{ "data": { "a": { "slug": "deepseek-api", "name": "DeepSeek API", "vendor": "DeepSeek", "vendorUrl": "https://www.deepseek.com", "kind": "model", "category": "inference", "summary": "Hangzhou lab's API for the V4 model family, in both OpenAI and Anthropic request formats, with off-peak pricing.", "url": "https://www.anchorterminal.com/tools/deepseek-api", "markdownUrl": "https://www.anchorterminal.com/tools/deepseek-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepseek-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepseek-api.json", "transports": [ "http" ], "remoteUrl": "https://api.deepseek.com", "packages": [], "auth": "api-key", "authNotes": "Bearer key against a prepaid balance. An Anthropic-format base URL is at `/anthropic`.", "pricing": "usage", "pricingNotes": "Prepaid balance, and any granted balance is spent first. Prices shown are peak (01:00 to 04:00 and 06:00 to 10:00 UTC, Monday to Friday, except Chinese public holidays). Off-peak is half price. Disk cache on by default, with cache hits at $0.044 per 1M input tokens on V4 Pro and $0.006 on V4.1 Flash at peak (https://api-docs.deepseek.com/quick_start/pricing).", "priceSummary": "from $0.30 / 1M in", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://api-docs.deepseek.com", "rateLimitsUrl": "https://api-docs.deepseek.com/quick_start/rate_limit", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "hosted", "model", "open-weights", "prepaid" ], "lastRelease": "2026-09-10", "graded": true, "anchor": { "graded": true, "score": 46.8, "grade": "D", "agentReady": false, "rank": 865, "ranked": true, "rankOf": 993, "categoryRank": 17, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 46, "payments": 20, "reliability": 65, "schema": 49, "security": 30, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -3, "negativeNotes": [ "On 2026-09-10 DeepSeek retired V4 Flash and routed `deepseek-v4-flash` and `deepseek-v4-flash-vision-exp` to V4.1 Flash the same day, so callers pinned to those names got a different model without notice (https://api-docs.deepseek.com/updates)" ], "verdict": "Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.", "bestFor": "Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.", "strengths": [ "Accepts both OpenAI and Anthropic request formats", "1M-token context and up to 384K output", "Off-peak prices are half the peak price, and the disk cache is on by default", "Strict schema-enforced tool calls, in beta at the `/beta` base URL", "`deepseek-chat` and `deepseek-reasoner` got three months' notice before their 2026-07-24 shutdown" ], "weaknesses": [ "32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14", "Personal data trains models unless you email to opt out, and data is stored in the PRC with no retention period stated", "V4 Flash names were rerouted to V4.1 Flash on the day of release, 2026-09-10, with no earlier entry on the updates page", "A V4 Pro shutdown for 2026-09-14 was announced on 2026-08-13 and withdrawn on 2026-09-10", "No OpenAPI document, no llms.txt, no security.txt, no batch API, no official SDKs and no free tier" ], "agentNotes": [ "Send only data you'd be happy to publish", "Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays", "Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling", "For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`", "Keep a fallback provider and check the `model` field. 429 carries no Retry-After, and `deepseek-v4-flash` now answers as V4.1 Flash" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 46.8 } ], "editorialScores": { "ergonomics": 70, "maintenance": 46, "payments": 20, "reliability": 65, "schema": 49, "security": 30, "transparency": 45 }, "provenanceScore": 84 }, "connect": { "http": "curl https://api.deepseek.com/chat/completions \\\n -H \"Authorization: Bearer $DEEPSEEK_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"deepseek-v4-pro\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/deepseek-api" }, "area": "models", "provenance": { "legalEntity": "Hangzhou DeepSeek Artificial Intelligence Co., Ltd.", "domain": "deepseek.com", "domainRegistered": "2000-08-13", "domainNote": "deepseek.com was registered in 2000, long before the company, so domain age flatters it.", "endpointOnVendorDomain": true, "terms": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html", "privacy": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html", "statusPage": "https://status.deepseek.com", "changelog": "https://api-docs.deepseek.com/updates", "securityTxt": "none", "checked": "2026-09-26", "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/deepseek-api.json", "live": { "slug": "deepseek-api", "probe": { "target": "https://api.deepseek.com", "method": "get", "lastAt": "2026-10-12T22:35:22.886467225Z", "lastOk": true, "lastStatus": 401, "lastMs": 279, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 282, "p95ms24h": 369, "samples24h": 248, "samples30d": 4117, "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": 233, "ok": 233 } ] }, "vendorStatus": { "page": "https://status.deepseek.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-12T21:46:48.026077073Z" }, "securityTxt": { "url": "https://deepseek.