{
  "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": 112,
        "ranked": true,
        "rankOf": 629,
        "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-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": "2026-10-08T19:08:53.3959162Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 72,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 76,
          "p95ms24h": 154,
          "samples24h": 272,
          "samples30d": 3089,
          "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": 217,
              "ok": 217
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.mistral.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-08T17:50:52.480495922Z"
        },
        "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": "2026-10-07T22:59:28.227561634Z"
          },
          "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": "2026-10-07T22:59:28.227561634Z"
          },
          "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": "2026-10-07T22:59:28.227561634Z"
          },
          "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": "2026-10-07T22:59:28.227561634Z"
          }
        },
        "updatedAt": "2026-10-08T19:08:53.3959162Z"
      }
    },
    "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against Prism Inference's 60.1 (C), and leads in 6 of 7 scored categories. Prism Inference leads on reliability.",
    "b": {
      "slug": "prism-inference",
      "name": "Prism Inference",
      "vendor": "Prism Technologies Inc",
      "vendorUrl": "https://prisminference.com",
      "kind": "model",
      "category": "inference",
      "summary": "Prism is a hosted inference API from Prism Technologies Inc for open-weight models, aimed at coding agents. It accepts OpenAI Chat Completions, OpenAI Responses and Anthropic Messages requests at api.prisminference.com. It launched on 24 September 2026.",
      "url": "https://www.anchorterminal.com/tools/prism-inference",
      "markdownUrl": "https://www.anchorterminal.com/tools/prism-inference.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/prism-inference.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/prism-inference.json",
      "repo": "https://github.com/prismhq/hermes-prism-provider",
      "license": "Proprietary service under Prism's terms of service. The OpenAPI file declares `LicenseRef-Proprietary`. The Hermes provider plugin repository carries no licence file",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.prisminference.com/v1",
      "packages": [],
      "auth": "api-key",
      "authNotes": "`Authorization: Bearer` with a key issued from account settings after sign-up at prisminference.com/signup. The inference endpoints also accept the key in `x-api-key`. A missing, invalid, expired or revoked key returns 401. No key scopes were found in the reviewed documentation. An agent can call `POST https://prisminference.com/api/agent-signups` with the owner's email and a username and receive a key once, but that key can't run inference until the owner supplies a six-digit emailed code, and it expires after 30 days. `GET /v1/models` needs no key.",
      "pricing": "usage",
      "pricingNotes": "Prepaid per-token pricing with no minimum. DeepSeek-V4.1-Flash is $0.09 in, $1.20 out and $0.06 cache read per million tokens, and Gemma 4 31B is $0.30, $0.40 and $0.15 (https://prisminference.com/pricing, matched by https://api.prisminference.com/v1/models). No free tier or trial credit was found, and a workspace without credit gets 402. A person funds the workspace in a browser. Elastic endpoints, dedicated deployments and batch are sold through sales with no published price.",
      "priceSummary": "from $0.09 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in llms.txt, the docs index, the OpenAPI file or the pricing page, read 2026-10-08. The docs describe prepaid credit funded by a person in the browser.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://docs.prisminference.com",
      "rateLimitsUrl": "https://docs.prisminference.com/rate-limits",
      "llmsTxt": "https://prisminference.com/llms.txt",
      "openapi": "https://docs.prisminference.com/openapi.yaml",
      "capabilities": [
        "inference.fast",
        "inference.open-weights",
        "inference.llm"
      ],
      "tags": [
        "hosted",
        "model",
        "open-weights",
        "fast",
        "usage-priced",
        "prepaid",
        "openapi",
        "llms-txt",
        "openai-compatible",
        "anthropic-compatible",
        "zero-retention",
        "status-page",
        "new"
      ],
      "lastRelease": "2026-10-06",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 60.1,
        "grade": "C",
        "agentReady": false,
        "rank": 363,
        "ranked": true,
        "rankOf": 629,
        "categoryRank": 8,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 68,
          "maintenance": 49,
          "payments": 30,
          "reliability": 65,
          "schema": 82,
          "security": 65,
          "transparency": 61
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": -2,
        "negativeNotes": [
          "2026-10-08. The home page shows a '99.99% Uptime SLA' tile, and the pricing page says 'No minimums, no rate limits' above the per-token table. The terms of 9 September 2026 say the services have no guaranteed uptime or service credit unless a separate written agreement says otherwise, and the docs describe per-key rate limits that return 429. No SLA document was found. A misleading claim, with the smallest deduction because the terms and docs state the real position (https://prisminference.com/, https://prisminference.com/pricing, https://prisminference.com/terms, https://docs.prisminference.com/rate-limits)."
