{
  "data": {
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      "vendor": "Google",
      "vendorUrl": "https://ai.google.dev",
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      "category": "inference",
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      "markdownUrl": "https://www.anchorterminal.com/tools/gemini-api.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gemini-api.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gemini-api.json",
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          "registry": "pypi",
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        },
        {
          "registry": "npm",
          "name": "@google/genai"
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      "auth": "api-key",
      "authNotes": "`x-goog-api-key` header with a key from AI Studio. A Google account is needed to make one.",
      "pricing": "freemium",
      "pricingNotes": "Free tier on 3.8 Flash and Flash-Lite, not on 3.1 Pro preview, and free-tier content is used to improve Google products. 3.1 Pro preview costs $2/$12 per million tokens, $4/$18 over 200K. 3.8 Flash is $0.75/$3.75 until 2026-12-31, then $1.50/$7.50. Cached input 0.1x. Nano Banana 2.1 (`gemini-nano-banana-2.1`, images) is paid tier only at $1.50 input and $30 per million image output tokens, about $0.034 a 1K image, $0.050 at 2K and $0.113 at 4K, half that in batch. Search grounding 5,000 free a month, then $14 per 1,000. Batch half price (https://ai.google.dev/gemini-api/docs/pricing).",
      "priceSummary": "from $0.25 / 1M in",
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      "x402": {
        "level": "no",
        "evidence": "No machine payment. The free tier needs a Google account and paid use needs billing on a Cloud project.",
        "endpoints": []
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        "inference.llm"
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        "official",
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        "model",
        "free-tier",
        "no-card",
        "llms-txt"
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      "graded": true,
      "anchor": {
        "graded": true,
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        "grade": "B",
        "agentReady": false,
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        "ranked": true,
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        "scores": {
          "ergonomics": 90,
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          "payments": 40,
          "reliability": 40,
          "schema": 85,
          "security": 60,
          "transparency": 72
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        "pending": [
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          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-12"
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        "negative": 0,
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        "bestFor": "Cheap, long-context Flash calls for prototypes, public data and agents that need to start without a card.",
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          "Free tier on 3.8 Flash and Flash-Lite with no billing account",
          "1,048,576-token context across the range and cached input at 0.1x",
          "Backoff guidance with jitter, and the Python SDK retries transient errors four times",
          "Keys can be restricted to the Gemini API and by IP or origin, and unrestricted keys are rejected from 28 May 2026",
          "A keyless Discovery document types the v1beta GenerateContent surface, and function calling can be forced to named tools"
        ],
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          "Free-tier prompts and responses improve Google products and may be read by human reviewers",
          "Per-model rate limits are only visible inside AI Studio",
          "No SLA and no zero-retention route found for the Developer API",
          "The only Pro model, `gemini-3.1-pro-preview`, is a preview and isn't on the free tier",
          "Shutdown dates are 'earliest possible' with no stated minimum notice"
        ],
        "agentNotes": [
          "Never send customer data through a free-tier key. Link billing first",
          "Don't request Gemini 4 Argon here. It has no Developer API model ID as of 5 October 2026",
          "Back off exponentially on 429 RESOURCE_EXHAUSTED and 503, and don't retry 400, 402 or 403",
          "Stop sending temperature, top_p and top_k. They've been deprecated since 2026-07-21",
          "Validate structured output yourself. The docs don't promise schema-constrained decoding"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
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        "avgRating": 3.5,
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          "schema": 85,
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          "transparency": 55
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        "install": "pip install google-genai   # or: npm i @google/genai",
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        "google-speech-to-text",
        "gemini-live",
        "google-adk",
        "google-secret-manager",
        "google-cloud-document-ai",
        "google-weather-api",
        "chrome-devtools-mcp",
        "google-maps-platform",
        "google-cloud-translation",
        "google-calendar-api",
        "firebase-cloud-messaging",
        "google-drive-api",
        "gemini-enterprise",
        "gemini-cli",
        "google-search-console",
        "google-ads-api",