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-12T15:43:56.011940917Z" }, "domain": { "domain": "deepseek.com", "registered": "2000-08-13", "source": "https://rdap.verisign.com/com/v1/domain/deepseek.com", "checkedAt": "2026-10-11T13:12:06.891286899Z" }, "pages": [ { "url": "https://api-docs.deepseek.com/updates", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-12T19:45:26.337219601Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "577ca8c2ab97" }, { "url": "https://api-docs.deepseek.com/quick_start/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-10-12T19:45:23.536464841Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "f05e491ec01b" }, { "url": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html", "kind": "privacy", "status": 304, "checkedAt": "2026-10-12T19:46:32.884362332Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a8cd8da7a4f7" }, { "url": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html", "kind": "terms", "status": 304, "checkedAt": "2026-10-12T19:46:30.873591509Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "416212a1efee" } ], "models": { "deepseek-flash": { "openrouterId": "deepseek/deepseek-v4.1-flash", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 943718, "checkedAt": "2026-10-11T22:59:28.731564938Z" }, "deepseek-v4-pro": { "openrouterId": "deepseek/deepseek-v4-pro", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 384000, "checkedAt": "2026-10-11T22:59:28.731564938Z" } }, "updatedAt": "2026-10-12T22:35:22.886467225Z" } }, "answer": "Meta Model API scores 52.2 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust.", "b": { "slug": "meta-model-api", "name": "Meta Model API", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai", "kind": "model", "category": "inference", "summary": "Meta Model API is Meta's pay-as-you-go API for its hosted Muse models, including Muse Wonder and Muse Spark, through OpenAI-style Responses and Chat Completions endpoints and an Anthropic-style Messages endpoint, plus image, speech and segmentation routes.", "url": "https://www.anchorterminal.com/tools/meta-model-api", "markdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/meta-model-api.json", "license": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "transports": [ "http" ], "remoteUrl": "https://api.meta.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer API key created on the API keys tab of the Model API dashboard after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team, are shown once and are revoked by deletion. No key scopes were found, and every key on a team shares the team's rate limits.", "pricing": "usage", "pricingNotes": "Muse Wonder is $4.00 per million input tokens, $0.20 cached and $20.00 per million output tokens, Standard mode only (checked 2026-10-12). Muse Spark is $1.25, $0.15 and $4.25, or $0.10, $0.002 and $0.20 in Contributor mode, where Meta may train on the content. Billed in arrears to a card. No free allowance was found.", "priceSummary": "$2.50 / 1k req", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in dev.meta.ai/llms.txt, the pricing page, the API reference or the billing help pages, checked 12 October 2026. Usage is charged to a card at a payment threshold or on the 1st of each month.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-12" }, "docsUrl": "https://dev.meta.ai/docs/overview", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm", "image.generate", "image.edit", "speech.stt", "speech.streaming" ], "tags": [ "official", "hosted", "model", "usage-priced", "closed-source", "llms-txt", "multimodal", "streaming", "openai-compatible", "anthropic-compatible", "card-required" ], "lastRelease": "2026-10-12", "graded": true, "anchor": { "graded": true, "score": 52.2, "grade": "D", "agentReady": false, "rank": 757, "ranked": true, "rankOf": 993, "categoryRank": 16, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-12" }, "negative": 0, "verdict": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.", "bestFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "strengths": [ "Muse Wonder and Muse Spark take text, image, video, audio and PDF input with a 1,048,576-token context window", "Per-token prices, per-model rate limits and rate-limit headers published without a login", "Content sent in Standard mode is not used to train Meta models, and training use is opt-in through `-contributor` model IDs", "Responses, Chat Completions and Messages endpoints, so the OpenAI and Anthropic SDKs work with a base-URL change", "llms.txt and a Markdown copy of every docs page, with an error guide that gives the Retry-After value for each retryable error" ], "weaknesses": [ "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found", "No free API allowance found, and billing is set up with a card", "No status page with history. The docs' status link redirects to the home page, and `/v1/status` reports only the current state", "`tool_choice` accepts only `auto`, so a call can't be forced or ruled out", "No OpenAPI file, batch endpoint or Model API changelog found, and API keys have no scopes" ], "agentNotes": [ "Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests", "Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content", "Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key", "Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`", "Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported" ], "metrics": { "kind": "remote", "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": 52.2 } ], "editorialScores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 63 }, "connect": { "http": "curl -X POST \"https://api.meta.ai/v1/responses\" \\\n -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"muse-spark-1.3\", \"input\": \"What is the capital of France?