{ "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. 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": "2026-09-30", "graded": true, "anchor": { "graded": true, "score": 71.2, "grade": "BB", "agentReady": true, "rank": 130, "ranked": true, "rankOf": 842, "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": "2026-10-01" }, "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 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": [ "Data sent to Labs and preview models may be used for training 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 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": "2026-10-09T11:46:34.554403373Z", "lastOk": true, "lastStatus": 404, "lastMs": 62, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 72, "p95ms24h": 120, "samples24h": 259, "samples30d": 3265, "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": 125, "ok": 125 } ] }, "vendorStatus": { "page": "https://status.mistral.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-09T07:58:10.956755027Z" }, "versions": [ { "registry": "github", "name": "mistralai/client-python", "version": "v3.1.0", "released": "2026-10-06", "seenAt": "2026-10-08T16:21:14.158564322Z" }, { "registry": "npm", "name": "@mistralai/mistralai", "version": "2.7.0", "seenAt": "2026-10-08T16:21:13.179335409Z" }, { "registry": "pypi", "name": "mistralai", "version": "3.1.0", "released": "2026-10-06", "seenAt": "2026-10-08T16:21:13.019182786Z" } ], "githubStars": 773, "npmWeekly": 9359288, "pypiWeekly": 3274123, "securityTxt": { "url": "https://mistral.ai/.well-known/security.txt", "state": "valid", "expires": "2027-05-05T23:59:59.000Z", "checkedAt": "2026-10-08T15:38:55.944328005Z" }, "llmsTxt": { "url": "https://docs.mistral.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:37.25034128Z" }, "domain": { "domain": "mistral.ai", "registered": "2019-05-15", "source": "https://rdap.identitydigital.services/rdap/domain/mistral.ai", "checkedAt": "2026-10-04T13:08:59.683466691Z" }, "pages": [ { "url": "https://docs.mistral.ai/resources/changelogs", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-08T18:19:07.816660656Z", "changedAt": "2026-10-07T18:05:15.998003428Z", "fingerprint": "f37008aff154" }, { "url": "https://legal.mistral.ai/terms/commercial-terms-of-service", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-08T18:21:27.176711468Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "227daf1e9929" }, { "url": "https://mistral.ai/pricing/api/", "kind": "pricing", "status": 304, "checkedAt": "2026-10-08T18:22:04.621353841Z", "changedAt": "2026-10-07T18:07:31.904425325Z", "fingerprint": "a7cad481f8de" }, { "url": "https://legal.mistral.ai/terms/privacy-policy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-08T18:21:29.566811569Z", "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": "2026-10-08T22:59:28.345696683Z" }, "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": "2026-10-08T22:59:28.345696683Z" }, "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": "2026-10-08T22:59:28.345696683Z" }, "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": "2026-10-08T22:59:28.345696683Z" } }, "updatedAt": "2026-10-09T11:46:34.554403373Z" } }, "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against SambaCloud's 66.4 (B), and leads in 5 of 7 scored categories. SambaCloud leads on reliability.", "b": { "slug": "sambanova", "name": "SambaCloud", "vendor": "SambaNova Systems, Inc.", "vendorUrl": "https://sambanova.ai", "kind": "model", "category": "inference", "summary": "SambaCloud is SambaNova's hosted inference API for open-weight models running on its own RDU processors. It answers OpenAI-style chat, completions and Responses calls and Anthropic-style Messages calls, with Python and TypeScript SDKs.", "url": "https://www.anchorterminal.com/tools/sambanova", "markdownUrl": "https://www.anchorterminal.com/tools/sambanova.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/sambanova.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/sambanova.json", "repo": "https://github.com/sambanova/sambanova-python", "license": "Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://api.sambanova.ai/v1", "packages": [ { "registry": "pypi", "name": "sambanova" }, { "registry": "npm", "name": "sambanova" } ], "auth": "api-key", "authNotes": "Self-serve Bearer key from the SambaCloud console at https://cloud.sambanova.ai/apis after a browser sign-up. The Messages routes also take the same key in `x-api-key`. Up to 25 keys per user, shown once, with no scopes.", "pricing": "freemium", "pricingNotes": "Free tier with no payment method, at 20 requests a minute, 20 requests a day and 200,000 tokens a day per model. Linking a card moves the account to the Developer tier, billed per token through Stripe, from $0.22 in and $0.59 out per 1M tokens on gpt-oss-120b (https://cloud.sambanova.ai/plans/pricing, checked 2026-10-08).", "priceSummary": "from $0.22 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI document or the pricing page (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 2, "npmWeekly": 76, "pypiWeekly": 6129, "asOf": "2026-10-08" }, "docsUrl": "https://docs.sambanova.ai/docs/en/get-started/overview", "rateLimitsUrl": "https://docs.sambanova.ai/docs/en/models/rate-limits", "llmsTxt": "https://docs.sambanova.ai/docs/llms.txt", "openapi": "https://raw.githubusercontent.com/sambanova/sambanova-inference-api-spec/refs/heads/main/openapi.documented.json", "capabilities": [ "inference.llm", "inference.open-weights", "inference.fast" ], "tags": [ "hosted", "model", "open-weights", "free-tier", "no-card", "openapi", "llms-txt", "openai-compatible", "anthropic-compatible", "python", "typescript", "status-page", "soc2" ], "lastRelease": "2026-09-17", "graded": true, "anchor": { "graded": true, "score": 66.4, "grade": "B", "agentReady": false, "rank": 269, "ranked": true, "rankOf": 842, "categoryRank": 7, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 77, "payments": 40, "reliability": 85, "schema": 81, "security": 58, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": -2, "negativeNotes": [ "2026-10-08. The models and rate-limit pages list `MiniMax-M2.7` as a production model, and the July 2026 release notes say `Mistral-Large-3-675B-Instruct-2512` was promoted to production. Neither is on the pricing page or in `/v1/models`, and the deprecations page records neither. Two points, since a keyed call was not made to confirm the ids fail (https://docs.sambanova.ai/docs/en/models/sambacloud-models, https://api.sambanova.ai/v1/models)." ], "verdict": "Per-token prices and the model list are readable without a key at `/v1/models`, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7.", "bestFor": "Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.", "strengths": [ "Public OpenAPI 3.1.1 document for all 10 operations, plus `llms.txt` and a Markdown copy of every docs page", "`GET /v1/models` answers without a key and returns context length, output cap and per-token prices for each model", "Free tier with no payment method at 20 requests a minute, 20 requests a day and 200,000 tokens a day per model", "One key works with the OpenAI client, the Anthropic client (`/v1/messages`, `x-api-key`) and SambaNova's own SDKs", "Status page with a component per model and no incident posted since 25 June 2026" ], "weaknesses": [ "Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026", "The docs list `MiniMax-M2.7` as a production model, while the pricing page and `/v1/models` did not list it on 8 October 2026", "`strict: true` on a JSON schema is accepted and has no effect, and the July 2026 notes record failing structured output on DeepSeek-V3.2", "Keys carry no scopes or project limits, and no key rotation guidance was found in the reviewed documentation", "The privacy policy is dated 27 May 2023, and no DPA, retention period or sub-processor list was found on the legal page" ], "agentNotes": [ "Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs name models the endpoint no longer lists", "Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model", "Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model", "Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing", "Check `max_completion_tokens` per model. DeepSeek-V3.1 caps output at 7,168 tokens and Llama 3.3 70B at 3,072" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66.4 } ], "editorialScores": { "ergonomics": 67, "maintenance": 77, "payments": 40, "reliability": 85, "schema": 81, "security": 58, "transparency": 44 }, "provenanceScore": 81 }, "connect": { "install": "pip install sambanova # or: npm install sambanova", "http": "curl https://api.sambanova.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $SAMBANOVA_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"gpt-oss-120b\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/sambanova" }, "area": "models", "provenance": { "legalEntity": "SambaNova Systems, Inc.", "domain": "sambanova.ai", "domainRegistered": "2017-12-18", "endpointOnVendorDomain": true, "terms": "https://sambanova.ai/cloud-end-user-license-agreement", "privacy": "https://sambanova.ai/privacy-policy", "statusPage": "https://status.sambanova.ai", "changelog": "https://docs.sambanova.ai/docs/en/release-notes/sambacloud", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The SambaCloud Terms of Service name SambaNova Systems, Inc., a Delaware corporation at 2460 N. First St, Suite #100, San Jose, CA 95131, and define the Service as the SambaCloud platform. The page carries no date. The legal index says it was last updated on 5 February 2026.", "The privacy policy is the company's only one. Its last revision is dated 27 May 2023, it covers the website, communications and related services, and it does not name SambaCloud or API inputs.", "No DPA, SLA, acceptable use policy or sub-processor list is linked from https://sambanova.ai/legal-agreements.", "https://sambanova.ai/.well-known/security.txt returns 404.", "RDAP for sambanova.ai gives a registration date of 2017-12-18.", "The API answers at api.sambanova.ai and the console at cloud.sambanova.ai." ], "score": 81 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/sambanova.json", "live": { "slug": "sambanova", "probe": { "target": "https://api.sambanova.ai/v1", "method": "get", "lastAt": "2026-10-09T11:46:39.537400402Z", "lastOk": true, "lastStatus": 405, "lastMs": 408, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 403, "p95ms24h": 1118, "samples24h": 44, "samples30d": 44, "days": [ { "date": "2026-10-09", "probes": 44, "ok": 44 } ] }, "vendorStatus": { "page": "https://status.sambanova.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-09T11:40:38.07700378Z" }, "updatedAt": "2026-10-09T11:46:39.537400402Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Mistral AI", "b": "SambaNova Systems, Inc.", "name": "Vendor" }, { "a": "https://api.mistral.ai/v1", "b": "https://api.sambanova.