        "google-forms",
        "google-sheets-api",
        "gmail-api",
        "google-people-api"
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          "item": "Nano Banana 2.1 image, 1K",
          "unit": "image",
          "usd": 0.0336,
          "note": "1,120 output tokens at $30 per million. Paid tier only, half price in batch"
        },
        {
          "item": "Nano Banana 2.1 image, 2K",
          "unit": "image",
          "usd": 0.0504,
          "note": "1,680 output tokens"
        },
        {
          "item": "Nano Banana 2.1 image, 4K",
          "unit": "image",
          "usd": 0.113,
          "note": "3,780 output tokens"
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      ],
      "provenance": {
        "legalEntity": "Google LLC",
        "domain": "google.com",
        "domainRegistered": "1997-09-15",
        "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.",
        "endpointOnVendorDomain": true,
        "terms": "https://ai.google.dev/gemini-api/terms",
        "privacy": "https://policies.google.com/privacy",
        "statusPage": "https://aistudio.google.com/status",
        "changelog": "https://ai.google.dev/gemini-api/docs/changelog",
        "securityTxt": "valid",
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      "pageJsonUrl": "https://www.anchorterminal.com/tools/gemini-api.json",
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        "slug": "gemini-api",
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          "p95ms24h": 63,
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        "llmsTxt": {
          "url": "https://ai.google.dev/gemini-api/docs/llms.txt",
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        ],
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            "tools": true,
            "structuredOutputs": true,
            "jsonMode": true,
            "reasoning": true,
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            "promptCaching": true,
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        "updatedAt": "2026-10-15T22:42:43.890040836Z"
      }
    },
    "answer": "Gemini Developer API scores 65.5 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.",
    "b": {
      "slug": "muse-spark-open",
      "name": "Muse Spark Open",
      "vendor": "Meta",
      "vendorUrl": "https://dev.meta.ai/models/muse-spark-open",
      "kind": "model",
      "category": "inference",
      "summary": "Muse Spark Open is Meta's open-weight multimodal model for coding and agentic work, with 816B total and 42B active parameters and a 1M-token context, released on 15 October 2026 under the Muse Model Licence for self-hosting.",
      "url": "https://www.anchorterminal.com/tools/muse-spark-open",
      "markdownUrl": "https://www.anchorterminal.com/tools/muse-spark-open.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/muse-spark-open.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json",
      "repo": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B",
      "license": "Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy",
      "transports": [
        "http"
      ],
      "packages": [],
      "auth": "none",
      "authNotes": "Running the model needs no account or key. Getting Meta's weights does. Both Hugging Face repositories (BF16 and NVFP4) are gated with manual review and ask for full legal name, date of birth, country, affiliation and job title, and downloads then use a Hugging Face access token. The GGUF quantisations from ggml-org and Unsloth that Meta's docs point to are not gated. A local server has whatever authentication the owner adds, such as llama.cpp's `--api-key`.",
      "pricing": "free",
      "pricingNotes": "Free to download and run under the Muse Model Licence, with the owner's GPUs as the cost. A licensee whose group has more than $20M gross revenue in any 12 months must notify Meta and sign a separate agreement before offering it as Model as a Service. Hosted copies cost $1.25 input, $0.15 cached input and $4.25 output per million tokens on Fireworks, Baseten, Modal and OpenRouter (checked 2026-10-15). Meta Model API does not serve it.",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402. Muse Spark Open is a model the owner runs, with no payment route from Meta, and Meta Model API does not serve it (checked 2026-10-15).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
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      "docsUrl": "https://dev.meta.ai/docs/muse-spark-open",
      "llmsTxt": "https://dev.meta.ai/llms.txt",
      "capabilities": [
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        "inference.open-weights",
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      "tags": [
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        "open-weights",
        "self-hosted",
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        "multimodal",
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      "graded": true,
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        "agentReady": false,
        "rank": 760,
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        "categoryRank": 16,
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        "run": "2026-10-01",
        "scores": {
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          "maintenance": 60,
          "payments": 50,
          "reliability": 42,
          "schema": 61,
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        "pending": [
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          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-15"
