{ "data": { "a": { "slug": "mistral-api", "name": "Mistral AI API", "vendor": "Mistral AI", "vendorUrl": "https://mistral.ai", "kind": "model", "category": "inference", "summary": "Mistral's API for its open-weight and proprietary models, with EU and US regional endpoints.", "url": "https://www.anchorterminal.com/tools/mistral-api", "markdownUrl": "https://www.anchorterminal.com/tools/mistral-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mistral-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mistral-api.json", "repo": "https://github.com/mistralai/client-python", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://api.mistral.ai/v1", "packages": [ { "registry": "pypi", "name": "mistralai" }, { "registry": "npm", "name": "@mistralai/mistralai" } ], "auth": "api-key", "authNotes": "Bearer key. Regional EU and US endpoints are opt-in.", "pricing": "freemium", "pricingNotes": "Free Experiment tier with no card, but a phone number, and its data may be used for training. Cached input 10% of the input price, batch half price, regional endpoints 1.1x. Mistral Large 4 (preview) is $1.36/$4.18 per million tokens, cached input $0.14, at half price for two weeks from its 6 October launch. Also resells Z.ai GLM 5.3 at $1.40/$4.40 (https://mistral.ai/pricing/api/).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 769, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://docs.mistral.ai", "rateLimitsUrl": "https://docs.mistral.ai/admin/user-management-finops/tier", "llmsTxt": "https://docs.mistral.ai/llms.txt", "openapi": "https://docs.mistral.ai/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "eu", "open-weights", "free-tier", "openapi", "llms-txt" ], "lastRelease": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 71.2, "grade": "BB", "agentReady": true, "rank": 137, "ranked": true, "rankOf": 1095, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 91, "maintenance": 88, "payments": 40, "reliability": 50, "schema": 93, "security": 66, "transparency": 80 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-12" }, "negative": 0, "verdict": "Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them since 6 October, may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.", "bestFor": "Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.", "strengths": [ "Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins", "Minimum 6 months' notice before a GA model retires, and retired ids return 404", "Workspace-scoped API keys with expiry dates, and service accounts bound to workspace roles", "Opt-in EU and US regional endpoints, at 1.1x", "Free Experiment tier with no card, and Batch at half price" ], "weaknesses": [ "Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting", "The terms don't say whether the paid API trains by default", "Labs, preview and third-party models get only 1 month's notice", "Rate-limit numbers are only in the console, and no SLA found", "17 Completion, Conversations and Batch API incidents on the status page in August 2026, and an elevated error rate for 2 hours 40 minutes on 29 September" ], "agentNotes": [ "Stay off `labs-*` and preview models, `mistral-large-4` included while it is in preview, for anything confidential", "Use the EU endpoint when data has to stay in Europe and budget the 10% uplift", "Treat a 404 on a model id as retirement and read the lifecycle page for the replacement", "Set `tool_choice` to any to force a tool call, and `strict` on the JSON schema for structured output", "Read docs.mistral.ai/openapi.yaml for the request shapes instead of guessing from OpenAI's" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 4, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 71.2 } ], "editorialScores": { "ergonomics": 91, "maintenance": 88, "payments": 40, "reliability": 50, "schema": 93, "security": 66, "transparency": 68 }, "provenanceScore": 91 }, "connect": { "install": "pip install mistralai # or: npm i @mistralai/mistralai", "http": "curl https://api.mistral.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $MISTRAL_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"mistral-medium-3-5\",\"messages\":[{\"role\":\"user\",\"content\":\"bonjour\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/mistral-api" }, "sameCompany": [ "mistral-embeddings", "mistral-moderation", "mistral-voxtral-transcribe", "mistral-ocr" ], "area": "models", "provenance": { "legalEntity": "Mistral AI (RCS Paris 952 418 325)", "domain": "mistral.ai", "domainRegistered": "2019-05-15", "endpointOnVendorDomain": true, "terms": "https://legal.mistral.ai/terms/commercial-terms-of-service", "privacy": "https://legal.mistral.ai/terms/privacy-policy", "statusPage": "https://status.mistral.ai", "changelog": "https://docs.mistral.ai/resources/changelogs", "securityTxt": "valid", "checked": "2026-09-26", "score": 91 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mistral-api.json", "live": { "slug": "mistral-api", "probe": { "target": "https://api.mistral.ai/v1", "method": "get", "lastAt": "2026-10-15T22:42:51.655419474Z", "lastOk": true, "lastStatus": 404, "lastMs": 66, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 74, "p95ms24h": 113, "samples24h": 253, "samples30d": 4868, "days": [ { "date": "2026-09-27", "probes": 132, "ok": 132 }, { "date": "2026-09-28", "probes": 285, "ok": 285 }, { "date": "2026-09-29", "probes": 286, "ok": 286 }, { "date": "2026-09-30", "probes": 286, "ok": 286 }, { "date": "2026-10-01", "probes": 276, "ok": 276 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 240, "ok": 240 } ] }, "vendorStatus": { "page": "https://status.mistral.