "checked": "2026-09-30"
  },
  "windows": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/sandbox.md",
   "quote": "Lightning AI Sandbox gives every workload its own isolated Linux environment, spun up in milliseconds and torn down when you're done.",
   "note": "Studios and the Sandbox API are both Linux-only (features.linux=true is the only OS documented); no Windows machine option exists on this Linux dev-env/GPU-cloud product.",
   "checked": "2026-09-30"
  },
  "macos": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/sandbox.md",
   "quote": "Lightning AI Sandbox gives every workload its own isolated Linux environment, spun up in milliseconds and torn down when you're done.",
   "note": "Product is a Linux Studio/Sandbox/GPU-cloud platform; no macOS machine offering exists anywhere in docs or pricing.",
   "checked": "2026-09-30"
  },
  "arm64": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/build/sandbox.md",
   "quote": "Run processes that require elevated permissions, with sudo access available in every sandbox.",
   "note": "No ARM/Graviton/Apple-Silicon instance type appears anywhere in the Sandbox instance types (cpu-1..cpu-16), Studio CPU/GPU shapes, or GPU marketplace docs; every documented shape/GPU pairing is x86_64 (confirmed separately by the ComputeSDK benchmark source noting an x86_64 env).",
   "checked": "2026-09-30"
  },
  "self_host": {
   "value": true,
   "corrected_from": false,
   "source": "https://lightning.ai/pricing",
   "quote": "Lightning on prem",
   "note": "The live pricing-page plan-comparison table (Security section) lists 'Lightning on prem' as a distinct capability alongside 'Lightning in your VPC' (BYOC) — i.e. Lightning offers running the platform on the customer's own on-prem infrastructure, gated to Enterprise/custom (quote-only) tiers. That is exactly the self_host definition ('you can run it on your own infrastructure'), so false is wrong; correct value is true (Enterprise-only, sales-gated).",
   "checked": "2026-09-30"
  },
  "open_source": {
   "value": false,
   "source": "https://lightning.ai/open-source/",
   "quote": "Lightning’s open-source ecosystem is for researchers and engineers who need flexibility and performance at scale. From the makers of PyTorch Lightning.",
   "note": "Lightning's open-source releases are ML libraries (PyTorch Lightning, Fabric, TorchMetrics, etc.), not the Studio/Sandbox/GPU-cloud control-plane product being rated here, which is closed-source SaaS (with an Enterprise on-prem deployment option, not a public source release under an OSI license).",
   "checked": "2026-09-30"
  },
  "fast_boot": {
   "value": true,
   "source": "https://www.computesdk.com/benchmarks",
   "quote": "burst of 100: p95 487 ms, 100% started",
   "note": "ComputeSDK sandbox benchmark 2026-08-21",
   "checked": "2026-08-21"
  },
  "usage_api": {
   "value": false,
   "source": "https://lightning.ai/docs/platform/team-management/organizations/manage-costs",
   "quote": "Visit Org settings > Activity to monitor organization costs. This section shows a summary of usage activities and financial transactions. Inspect transactions shows machine types and usage duration.",
   "note": "granularity: account-only; cost: no; Lightning AI provides a web UI (Activity section in Org settings) and Python SDK for controlling Studios/Sandboxes, but no programmatic API to query billable usage per sandbox/VM. The Sandbox Python SDK (lightning.ai/docs/platform/build/sandbox.md) supports create/run/snapshot/file operations but not usage retrieval. Organization and Teamspace SDKs also lack usage endpoints. Usage monitoring is dashboard-only at account/org level, not per-resource via API.",
   "confidence": "high",
   "checked": "2026-10-01"
  }
 },
 "locations": [],
 "locations_source": "https://lightning.ai/docs/platform/security/privacy/data-residency.md",
 "locations_quote": "Lightning AI supports all major US, EU, Asia regions. Additional support can be provided upon request.",
 "locations_checked": "2026-10-01"
}