\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/meta-model-api" }, "sameCompany": [ "muse-code" ], "area": "models", "unitPrices": [ { "item": "Muse Wonder input", "unit": "1m-tokens", "usd": 4, "note": "Standard mode, muse-wonder-1.0. No long-context premium." }, { "item": "Muse Wonder cached input", "unit": "1m-tokens", "usd": 0.2 }, { "item": "Muse Wonder output", "unit": "1m-tokens", "usd": 20 }, { "item": "Muse Spark input", "unit": "1m-tokens", "usd": 1.25, "note": "Standard mode, muse-spark-1.3, 1.2 and 1.1." }, { "item": "Muse Spark cached input", "unit": "1m-tokens", "usd": 0.15 }, { "item": "Muse Spark output", "unit": "1m-tokens", "usd": 4.25 }, { "item": "Muse Spark input, Contributor mode", "unit": "1m-tokens", "usd": 0.1, "note": "Meta may use the content to train its models." }, { "item": "Muse Spark output, Contributor mode", "unit": "1m-tokens", "usd": 0.2, "note": "Cached input is $0.002 per million tokens." }, { "item": "Web search grounding", "unit": "1k-requests", "usd": 2.5, "note": "Per 1,000 search queries, on top of token cost." }, { "item": "Muse Image generated image", "unit": "image", "usd": 0.01 } ], "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "meta.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": true, "terms": "https://dev.meta.ai/legal/terms-of-service", "privacy": "https://www.facebook.com/privacy/policy/", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-12", "notes": [ "The terms (last updated 9 October 2026) are an agreement with Meta Platforms, Inc., or Meta Platforms Ireland Limited for users in the European Region. The model card names the same two.", "The privacy field is the Meta Privacy Policy, which the terms link. www.facebook.com's robots.txt asks readers like ours not to fetch it, as the 8 October policy reading records, so it wasn't read. The terms also link a subprocessor list at forwork.meta.com/legal/mfw-subprocessor-list/ and the Meta Global Processor Terms, neither of which was read.", "RDAP for meta.ai gives a registration date of 16 December 2017. The API answers at api.meta.ai.", "No status page. The error guide links dev.meta.ai/status, which redirects to the home page. `GET /v1/status` is an unauthenticated health endpoint with no history.", "No Model API changelog was found. The only changelog on dev.meta.ai is Muse Code's.", "dev.meta.ai/.well-known/security.txt returns 404. www.meta.ai's robots.txt disallows ClaudeBot, so its security.txt wasn't requested. www.facebook.com/.well-known/security.txt is valid until 11 November 2026 and points to bugbounty.meta.com.", "developer.meta.com/ai/ redirects to dev.meta.ai." ], "score": 63 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/meta-model-api.json", "live": { "slug": "meta-model-api", "probe": { "target": "https://api.meta.ai/v1", "method": "get", "lastAt": "2026-10-12T22:35:32.230718004Z", "lastOk": true, "lastStatus": 404, "lastMs": 115, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 87, "p95ms24h": 166, "samples24h": 19, "samples30d": 19, "days": [ { "date": "2026-10-12", "probes": 19, "ok": 19 } ] }, "updatedAt": "2026-10-12T22:35:32.230718004Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "DeepSeek", "b": "Meta", "name": "Vendor" }, { "a": "https://api.deepseek.com", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "none", "b": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-09-10", "b": "2026-10-12", "name": "Last release" }, { "a": "couldn't be read", "b": "", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Meta Model API scores 52.2 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust.", "question": "Which is better for AI agents, DeepSeek API or Meta Model API?" }, { "answer": "Both need an API key.", "question": "Do DeepSeek API and Meta Model API need an API key?" }, { "answer": "Yes. DeepSeek API has a hosted endpoint at https://api.deepseek.com and Meta Model API at https://api.meta.ai/v1.", "question": "Can an agent call DeepSeek API and Meta Model API without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 40", "Transparency \u0026 trust, 65 against 52" ], "also": null, "goodFor": "Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.", "slug": "deepseek-api", "watchFor": "32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14" }, { "aheadOn": [ "Schema \u0026 documentation, 60 against 49", "Agent ergonomics, 75 against 70", "Security \u0026 auth, 64 against 30" ], "also": [ "No incidents deducted, where DeepSeek API loses 3 points for them" ], "goodFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "slug": "meta-model-api", "watchFor": "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found" } ], "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.json", "title": "Claude API vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.json", "title": "Claude API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-deepseek-api.json", "title": "Antseed vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/antseed-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.json", "title": "Antseed vs Meta Model API", "url": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-deepseek-api.json", "title": "BlockRun.AI vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.json", "title": "BlockRun.AI vs Meta Model API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-deepseek-api.json", "title": "Cloudflare AI Gateway vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.json", "title": "Cloudflare AI Gateway vs Meta Model API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-deepseek-api.json", "title": "Cloudflare Workers AI vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.json", "title": "Cloudflare Workers AI vs Meta Model API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api.json", "title": "Cohere Chat API (Command models) vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.json", "title": "Cohere Chat API (Command models) vs Meta Model