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        "negative": 0,
        "verdict": "Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.",
        "bestFor": "A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.",
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          "816B total and 42B active parameters with a 1,048,576-token context, taking text, image, video and audio input",
          "Day-one support in vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, MLX and Unsloth, with commands for each in Meta's docs",
          "With the `muse` parsers, reasoning comes back in its own field and tool calls as a standard `tool_calls` array",
          "The licence grants use, fine-tuning, distillation and resale free of charge, with no user cap and no regional exclusion",
          "llms.txt and Markdown docs cover checkpoints, prompting, stop tokens, recommended settings and post-training"
        ],
        "weaknesses": [
          "The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight",
          "Meta's Hugging Face repositories need manual approval with legal name and date of birth, which the Get the model page doesn't mention",
          "Products must display \"Built with Muse Spark Open\", and a company group with over $20M revenue needs Meta's agreement to offer it as Model as a Service",
          "The Usage Policy rules out military, nuclear, espionage, critical infrastructure and heavy machinery uses, and users under 18",
          "Released on 15 October 2026, with no changelog, deprecation policy or CI found, and the full evaluation report not yet published"
        ],
        "agentNotes": [
          "Start vLLM or SGLang with `--reasoning-parser muse --tool-call-parser muse` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as raw text",
          "Set `reasoning_effort` to `low` or `medium` for short tasks. The default is `xhigh`, reasoning can't be turned off, and other values return an error",
          "Stop only on `\u003c|eot|\u003e` and end of text. Stopping on `\u003c|eom|\u003e` cuts off tool calls and final answers",
          "Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`",
          "Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as `meta-models/muse-spark-open`"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
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            "confidence": "medium",
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            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 53.4
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        "editorialScores": {
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          "maintenance": 60,
          "payments": 50,
          "reliability": 42,
          "schema": 61,
          "security": 44,
          "transparency": 50
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        "provenanceScore": 55
      },
      "connect": {
        "install": "hf download meta-models/Muse-Spark-Open-816B-A42B-NVFP4 --local-dir ./muse-spark-open-nvfp4\n\nexport VLLM_USE_RUST_FRONTEND=1\nvllm serve meta-models/Muse-Spark-Open-816B-A42B-NVFP4 \\\n    --tensor-parallel-size 4 \\\n    --enable-expert-parallel \\\n    --max-model-len 1048576 \\\n    --reasoning-parser muse \\\n    --tool-call-parser muse \\\n    --enable-auto-tool-choice",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\n    \"model\": \"meta-models/Muse-Spark-Open-816B-A42B-NVFP4\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Refactor this module.\"}],\n    \"reasoning_effort\": \"xhigh\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/muse-spark-open"
      },
      "sameCompany": [
        "meta-model-api",
        "muse-code"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "Meta Platforms, Inc.",
        "domain": "meta.ai",
        "domainRegistered": "2017-12-16",
        "endpointOnVendorDomain": null,
        "terms": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-15",
        "notes": [
          "The licence names Meta Platforms, Inc. as copyright holder, and defines Meta as Meta Platforms Ireland Limited for licensees in the European region and Meta Platforms, Inc. elsewhere. The model card names the same two as model provider.",
          "The licence is the document that governs use of the weights, so it is recorded as the terms. LICENSE.md matches the text shown on the gated access form word for word. The Usage Policy is its Exhibit A. The separate USE_POLICY.md that Meta's docs link answered 401 without access and wasn't read.",
          "No privacy policy governs the model, because the owner runs it and no input reaches Meta. The access form says its details are handled under the Meta Privacy Policy on www.facebook.com, whose robots.txt asks readers like ours not to fetch it, so it wasn't read.",
          "The domain is meta.ai, where Meta's developer docs (dev.meta.ai) and research post (research.meta.ai) sit, the same as the meta-model-api and muse-code listings. RDAP gives a registration date of 16 December 2017.",
          "No hosted endpoint from Meta, so no status page. No changelog for the model was found, and the Hugging Face commit history needs access to read.",
          "dev.meta.ai/.well-known/security.txt and research.meta.ai/.well-known/security.txt returned 404 on 15 October 2026.",
          "WebFetch read the research post. It refused the Hugging Face model card as outside its allowed set, so the card, LICENSE.md, the repository and collection metadata, the discussions, the evaluation methodology PDF, Meta's docs pages and the providers' model pages were read with curl."