        ],
        "verdict": "Three wire formats, a public OpenAPI 3.1 file, per-token prices in a keyless catalogue and zero data retention by default on every tier. The service launched on 24 September 2026 with two models, one of them by request, from a two-person company. No rate-limit numbers, SLA document, free tier or deprecation policy was found.",
        "bestFor": "Coding agents that want DeepSeek-V4.1-Flash at a low input price, with no retention, through whichever of the three wire formats the harness already speaks.",
        "strengths": [
          "One key works across OpenAI Chat Completions, OpenAI Responses and Anthropic Messages, with a public OpenAPI 3.1 file, llms.txt and Markdown docs",
          "Zero data retention is the default on every tier, and the privacy policy, terms and docs all say inputs and outputs are never used for training",
          "Every error carries a stable `code`, a `retryable` flag, a `fix` hint and a `docs_url`, and 429 carries `Retry-After` in seconds",
          "`GET /v1/models` answers without a key and returns context length, maximum output and per-token prices for each model",
          "DeepSeek-V4.1-Flash is listed with a 1M-token context and 384,000 output tokens at $0.09 in and $1.20 out per million"
        ],
        "weaknesses": [
          "Two models. The docs mark Gemma 4 31B as request access per organisation, while llms.txt and the keyless catalogue list it as available",
          "No rate-limit numbers are published. The docs say per-key limits exist, and the pricing page says 'no rate limits'",
          "The home page shows a '99.99% Uptime SLA' tile, while the terms say there is no guaranteed uptime without a separate written agreement",
          "No free tier found. Billing is prepaid, a person funds the workspace in a browser, and the agent sign-up key needs an emailed code",
          "The service launched on 24 September 2026. The changelog has one entry, and no deprecation policy, sub-processor list or certification was found"
        ],
        "agentNotes": [
          "Call `GET https://api.prisminference.com/v1/models` at start-up, with no key, and use only ids it returns. Expect 403 on `gemma-4-31b` without organisation access",
          "Use base URL `https://api.prisminference.com/v1` for OpenAI clients and `https://api.prisminference.com` with no `/v1` for Anthropic clients",
          "Read `error.retryable` before retrying, and wait for `Retry-After` on 429, which covers both key limits and model capacity",
          "Send `reasoning_effort: \"none\"` or `low` when latency matters. Reasoning is on by default and its tokens are billed as output",
          "Keep conversation state yourself and send `store: false` on Responses. `previous_response_id`, stored responses and hosted tools aren't supported"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 60.1
          }
        ],
        "editorialScores": {
          "ergonomics": 68,
          "maintenance": 49,
          "payments": 30,
          "reliability": 65,
          "schema": 82,
          "security": 65,
          "transparency": 43
        },
        "provenanceScore": 79
      },
      "connect": {
        "install": "pip install openai   # or: npm install openai, base URL https://api.prisminference.com/v1. Anthropic SDKs use https://api.prisminference.com with no /v1",
        "http": "curl \"https://api.prisminference.com/v1/chat/completions\" \\\n  -H \"Authorization: Bearer $PRISM_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"deepseek-v4.1-flash\",\"messages\":[{\"role\":\"user\",\"content\":\"Return pong.\"}]}'",
        "claudeCode": "export ANTHROPIC_BASE_URL=https://api.prisminference.com\nexport ANTHROPIC_AUTH_TOKEN=$PRISM_API_KEY\nexport ANTHROPIC_MODEL=deepseek-v4.1-flash\nexport ANTHROPIC_SMALL_FAST_MODEL=gemma-4-31b"
      },
      "letme": {
        "capability": "https://letme.dev/inference.fast",
        "tool": "https://letme.dev/prism-inference"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Prism Technologies Inc",
        "domain": "prisminference.com",
        "domainRegistered": "2026-09-09",
        "endpointOnVendorDomain": true,
        "terms": "https://prisminference.com/terms",
        "privacy": "https://prisminference.com/privacy",
        "statusPage": "https://status.prisminference.com",
        "changelog": "https://docs.prisminference.com/changelog",
        "securityTxt": "valid",
        "checked": "2026-10-08",
        "notes": [