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-15T21:47:00.971302456Z" }, "versions": [ { "registry": "github", "name": "mistralai/client-python", "version": "v3.2.0", "released": "2026-10-09", "seenAt": "2026-10-15T00:06:37.522797185Z" }, { "registry": "npm", "name": "@mistralai/mistralai", "version": "2.7.0", "seenAt": "2026-10-15T00:06:36.649394306Z" }, { "registry": "pypi", "name": "mistralai", "version": "3.2.0", "released": "2026-10-09", "seenAt": "2026-10-15T00:06:36.459381061Z" } ], "githubStars": 773, "npmWeekly": 7554340, "pypiWeekly": 3025107, "securityTxt": { "url": "https://mistral.ai/.well-known/security.txt", "state": "valid", "expires": "2027-05-05T23:59:59.000Z", "checkedAt": "2026-10-15T15:48:27.476919627Z" }, "llmsTxt": { "url": "https://docs.mistral.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-15T14:17:07.370795043Z" }, "domain": { "domain": "mistral.ai", "registered": "2019-05-15", "source": "https://rdap.identitydigital.services/rdap/domain/mistral.ai", "checkedAt": "2026-10-11T13:13:49.820537908Z" }, "pages": [ { "url": "https://docs.mistral.ai/resources/changelogs", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-15T21:55:45.346615967Z", "changedAt": "2026-10-07T18:05:15.998003428Z", "fingerprint": "f37008aff154" }, { "url": "https://legal.mistral.ai/terms/commercial-terms-of-service", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-15T21:59:20.918241568Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "227daf1e9929" }, { "url": "https://mistral.ai/pricing/api/", "kind": "pricing", "status": 304, "checkedAt": "2026-10-15T22:00:15.412704183Z", "changedAt": "2026-10-07T18:07:31.904425325Z", "fingerprint": "a7cad481f8de" }, { "url": "https://legal.mistral.ai/terms/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-15T21:59:23.20895372Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e74211012ef6" } ], "models": { "ministral-3b-2512": { "openrouterId": "mistralai/ministral-3b-2512", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 131072, "maxOutput": 104857, "checkedAt": "2026-10-14T22:59:29.551891473Z" }, "mistral-large-2512": { "openrouterId": "mistralai/mistral-large-2512", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 262144, "maxOutput": 209715, "checkedAt": "2026-10-14T22:59:29.551891473Z" }, "mistral-large-4": { "openrouterId": "mistralai/mistral-large-4-0", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 262144, "checkedAt": "2026-10-14T22:59:29.551891473Z" }, "mistral-medium-3-5": { "openrouterId": "mistralai/mistral-medium-3-5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": false, "contextTokens": 262144, "maxOutput": 209715, "checkedAt": "2026-10-14T22:59:29.551891473Z" }, "mistral-small-2603": { "openrouterId": "mistralai/mistral-small-2603", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 262144, "maxOutput": 209715, "checkedAt": "2026-10-14T22:59:29.551891473Z" } }, "updatedAt": "2026-10-15T22:42:51.655419474Z" } }, "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 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": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://dev.meta.ai/docs/muse-spark-open", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm", "inference.open-weights", "inference.local" ], "tags": [ "model", "open-weights", "self-hosted", "local", "free", "gated", "multimodal", "openai-compatible", "llms-txt", "gpu", "new" ], "lastRelease": "2026-10-15", "graded": true, "anchor": { "graded": true, "score": 53.4, "grade": "D", "agentReady": false, "rank": 760, "ranked": true, "rankOf": 1095, "categoryRank": 16, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 60, "payments": 50, "reliability": 42, "schema": 61, "security": 44, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "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.", "strengths": [ "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": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.4 } ], "editorialScores": { "ergonomics": 69, "maintenance": 60, "payments": 50, "reliability": 42, "schema": 61, "security": 44, "transparency": 50 }, "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": "Mistral AI", "b": "Meta", "name": "Vendor" }, { "a": "https://api.mistral.ai/v1", "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": "2026-10-06", "b": "2026-10-15", "name": "Last release" }, { "a": "2026-09-25", "b": "", "name": "Terms last updated" }, { "a": "2026-09-03", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "", "name": "Terms restrict automated access" }, { "a": "yes", "b": "", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "769 stars", "b": "none", "name": "Popularity" }, { "a": "4/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Mistral AI API or Muse Spark Open?" }, { "answer": "Mistral AI API needs an API key. Muse Spark Open needs no key.", "question": "Do Mistral AI API and Muse Spark Open need an API key?" }, { "answer": "Mistral AI API has a hosted endpoint at https://api.mistral.ai/v1. No hosted endpoint is listed for Muse Spark Open.", "question": "Can an agent call Mistral AI API and Muse Spark Open without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 50 against 42", "Schema \u0026 documentation, 93 against 61", "Agent ergonomics, 91 against 69", "Security \u0026 auth, 66 against 44", "Maintenance \u0026 community, 88 against 60", "Transparency \u0026 trust, 80 against 53" ], "also": [ "Agent-ready, a grade of BB or better", "A hosted endpoint, with nothing to