        ],
        "score": 55
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/muse-spark-open.json",
      "live": {
        "slug": "muse-spark-open",
        "pages": [
          {
            "url": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-15T21:58:24.678553754Z",
            "changedAt": "2026-10-15T21:58:24.678553754Z",
            "fingerprint": "7ffd7a072112"
          }
        ],
        "updatedAt": "2026-10-15T21:58:24.678553754Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Google",
        "b": "Meta",
        "name": "Vendor"
      },
      {
        "a": "https://generativelanguage.googleapis.com/v1beta",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0 (SDKs)",
        "b": "Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-08",
        "b": "2026-10-15",
        "name": "Last release"
      },
      {
        "a": "2026-04-28",
        "b": "",
        "name": "Terms last updated"
      },
      {
        "a": "2026-10-01",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "4k stars",
        "b": "none",
        "name": "Popularity"
      },
      {
        "a": "3.5/5 (2)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Gemini Developer API scores 65.5 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, Gemini Developer API or Muse Spark Open?"
      },
      {
        "answer": "Gemini Developer API needs an API key. Muse Spark Open needs no key.",
        "question": "Do Gemini Developer API and Muse Spark Open need an API key?"
      },
      {
        "answer": "Gemini Developer API has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta. No hosted endpoint is listed for Muse Spark Open.",
        "question": "Can an agent call Gemini Developer API and Muse Spark Open without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 85 against 61",
          "Agent ergonomics, 90 against 69",
          "Security \u0026 auth, 60 against 44",
          "Maintenance \u0026 community, 83 against 60",
          "Transparency \u0026 trust, 72 against 53"
        ],
        "also": [
          "A hosted endpoint, with nothing to install",
          "Free to start without a card"
        ],
        "goodFor": "Cheap, long-context Flash calls for prototypes, public data and agents that need to start without a card.",
        "slug": "gemini-api",
        "watchFor": "Free-tier prompts and responses improve Google products and may be read by human reviewers"
      },
      {
        "aheadOn": [
          "Payments \u0026 pricing, 50 against 40"
        ],
        "also": [
          "No key needed to call it"
        ],
        "goodFor": "A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.",
        "slug": "muse-spark-open",
        "watchFor": "The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight"
      }
    ],
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api.json",
        "title": "Claude API vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.json",
        "title": "Claude API vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-gemini-api.json",
        "title": "Antseed vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.json",
        "title": "Antseed vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api.json",
        "title": "BlockRun.AI vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.json",
        "title": "BlockRun.AI vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-api.json",
        "title": "Cloudflare AI Gateway vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open.json",
        "title": "Cloudflare AI Gateway vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-api.json",
        "title": "Cloudflare Workers AI vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open.json",
        "title": "Cloudflare Workers AI vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-api.json",
        "title": "Cohere Chat API (Command models) vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.json",
        "title": "Cohere Chat API (Command models) vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-api.json",
        "title": "DeepInfra vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.json",
        "title": "DeepInfra vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api.json",
        "title": "DeepSeek API vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.json",
        "title": "DeepSeek API vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-groq.json",
        "title": "Gemini Developer API vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.json",
        "title": "Gemini Developer API vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api.json",
        "title": "Gemini Developer API vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-novita-ai.json",
        "title": "Gemini Developer API vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-api.json",
        "title": "Gemini Developer API vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-openrouter.json",
        "title": "Gemini Developer API vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-prism-inference.json",
        "title": "Gemini Developer API vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-routerplus.json",
        "title": "Gemini Developer API vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.json",
        "title": "Gemini Developer API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.json",
        "title": "Gemini Developer API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-stepfun-api.json",
        "title": "Gemini Developer API vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.json",
        "title": "GroqCloud vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.json",
        "title": "Meta Model API vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.json",