          "The terms and the privacy policy, both last updated 9 September 2026, name Prism Technologies Inc. The terms are governed by California law with arbitration in San Francisco.",
          "RDAP gives a registration date of 2026-09-09 for prisminference.com, with Name.com as registrar.",
          "security.txt has a Contact line (founders@prisminference.com), an Expires date of 2027-10-06 and a Canonical line. No disclosure policy or bug bounty is named.",
          "The status page runs on incident.io with one component for each model and no component for the API or the website. Its incidents feed was empty on 8 October 2026.",
          "The YC directory lists Prism in the Spring 2025 batch, in San Francisco, with a team of 2. The home page links an X account named prism_videos, from the company's earlier video product."
        ],
        "score": 79
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/prism-inference.json",
      "live": {
        "slug": "prism-inference",
        "probe": {
          "target": "https://api.prisminference.com/v1",
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        "vendorStatus": {
          "page": "https://status.prisminference.com",
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          "checkedAt": "2026-10-08T19:06:55.435401601Z"
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        "versions": [
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          "url": "https://prisminference.com/.well-known/security.txt",
          "state": "valid",
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            "status": 200,
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            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "184a0fafdb8c"
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            "url": "https://prisminference.com/pricing",
            "kind": "pricing",
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            "checkedAt": "2026-10-08T18:23:20.103073255Z",
            "changedAt": "0001-01-01T00:00:00Z",
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            "url": "https://prisminference.com/privacy",
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            "changedAt": "0001-01-01T00:00:00Z",
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        "updatedAt": "2026-10-08T19:08:56.350063654Z"
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    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
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      {
        "a": "Mistral AI",
        "b": "Prism Technologies Inc",
        "name": "Vendor"
      },
      {
        "a": "https://api.mistral.ai/v1",
        "b": "https://api.prisminference.com/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
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      {
        "a": "Freemium",
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        "name": "Pricing"
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      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0 (SDKs)",
        "b": "Proprietary service under Prism's terms of service. The OpenAPI file declares `LicenseRef-Proprietary`. The Hermes provider plugin repository carries no licence file",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
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      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
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      {
        "a": "2026-09-30",
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        "name": "Last release"
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      {
        "a": "2026-09-25",
        "b": "2026-09-09",
        "name": "Terms last updated"
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      {
        "a": "2026-09-03",
        "b": "2026-09-09",
        "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": "yes",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "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": "yes",
        "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 Prism Inference's 60.1 (C), and leads in 6 of 7 scored categories. Prism Inference leads on reliability.",
        "question": "Which is better for AI agents, Mistral AI API or Prism Inference?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Mistral AI API and Prism Inference need an API key?"
      },
      {
        "answer": "Yes. Mistral AI API has a hosted endpoint at https://api.mistral.ai/v1 and Prism Inference at https://api.prisminference.com/v1.",
        "question": "Can an agent call Mistral AI API and Prism Inference without installing anything?"