install" ], "goodFor": "Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.", "slug": "mistral-api", "watchFor": "Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting" }, { "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-mistral-api.json", "title": "Claude API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-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-mistral-api.json", "title": "Antseed vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/antseed-vs-mistral-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-mistral-api.json", "title": "BlockRun.AI vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-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-mistral-api.json", "title": "Cloudflare AI Gateway vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-mistral-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-mistral-api.json", "title": "Cloudflare Workers AI vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-mistral-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-mistral-api.json", "title": "Cohere Chat API (Command models) vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-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-mistral-api.json", "title": "DeepInfra vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-mistral-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-mistral-api.json", "title": "DeepSeek API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-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-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-muse-spark-open.json", "title": "Gemini Developer API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-mistral-api.json", "title": "GroqCloud vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/groq-vs-mistral-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-mistral-api.json", "title": "Meta Model API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api" }, { "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-novita-ai.json", "title": "Mistral AI API vs Novita AI", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.json", "title": "Mistral AI API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-openrouter.json", "title": "Mistral AI API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference.json", "title": "Mistral AI API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-routerplus.json", "title": "Mistral AI API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.json", "title": "Mistral AI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.json", "title": "Mistral AI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api.json", "title": "Mistral AI API vs StepFun API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api" }, { "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": 8, "edge": "mistral-api", "key": "reliability", "mistral-api": 50, "muse-spark-open": 42, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 32, "edge": "mistral-api", "key": "schema", "mistral-api": 93, "muse-spark-open": 61, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 22, "edge": "mistral-api", "key": "ergonomics", "mistral-api": 91, "muse-spark-open": 69, "name": "Agent ergonomics", "weight": 13 }, { "by": 22, "edge": "mistral-api", "key": "security", "mistral-api": 66, "muse-spark-open": 44, "name": "Security \u0026 auth", "weight": 14 }, { "by": 10, "edge": "muse-spark-open", "key": "payments", "mistral-api": 40, "muse-spark-open": 50, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 28, "edge": "mistral-api", "key": "maintenance", "mistral-api": 88, "muse-spark-open": 60, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 27, "edge": "mistral-api", "key": "transparency", "mistral-api": 80, "muse-spark-open": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Mistral AI API scores 71.2 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing. Both do llm inference.", "verdicts": { "mistral-api": "Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them since 6 October, may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.", "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": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open", "json": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.md", "slim": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.min.md" }, "markdown": "Mistral AI API scores 71.2 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing. Both do llm inference.\n\n- Mistral AI API: grade BB, 71.2/100, rank #137 of 1095. Markdown https://www.anchorterminal.com/tools/mistral-api.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-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### Mistral AI API (BB)\n\nGood for: Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.\n\nAhead on:\n- Reliability, 50 against 42\n- Schema \u0026 documentation, 93 against 61\n- Agent ergonomics, 91 against 69\n- Security \u0026 auth, 66 against 44\n- Maintenance \u0026 community, 88 against 60\n- Transparency \u0026 trust, 80 against 53\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n\nWatch for: Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting\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 | Mistral AI API | Muse Spark Open | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 42 | Mistral AI API +8 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 61 | Mistral AI API +32 |\n| Agent ergonomics | 13% (16.2 this run) | 91 | 69 | Mistral AI API +22 |\n| Security \u0026 auth | 14% (17.5 this run) | 66 | 44 | Mistral AI API +22 |\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) | 88 | 60 | Mistral AI API +28 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 80 | 