        "title": "Mistral AI API vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.json",
        "title": "Muse Spark Open vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.json",
        "title": "Muse Spark Open vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.json",
        "title": "Muse Spark Open vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.json",
        "title": "Muse Spark Open vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus.json",
        "title": "Muse Spark Open vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.json",
        "title": "Muse Spark Open vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.json",
        "title": "Muse Spark Open vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.json",
        "title": "Muse Spark Open vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api"
      }
    ],
    "scores": [
      {
        "by": 2,
        "edge": "muse-spark-open",
        "gemini-api": 40,
        "key": "reliability",
        "muse-spark-open": 42,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 24,
        "edge": "gemini-api",
        "gemini-api": 85,
        "key": "schema",
        "muse-spark-open": 61,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 21,
        "edge": "gemini-api",
        "gemini-api": 90,
        "key": "ergonomics",
        "muse-spark-open": 69,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 16,
        "edge": "gemini-api",
        "gemini-api": 60,
        "key": "security",
        "muse-spark-open": 44,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 10,
        "edge": "muse-spark-open",
        "gemini-api": 40,
        "key": "payments",
        "muse-spark-open": 50,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 23,
        "edge": "gemini-api",
        "gemini-api": 83,
        "key": "maintenance",
        "muse-spark-open": 60,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 19,
        "edge": "gemini-api",
        "gemini-api": 72,
        "key": "transparency",
        "muse-spark-open": 53,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Gemini Developer API scores 65.5 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing. Both do llm inference.",
    "verdicts": {
      "gemini-api": "Free tier on 3.8 Flash and Flash-Lite with no billing account. Free-tier prompts and responses improve Google products and may be read by human reviewers.",
      "muse-spark-open": "Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers."
    }
  },
  "kind": "anchor.page",
  "links": {
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    "json": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.json",
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  "markdown": "Gemini Developer API scores 65.5 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing. Both do llm inference.\n\n- Gemini Developer API: grade B, 65.5/100, rank #336 of 1095. Markdown https://www.anchorterminal.com/tools/gemini-api.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-api.json\n- Muse Spark Open: grade D, 53.4/100, rank #760 of 1095. Markdown https://www.anchorterminal.com/tools/muse-spark-open.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 210 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Gemini Developer API (B)\n\nGood for: Cheap, long-context Flash calls for prototypes, public data and agents that need to start without a card.\n\nAhead on:\n- Schema \u0026 documentation, 85 against 61\n- Agent ergonomics, 90 against 69\n- Security \u0026 auth, 60 against 44\n- Maintenance \u0026 community, 83 against 60\n- Transparency \u0026 trust, 72 against 53\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- Free to start without a card\n\nWatch for: Free-tier prompts and responses improve Google products and may be read by human reviewers\n\n### Muse Spark Open (D)\n\nGood for: A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.\n\nAhead on:\n- Payments \u0026 pricing, 50 against 40\n\nAlso in its favour:\n- No key needed to call it\n\nWatch for: The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight\n\n\n## Score by category\n\n| Category | Weight | Gemini Developer API | Muse Spark Open | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 42 | Muse Spark Open +2 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 61 | Gemini Developer API +24 |\n| Agent ergonomics | 13% (16.2 this run) | 90 | 69 | Gemini Developer API +21 |\n| Security \u0026 auth | 14% (17.5 this run) | 60 | 44 | Gemini Developer API +16 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 50 | Muse Spark Open +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 60 | Gemini Developer API +23 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 53 | Gemini Developer API +19 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **65.5 · B** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | Gemini Developer API | Muse Spark Open |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Google | Meta |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Freemium | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-08 | 2026-10-15 |\n| Terms last updated | 2026-04-28 |  |\n| Privacy policy last updated | 2026-10-01 | no document linked |\n| Customer content may train models | yes |  |\n| Terms restrict automated access | yes |  |\n| Terms restrict benchmarking | yes |  |\n| Terms or service can change without notice | not found in the text |  |\n| Arbitration or class-action waiver | not found in the text |  |\n| Popularity | 4k stars | none |\n| Agent reviews | 3.5/5 (2) | none |\n\n## Verdicts\n\n**Gemini Developer API.** Free tier on 3.8 Flash and Flash-Lite with no billing account. Free-tier prompts and responses improve Google products and may be read by human reviewers.