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Freemium", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (SDKs)", "b": "Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-09-30", "b": "2026-09-17", "name": "Last release" }, { "a": "2026-09-25", "b": "no date given", "name": "Terms last updated" }, { "a": "2026-09-03", "b": "2023-05-27", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "769 stars", "b": "2 stars, 76 npm/wk, 6.1k PyPI/wk", "name": "Popularity" }, { "a": "4/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against SambaCloud's 66.4 (B), and leads in 5 of 7 scored categories. SambaCloud leads on reliability.", "question": "Which is better for AI agents, Mistral AI API or SambaCloud?" }, { "answer": "Both need an API key.", "question": "Do Mistral AI API and SambaCloud need an API key?" }, { "answer": "Yes. Mistral AI API has a hosted endpoint at https://api.mistral.ai/v1 and SambaCloud at https://api.sambanova.ai/v1.", "question": "Can an agent call Mistral AI API and SambaCloud without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 93 against 81", "Agent ergonomics, 91 against 67", "Security \u0026 auth, 66 against 58", "Maintenance \u0026 community, 88 against 77", "Transparency \u0026 trust, 80 against 63" ], "also": [ "Agent-ready, a grade of BB or better" ], "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": "Data sent to Labs and preview models may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting" }, { "aheadOn": [ "Reliability, 85 against 50" ], "also": [ "Free to start without a card" ], "goodFor": "Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.", "slug": "sambanova", "watchFor": "Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026" } ], "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-sambanova.json", "title": "Claude API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova" }, { "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-sambanova.json", "title": "Antseed vs SambaCloud", "url": "https://www.anchorterminal.com/compare/antseed-vs-sambanova" }, { "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-sambanova.json", "title": "BlockRun.AI vs SambaCloud", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova" }, { "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-sambanova.json", "title": "DeepInfra vs SambaCloud", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-sambanova" }, { "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-sambanova.json", "title": "DeepSeek API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova" }, { "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-sambanova.json", "title": "Gemini Developer API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova" }, { "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-sambanova.json", "title": "GroqCloud vs SambaCloud", "url": "https://www.anchorterminal.com/compare/groq-vs-sambanova" }, { "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/openai-api-vs-sambanova.json", "title": "OpenAI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-sambanova.json", "title": "OpenRouter vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openrouter-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.json", "title": "Prism Inference vs SambaCloud", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-sambanova" } ], "scores": [ { "by": 35, "edge": "sambanova", "key": "reliability", "mistral-api": 50, "name": "Reliability", "sambanova": 85, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 12, "edge": "mistral-api", "key": "schema", "mistral-api": 93, "name": "Schema \u0026 documentation", "sambanova": 81, "weight": 13 }, { "by": 24, "edge": "mistral-api", "key": "ergonomics", "mistral-api": 91, "name": "Agent ergonomics", "sambanova": 67, "weight": 13 }, { "by": 8, "edge": "mistral-api", "key": "security", "mistral-api": 66, "name": "Security \u0026 auth", "sambanova": 58, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "mistral-api": 40, "name": "Payments \u0026 pricing", "sambanova": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 11, "edge": "mistral-api", "key": "maintenance", "mistral-api": 88, "name": "Maintenance \u0026 community", "sambanova": 77, "weight": 7 }, { "by": 17, "edge": "mistral-api", "key": "transparency", "mistral-api": 80, "name": "Transparency \u0026 trust", "sambanova": 63, "weight": 7 } ], "summary": "Mistral AI API scores 71.2 (BB) on agent readiness against SambaCloud's 66.4 (B), and leads in 5 of 7 scored categories. SambaCloud leads on reliability. 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 may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.", "sambanova": "Per-token prices and the model list are readable without a key at `/v1/models`, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova", "json": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.md", "slim": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.min.md" }, "markdown": "Mistral AI API scores 71.2 (BB) on agent readiness against SambaCloud's 66.4 (B), and leads in 5 of 7 scored categories. SambaCloud leads on reliability. Both do llm inference.\n\n- Mistral AI API: grade BB, 71.2/100, rank #130 of 842. Markdown https://www.anchorterminal.com/tools/mistral-api.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-api.json\n- SambaCloud: grade B, 66.4/100, rank #269 of 842. Markdown https://www.anchorterminal.com/tools/sambanova.md · JSON https://www.anchorterminal.com/api/v1/tools/sambanova.json\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- Schema \u0026 documentation, 93 against 81\n- Agent ergonomics, 91 against 67\n- Security \u0026 auth, 66 against 58\n- Maintenance \u0026 community, 88 against 77\n- Transparency \u0026 trust, 80 against 63\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Data sent to Labs and preview models may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting\n\n### SambaCloud (B)\n\nGood for: Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.