      }
    ],
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          "Schema \u0026 documentation, 93 against 82",
          "Agent ergonomics, 91 against 68",
          "Payments \u0026 pricing, 40 against 30",
          "Maintenance \u0026 community, 88 against 49",
          "Transparency \u0026 trust, 80 against 61"
        ],
        "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.",
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        "aheadOn": [
          "Reliability, 65 against 50"
        ],
        "also": null,
        "goodFor": "Coding agents that want DeepSeek-V4.1-Flash at a low input price, with no retention, through whichever of the three wire formats the harness already speaks.",
        "slug": "prism-inference",
        "watchFor": "Two models. The docs mark Gemma 4 31B as request access per organisation, while llms.txt and the keyless catalogue list it as available"
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        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference.json",
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      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-prism-inference.json",
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        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.json",
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      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-prism-inference.json",
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    "scores": [
      {
        "by": 15,
        "edge": "prism-inference",
        "key": "reliability",
        "mistral-api": 50,
        "name": "Reliability",
        "prism-inference": 65,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 11,
        "edge": "mistral-api",
        "key": "schema",
        "mistral-api": 93,
        "name": "Schema \u0026 documentation",
        "prism-inference": 82,
        "weight": 13
      },
      {
        "by": 23,
        "edge": "mistral-api",
        "key": "ergonomics",
        "mistral-api": 91,
        "name": "Agent ergonomics",
        "prism-inference": 68,
        "weight": 13
      },
      {
        "by": 1,
        "edge": "mistral-api",
        "key": "security",
        "mistral-api": 66,
        "name": "Security \u0026 auth",
        "prism-inference": 65,
        "weight": 14
      },
      {
        "by": 10,
        "edge": "mistral-api",
        "key": "payments",
        "mistral-api": 40,
        "name": "Payments \u0026 pricing",
        "prism-inference": 30,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 39,
        "edge": "mistral-api",
        "key": "maintenance",
        "mistral-api": 88,
        "name": "Maintenance \u0026 community",
        "prism-inference": 49,
        "weight": 7
      },
      {
        "by": 19,
        "edge": "mistral-api",
        "key": "transparency",
        "mistral-api": 80,
        "name": "Transparency \u0026 trust",
        "prism-inference": 61,
        "weight": 7
      }
    ],
    "summary": "Mistral AI API scores 71.2 (BB) on agent readiness against Prism Inference's 60.1 (C), and leads in 6 of 7 scored categories. Prism Inference 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.",
      "prism-inference": "Three wire formats, a public OpenAPI 3.1 file, per-token prices in a keyless catalogue and zero data retention by default on every tier. The service launched on 24 September 2026 with two models, one of them by request, from a two-person company. No rate-limit numbers, SLA document, free tier or deprecation policy was found."
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  "markdown": "Mistral AI API scores 71.2 (BB) on agent readiness against Prism Inference's 60.1 (C), and leads in 6 of 7 scored categories. Prism Inference leads on reliability. Both do llm inference.\n\n- Mistral AI API: grade BB, 71.2/100, rank #112 of 629. Markdown https://www.anchorterminal.com/tools/mistral-api.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-api.json\n- Prism Inference: grade C, 60.1/100, rank #363 of 629. Markdown https://www.anchorterminal.com/tools/prism-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/prism-inference.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 82\n- Agent ergonomics, 91 against 68\n- Payments \u0026 pricing, 40 against 30\n- Maintenance \u0026 community, 88 against 49\n- Transparency \u0026 trust, 80 against 61\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### Prism Inference (C)\n\nGood for: Coding agents that want DeepSeek-V4.1-Flash at a low input price, with no retention, through whichever of the three wire formats the harness already speaks.\n\nAhead on:\n- Reliability, 65 against 50\n\nWatch for: Two models. The docs mark Gemma 4 31B as request access per organisation, while llms.txt and the keyless catalogue list it as available\n\n\n## Score by category\n\n| Category | Weight | Mistral AI API | Prism Inference | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 65 | Prism Inference +15 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 82 | Mistral AI API +11 |\n| Agent ergonomics | 13% (16.2 this run) | 91 | 68 | Mistral AI API +23 |\n| Security \u0026 auth | 14% (17.5 this run) | 66 | 65 | Mistral AI API +1 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 30 | Mistral AI API +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 88 | 49 | Mistral AI API +39 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 80 | 61 | Mistral AI API +19 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **71.2 · BB** | **60.1 · C** | |\n\n## Facts side by side\n\n| Fact | Mistral AI API | Prism Inference |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Mistral AI | Prism Technologies Inc |\n| Hosted endpoint | `https://api.mistral.ai/v1` | `https://api.prisminference.