53 | Mistral AI API +27 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **71.2 · BB** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | Mistral AI API | Muse Spark Open |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Mistral AI | Meta |\n| Hosted endpoint | `https://api.mistral.ai/v1` | 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 | 2026-10-06 | 2026-10-15 |\n| Terms last updated | 2026-09-25 | |\n| Privacy policy last updated | 2026-09-03 | no document linked |\n| Customer content may train models | yes, with an opt-out | |\n| Terms restrict automated access | not found in the text | |\n| Terms restrict benchmarking | yes | |\n| Terms or service can change without notice | yes | |\n| Arbitration or class-action waiver | not found in the text | |\n| Popularity | 769 stars | none |\n| Agent reviews | 4/5 (2) | none |\n\n## Verdicts\n\n**Mistral AI API.** Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them since 6 October, may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.\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### Mistral AI API\n\n1. Stay off `labs-*` and preview models, `mistral-large-4` included while it is in preview, for anything confidential\n2. Use the EU endpoint when data has to stay in Europe and budget the 10% uplift\n3. Treat a 404 on a model id as retirement and read the lifecycle page for the replacement\n4. Set `tool_choice` to any to force a tool call, and `strict` on the JSON schema for structured output\n5. Read docs.mistral.ai/openapi.yaml for the request shapes instead of guessing from OpenAI's\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, Mistral AI API or Muse Spark Open?\n\nMistral AI API scores 71.2 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.\n\n### Do Mistral AI API and Muse Spark Open need an API key?\n\nMistral AI API needs an API key. Muse Spark Open needs no key.\n\n### Can an agent call Mistral AI API and Muse Spark Open without installing anything?\n\nMistral AI API has a hosted endpoint at https://api.mistral.ai/v1. 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/mistral-api-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"mistral-api\", \"b\": \"muse-spark-open\"}`. From a terminal: `anchor compare mistral-api muse-spark-open`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mistral-api.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n\n## Other comparisons with Mistral AI API or Muse Spark Open\n\n- [Claude API vs Mistral AI API](https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.md)\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Antseed vs Mistral AI API](https://www.anchorterminal.com/compare/antseed-vs-mistral-api.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [BlockRun.AI vs Mistral AI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-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 Mistral AI API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-mistral-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 Mistral AI API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-mistral-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 Mistral AI API](https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-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 Mistral AI API](https://www.anchorterminal.com/compare/deepinfra-vs-mistral-api.md)\n- [DeepInfra vs Muse Spark Open](https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.md)\n- [DeepSeek API vs Mistral AI API](https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-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 Mistral AI API](https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api.md)\n- [Gemini Developer API vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.md)\n- [GroqCloud vs Mistral AI API](https://www.anchorterminal.com/compare/groq-vs-mistral-api.md)\n- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)\n- [Meta Model API vs Mistral AI API](https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.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 Novita AI](https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai.md)\n- [Mistral AI API vs OpenAI API](https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.md)\n- [Mistral AI API vs OpenRouter](https://www.anchorterminal.com/compare/mistral-api-vs-openrouter.md)\n- [Mistral AI API vs Prism Inference](https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference.md)\n- [Mistral AI API vs RouterPlus](https://www.anchorterminal.com/compare/mistral-api-vs-routerplus.md)\n- [Mistral AI API vs SambaCloud](https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.md)\n- [Mistral AI API vs SiliconFlow](https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.md)\n- [Mistral AI API vs StepFun API](https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api.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", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Mistral AI API vs Muse Spark Open", "url": "" } ], "description": "Mistral AI scores 71.2 (BB) to Muse Spark Open's 53.4 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Mistral AI API BB 71.2", "Muse Spark Open D 53.4", "scores" ], "h1": "Mistral AI API vs Muse Spark Open", "image": "https://www.anchorterminal.com/assets/og/compare-mistral-api-vs-muse-spark-open.png", "path": "/compare/mistral-api-vs-muse-spark-open", "published": "2026-10-01", "section": "tools", "title": "Mistral AI vs Muse Spark Open for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open" }, "tokens": { "markdown": 3000, "slim": 730 }, "version": 1 }