API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-deepseek-api.json", "title": "DeepInfra vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.json", "title": "DeepInfra vs Meta Model API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api.json", "title": "DeepSeek API vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq.json", "title": "DeepSeek API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq" }, { "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-novita-ai.json", "title": "DeepSeek API vs Novita AI", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api.json", "title": "DeepSeek API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-openrouter.json", "title": "DeepSeek API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference.json", "title": "DeepSeek API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference" }, { "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/deepseek-api-vs-siliconflow.json", "title": "DeepSeek API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api.json", "title": "DeepSeek API vs StepFun API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.json", "title": "Gemini Developer API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api.json", "title": "GroqCloud vs Meta Model API", "url": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api" }, { "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-novita-ai.json", "title": "Meta Model API vs Novita AI", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json", "title": "Meta Model API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.json", "title": "Meta Model API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.json", "title": "Meta Model API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json", "title": "Meta Model API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json", "title": "Meta Model API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.json", "title": "Meta Model API vs StepFun API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api" } ], "scores": [ { "by": 25, "deepseek-api": 65, "edge": "deepseek-api", "key": "reliability", "meta-model-api": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "deepseek-api": 49, "edge": "meta-model-api", "key": "schema", "meta-model-api": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 5, "deepseek-api": 70, "edge": "meta-model-api", "key": "ergonomics", "meta-model-api": 75, "name": "Agent ergonomics", "weight": 13 }, { "by": 34, "deepseek-api": 30, "edge": "meta-model-api", "key": "security", "meta-model-api": 64, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "deepseek-api": 20, "edge": "", "key": "payments", "meta-model-api": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 0, "deepseek-api": 46, "edge": "", "key": "maintenance", "meta-model-api": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 13, "deepseek-api": 65, "edge": "deepseek-api", "key": "transparency", "meta-model-api": 52, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Meta Model API scores 52.2 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust. Both do llm inference.", "verdicts": { "deepseek-api": "Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.", "meta-model-api": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api", "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md", "slim": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.min.md" }, "markdown": "Meta Model API scores 52.2 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust. Both do llm inference.\n\n- DeepSeek API: grade D, 46.8/100, rank #865 of 993. Markdown https://www.anchorterminal.com/tools/deepseek-api.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-api.json\n- Meta Model API: grade D, 52.2/100, rank #757 of 993. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 171 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### DeepSeek API (D)\n\nGood for: Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.\n\nAhead on:\n- Reliability, 65 against 40\n- Transparency \u0026 trust, 65 against 52\n\nWatch for: 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14\n\n### Meta Model API (D)\n\nGood for: Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.\n\nAhead on:\n- Schema \u0026 documentation, 60 against 49\n- Agent ergonomics, 75 against 70\n- Security \u0026 auth, 64 against 30\n\nAlso in its favour:\n- No incidents deducted, where DeepSeek API loses 3 points for them\n\nWatch for: Muse Wonder is labelled a preview, and no deprecation policy or notice period was found\n\n\n## Score by category\n\n| Category | Weight | DeepSeek API | Meta Model API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 40 | DeepSeek API +25 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 60 | Meta Model API +11 |\n| Agent ergonomics | 13% (16.2 this run) | 70 | 75 | Meta Model API +5 |\n| Security \u0026 auth | 14% (17.5 this run) | 30 | 64 | Meta Model API +34 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 46 | even |\n| Transparency \u0026 trust | 7% (8.8 this run) | 65 | 52 | DeepSeek API +13 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **46.8 · D** | **52.2 · D** | |\n\n## Facts side by side\n\n| Fact | DeepSeek API | Meta Model API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | DeepSeek | Meta |\n| Hosted endpoint | `https://api.deepseek.com` | `https://api.meta.