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | Proprietary service under Prism's terms of service. The OpenAPI file declares `LicenseRef-Proprietary`. The Hermes provider plugin repository carries no licence file |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-30 | 2026-10-06 |\n| Terms last updated | 2026-09-25 | 2026-09-09 |\n| Privacy policy last updated | 2026-09-03 | 2026-09-09 |\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 | yes |\n| Terms restrict benchmarking | yes | not found in the text |\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 | yes |\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 may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.\n\n**Prism Inference.** Three wire formats, a public OpenAPI 3.1 file, per-token prices in a keyless catalogue and zero data retention by default on every tier. The service launched on 24 September 2026 with two models, one of them by request, from a two-person company. No rate-limit numbers, SLA document, free tier or deprecation policy was found.\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### Prism Inference\n\n1. Call `GET https://api.prisminference.com/v1/models` at start-up, with no key, and use only ids it returns. Expect 403 on `gemma-4-31b` without organisation access\n2. Use base URL `https://api.prisminference.com/v1` for OpenAI clients and `https://api.prisminference.com` with no `/v1` for Anthropic clients\n3. Read `error.retryable` before retrying, and wait for `Retry-After` on 429, which covers both key limits and model capacity\n4. Send `reasoning_effort: \"none\"` or `low` when latency matters. Reasoning is on by default and its tokens are billed as output\n5. Keep conversation state yourself and send `store: false` on Responses. `previous_response_id`, stored responses and hosted tools aren't supported\n\n## Questions\n\n### Which is better for AI agents, Mistral AI API or Prism Inference?\n\nMistral AI API scores 71.2 (BB) on agent readiness against Prism Inference's 60.1 (C), and leads in 6 of 7 scored categories. Prism Inference leads on reliability.\n\n### Do Mistral AI API and Prism Inference need an API key?\n\nBoth need an API key.\n\n### Can an agent call Mistral AI API and Prism Inference without installing anything?\n\nYes. Mistral AI API has a hosted endpoint at https://api.mistral.ai/v1 and Prism Inference at https://api.prisminference.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"mistral-api\", \"b\": \"prism-inference\"}`. From a terminal: `anchor compare mistral-api prism-inference`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mistral-api.json and https://www.anchorterminal.com/api/v1/tools/prism-inference.json\n\n## Other comparisons with Mistral AI API or Prism Inference\n\n- [Claude API vs Mistral AI API](https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.md)\n- [Claude API vs Prism Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference.md)\n- [Antseed vs Mistral AI API](https://www.anchorterminal.com/compare/antseed-vs-mistral-api.md)\n- [Antseed vs Prism Inference](https://www.anchorterminal.com/compare/antseed-vs-prism-inference.md)\n- [BlockRun.AI vs Mistral AI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.md)\n- [BlockRun.AI vs Prism Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-prism-inference.md)\n- [DeepSeek API vs Mistral AI API](https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.md)\n- [DeepSeek API vs Prism Inference](https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference.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 Prism Inference](https://www.anchorterminal.com/compare/gemini-api-vs-prism-inference.md)\n- [GroqCloud vs Mistral AI API](https://www.anchorterminal.com/compare/groq-vs-mistral-api.md)\n- [GroqCloud vs Prism Inference](https://www.anchorterminal.com/compare/groq-vs-prism-inference.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- [OpenAI API vs Prism Inference](https://www.anchorterminal.com/compare/openai-api-vs-prism-inference.md)\n- [OpenRouter vs Prism Inference](https://www.anchorterminal.com/compare/openrouter-vs-prism-inference.md)\n",
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    "description": "Mistral AI API scores 71.2 (BB) on agent readiness against Prism Inference's 60.1 (C), and leads in 6 of 7 scored categories. Prism Inference leads on reliability. Both do llm inference. Category scores, facts, verdicts and agent notes side by side.",
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    "title": "Mistral AI API vs Prism Inference for AI agents, BB 71.2 vs C 60.1",
    "toc": null,
    "updated": "2026-10-08",
    "url": "https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference"
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