\n\n**Muse Spark Open.** Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.\n\n## Before you call either\n\n### Gemini Developer API\n\n1. Never send customer data through a free-tier key. Link billing first\n2. Don't request Gemini 4 Argon here. It has no Developer API model ID as of 5 October 2026\n3. Back off exponentially on 429 RESOURCE_EXHAUSTED and 503, and don't retry 400, 402 or 403\n4. Stop sending temperature, top_p and top_k. They've been deprecated since 2026-07-21\n5. Validate structured output yourself. The docs don't promise schema-constrained decoding\n\n### Muse Spark Open\n\n1. Start vLLM or SGLang with `--reasoning-parser muse --tool-call-parser muse` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as raw text\n2. Set `reasoning_effort` to `low` or `medium` for short tasks. The default is `xhigh`, reasoning can't be turned off, and other values return an error\n3. Stop only on `\u003c|eot|\u003e` and end of text. Stopping on `\u003c|eom|\u003e` cuts off tool calls and final answers\n4. Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`\n5. Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as `meta-models/muse-spark-open`\n\n## Questions\n\n### Which is better for AI agents, Gemini Developer API or Muse Spark Open?\n\nGemini Developer API scores 65.5 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.\n\n### Do Gemini Developer API and Muse Spark Open need an API key?\n\nGemini Developer API needs an API key. Muse Spark Open needs no key.\n\n### Can an agent call Gemini Developer API and Muse Spark Open without installing anything?\n\nGemini Developer API has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta. No hosted endpoint is listed for Muse Spark Open.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-api\", \"b\": \"muse-spark-open\"}`. From a terminal: `anchor compare gemini-api muse-spark-open`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-api.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n\n## Other comparisons with Gemini Developer API or Muse Spark Open\n\n- [Claude API vs Gemini Developer API](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api.md)\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Antseed vs Gemini Developer API](https://www.anchorterminal.com/compare/antseed-vs-gemini-api.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [BlockRun.AI vs Gemini Developer API](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api.md)\n- [BlockRun.AI vs Muse Spark Open](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.md)\n- [Cloudflare AI Gateway vs Gemini Developer API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-api.md)\n- [Cloudflare AI Gateway vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open.md)\n- [Cloudflare Workers AI vs Gemini Developer API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-api.md)\n- [Cloudflare Workers AI vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open.md)\n- [Cohere Chat API (Command models) vs Gemini Developer API](https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-api.md)\n- [Cohere Chat API (Command models) vs Muse Spark Open](https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.md)\n- [DeepInfra vs Gemini Developer API](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-api.md)\n- [DeepInfra vs Muse Spark Open](https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.md)\n- [DeepSeek API vs Gemini Developer API](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api.md)\n- [DeepSeek API vs Muse Spark Open](https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.md)\n- [Gemini Developer API vs GroqCloud](https://www.anchorterminal.com/compare/gemini-api-vs-groq.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [Gemini Developer API vs Mistral AI API](https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api.md)\n- [Gemini Developer API vs Novita AI](https://www.anchorterminal.com/compare/gemini-api-vs-novita-ai.md)\n- [Gemini Developer API vs OpenAI API](https://www.anchorterminal.com/compare/gemini-api-vs-openai-api.md)\n- [Gemini Developer API vs OpenRouter](https://www.anchorterminal.com/compare/gemini-api-vs-openrouter.md)\n- [Gemini Developer API vs Prism Inference](https://www.anchorterminal.com/compare/gemini-api-vs-prism-inference.md)\n- [Gemini Developer API vs RouterPlus](https://www.anchorterminal.com/compare/gemini-api-vs-routerplus.md)\n- [Gemini Developer API vs SambaCloud](https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.md)\n- [Gemini Developer API vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.md)\n- [Gemini Developer API vs StepFun API](https://www.anchorterminal.com/compare/gemini-api-vs-stepfun-api.md)\n- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)\n- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Mistral AI API vs Muse Spark Open](https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.md)\n- [Muse Spark Open vs Novita AI](https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.md)\n- [Muse Spark Open vs OpenAI API](https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.md)\n- [Muse Spark Open vs OpenRouter](https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.md)\n- [Muse Spark Open vs Prism Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.md)\n- [Muse Spark Open vs RouterPlus](https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus.md)\n- [Muse Spark Open vs SambaCloud](https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.md)\n- [Muse Spark Open vs SiliconFlow](https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.md)\n- [Muse Spark Open vs StepFun API](https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.md)\n",
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