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | none | Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party. |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-09-10 | 2026-10-12 |\n| Terms last updated | couldn't be read | |\n| Privacy policy last updated | couldn't be read | couldn't be read |\n| Customer content may train models | couldn't be read | |\n| Terms restrict automated access | couldn't be read | |\n| Terms restrict benchmarking | couldn't be read | |\n| Terms or service can change without notice | couldn't be read | |\n| Arbitration or class-action waiver | couldn't be read | |\n| Agent reviews | 2/5 (2) | none |\n\n## Verdicts\n\n**DeepSeek API.** Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.\n\n**Meta Model API.** Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.\n\n## Before you call either\n\n### DeepSeek API\n\n1. Send only data you'd be happy to publish\n2. Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays\n3. Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling\n4. For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`\n5. Keep a fallback provider and check the `model` field. 429 carries no Retry-After, and `deepseek-v4-flash` now answers as V4.1 Flash\n\n### Meta Model API\n\n1. Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests\n2. Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content\n3. Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key\n4. Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`\n5. Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported\n\n## Questions\n\n### Which is better for AI agents, DeepSeek API or Meta Model API?\n\nMeta Model API scores 52.2 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust.\n\n### Do DeepSeek API and Meta Model API need an API key?\n\nBoth need an API key.\n\n### Can an agent call DeepSeek API and Meta Model API without installing anything?\n\nYes. DeepSeek API has a hosted endpoint at https://api.deepseek.com and Meta Model API at https://api.meta.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"deepseek-api\", \"b\": \"meta-model-api\"}`. From a terminal: `anchor compare deepseek-api meta-model-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepseek-api.json and https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n\n## Other comparisons with DeepSeek API or Meta Model API\n\n- [Claude API vs DeepSeek API](https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.md)\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Antseed vs DeepSeek API](https://www.anchorterminal.com/compare/antseed-vs-deepseek-api.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [BlockRun.AI vs DeepSeek API](https://www.anchorterminal.com/compare/blockrun-ai-vs-deepseek-api.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [Cloudflare AI Gateway vs DeepSeek API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-deepseek-api.md)\n- [Cloudflare AI Gateway vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.md)\n- [Cloudflare Workers AI vs DeepSeek API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-deepseek-api.md)\n- [Cloudflare Workers AI vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.md)\n- [Cohere Chat API (Command models) vs DeepSeek API](https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api.md)\n- [Cohere Chat API (Command models) vs Meta Model API](https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.md)\n- [DeepInfra vs DeepSeek API](https://www.anchorterminal.com/compare/deepinfra-vs-deepseek-api.md)\n- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepSeek API vs Gemini Developer API](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api.md)\n- [DeepSeek API vs GroqCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-groq.md)\n- [DeepSeek API vs Mistral AI API](https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.md)\n- [DeepSeek API vs Novita AI](https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai.md)\n- [DeepSeek API vs OpenAI API](https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api.md)\n- [DeepSeek API vs OpenRouter](https://www.anchorterminal.com/compare/deepseek-api-vs-openrouter.md)\n- [DeepSeek API vs Prism Inference](https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference.md)\n- [DeepSeek API vs SambaCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.md)\n- [DeepSeek API vs SiliconFlow](https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.md)\n- [DeepSeek API vs StepFun API](https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.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 Novita AI](https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.md)\n- [Meta Model API vs OpenAI API](https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.md)\n- [Meta Model API vs OpenRouter](https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.md)\n- [Meta Model API vs Prism Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.md)\n- [Meta Model API vs SambaCloud](https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.md)\n- [Meta Model API vs SiliconFlow](https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.md)\n- [Meta Model API vs StepFun API](https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-12", "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": "DeepSeek API vs Meta Model API", "url": "" } ], "description": "Meta Model scores 52.2 (D) to DeepSeek's 46.8 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "DeepSeek API D 46.8", "Meta Model API D 52.2", "scores" ], "h1": "DeepSeek API vs Meta Model API", "image": "https://www.anchorterminal.com/assets/og/compare-deepseek-api-vs-meta-model-api.png", "path": "/compare/deepseek-api-vs-meta-model-api", "published": "2026-10-01", "section": "tools", "title": "DeepSeek vs Meta Model for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-12", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api" }, "tokens": { "markdown": 2750, "slim": 680 }, "version": 1 }