\n\nAhead on:\n- Reliability, 85 against 50\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026\n\n\n## Score by category\n\n| Category | Weight | Mistral AI API | SambaCloud | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 85 | SambaCloud +35 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 81 | Mistral AI API +12 |\n| Agent ergonomics | 13% (16.2 this run) | 91 | 67 | Mistral AI API +24 |\n| Security \u0026 auth | 14% (17.5 this run) | 66 | 58 | Mistral AI API +8 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 40 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 88 | 77 | Mistral AI API +11 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 80 | 63 | Mistral AI API +17 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **71.2 · BB** | **66.4 · B** | |\n\n## Facts side by side\n\n| Fact | Mistral AI API | SambaCloud |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Mistral AI | SambaNova Systems, Inc. |\n| Hosted endpoint | `https://api.mistral.ai/v1` | `https://api.sambanova.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-30 | 2026-09-17 |\n| Terms last updated | 2026-09-25 | no date given |\n| Privacy policy last updated | 2026-09-03 | 2023-05-27 |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 769 stars | 2 stars, 76 npm/wk, 6.1k PyPI/wk |\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 may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.\n\n**SambaCloud.** Per-token prices and the model list are readable without a key at `/v1/models`, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7.\n\n## Before you call either\n\n### Mistral AI API\n\n1. Stay off `labs-*` and preview models 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### SambaCloud\n\n1. Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs name models the endpoint no longer lists\n2. Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model\n3. Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model\n4. Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing\n5. Check `max_completion_tokens` per model. DeepSeek-V3.1 caps output at 7,168 tokens and Llama 3.3 70B at 3,072\n\n## Questions\n\n### Which is better for AI agents, Mistral AI API or SambaCloud?\n\nMistral AI API scores 71.2 (BB) on agent readiness against SambaCloud's 66.4 (B), and leads in 5 of 7 scored categories. SambaCloud leads on reliability.\n\n### Do Mistral AI API and SambaCloud need an API key?\n\nBoth need an API key.\n\n### Can an agent call Mistral AI API and SambaCloud without installing anything?\n\nYes. Mistral AI API has a hosted endpoint at https://api.mistral.ai/v1 and SambaCloud at https://api.sambanova.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"mistral-api\", \"b\": \"sambanova\"}`. From a terminal: `anchor compare mistral-api sambanova`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mistral-api.json and https://www.anchorterminal.com/api/v1/tools/sambanova.json\n\n## Other comparisons with Mistral AI API or SambaCloud\n\n- [Claude API vs Mistral AI API](https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.md)\n- [Claude API vs SambaCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.md)\n- [Antseed vs Mistral AI API](https://www.anchorterminal.com/compare/antseed-vs-mistral-api.md)\n- [Antseed vs SambaCloud](https://www.anchorterminal.com/compare/antseed-vs-sambanova.md)\n- [BlockRun.AI vs Mistral AI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.md)\n- [BlockRun.AI vs SambaCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.md)\n- [DeepInfra vs Mistral AI API](https://www.anchorterminal.com/compare/deepinfra-vs-mistral-api.md)\n- [DeepInfra vs SambaCloud](https://www.anchorterminal.com/compare/deepinfra-vs-sambanova.md)\n- [DeepSeek API vs Mistral AI API](https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.md)\n- [DeepSeek API vs SambaCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.md)\n- [GroqCloud vs Mistral AI API](https://www.anchorterminal.com/compare/groq-vs-mistral-api.md)\n- [GroqCloud vs SambaCloud](https://www.anchorterminal.com/compare/groq-vs-sambanova.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- [OpenAI API vs SambaCloud](https://www.anchorterminal.com/compare/openai-api-vs-sambanova.md)\n- [OpenRouter vs SambaCloud](https://www.anchorterminal.com/compare/openrouter-vs-sambanova.md)\n- [Prism Inference vs SambaCloud](https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "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" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Mistral AI API vs SambaCloud", "url": "" } ], "description": "Mistral AI API scores 71.2 (BB) on agent readiness against SambaCloud's 66.4 (B), and leads in 5 of 7 scored categories. SambaCloud leads on reliability. Both do llm inference. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Mistral AI API BB 71.2", "SambaCloud B 66.4", "scores" ], "h1": "Mistral AI API vs SambaCloud", "image": "https://www.anchorterminal.com/assets/og/compare-mistral-api-vs-sambanova.png", "path": "/compare/mistral-api-vs-sambanova", "published": "2026-10-01", "section": "tools", "title": "Mistral AI API vs SambaCloud for AI agents, BB 71.2 vs B 66.4", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova" }, "tokens": { "markdown": 2250, "slim": 630 }, "version": 1 }