{ "data": { "a": { "slug": "cerebras-inference", "name": "Cerebras Inference", "vendor": "Cerebras Systems Inc.", "vendorUrl": "https://www.cerebras.ai/inference", "kind": "http-api", "category": "inference", "summary": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API. It supports streaming, structured outputs, tool calling and prompt caching, with shared and dedicated inference options.", "url": "https://www.anchorterminal.com/tools/cerebras-inference", "markdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json", "repo": "https://github.com/Cerebras/cerebras-cloud-sdk-python", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.cerebras.ai/v1", "packages": [ { "registry": "pypi", "name": "cerebras-cloud-sdk" }, { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk" } ], "auth": "api-key", "authNotes": "Bearer API keys from the Cloud Console. Paid accounts scope keys to projects; trial accounts do not have projects. Keys do not expire and can be rotated by creating a replacement and deleting the old key.", "pricing": "paid", "pricingNotes": "Pay per token. GPT OSS 120B is $0.35 per million input tokens and $0.75 per million output tokens. New accounts get $5 for 30 days only after adding a verified payment method. Dedicated capacity is priced by agreement.", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 170, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://inference-docs.cerebras.ai", "llmsTxt": "https://inference-docs.cerebras.ai/llms.txt", "openapi": "https://inference-docs.cerebras.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "paid" ], "lastRelease": "2026-10-09", "graded": true, "anchor": { "graded": true, "score": 68.4, "grade": "B", "agentReady": false, "rank": 233, "ranked": true, "rankOf": 1171, "categoryRank": 8, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-19" }, "negative": 0, "verdict": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "bestFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "strengths": [ "Public OpenAPI 3.1, Markdown docs, and official Python and TypeScript SDKs", "Tool calling, structured outputs, streaming and prompt caching on supported models", "Documented project controls, usage logs and numeric request and token limits" ], "weaknesses": [ "Trial access requires a verified payment method and ends after $5 or 30 days", "The GPT OSS model page and central rate-limit page disagree on trial request limits", "Cloud terms returned an empty page to the reader; no public shared-inference SLA was established" ], "agentNotes": [ "Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.", "Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.", "Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.", "Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 68.4 } ], "editorialScores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 45 }, "provenanceScore": 71 }, "connect": { "http": "curl 'https://api.cerebras.ai/v1/chat/completions' -H \"Authorization: Bearer $CEREBRAS_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/cerebras-inference" }, "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.35, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.75, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" } ], "provenance": { "legalEntity": "Cerebras Systems Inc.", "domain": "cerebras.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://cloud.cerebras.ai/terms", "privacy": "https://www.cerebras.ai/privacy-policy", "statusPage": "https://status.cerebras.ai", "changelog": "https://inference-docs.cerebras.ai/support/change-log", "securityTxt": "none", "checked": "2026-10-19", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "Cloud terms at cloud.cerebras.ai/terms returned no readable document; privacy identifies Cerebras Systems Inc.", "The well-known security.txt returned 404. The trust centre lists SOC 2 Type II." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cerebras-inference.json", "live": { "slug": "cerebras-inference", "probe": { "target": "https://api.cerebras.ai/v1", "method": "get", "lastAt": "2026-10-19T09:34:24.387029889Z", "lastOk": true, "lastStatus": 404, "lastMs": 131, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 140, "p95ms24h": 194, "samples24h": 20, "samples30d": 20, "days": [ { "date": "2026-10-19", "probes": 20, "ok": 20 } ] }, "vendorStatus": { "page": "https://status.cerebras.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-19T09:26:58.948841855Z" }, "updatedAt": "2026-10-19T09:34:24.387029889Z" } }, "answer": "Cerebras Inference scores 68.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 6 of 7 scored categories.", "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": 842, "ranked": true, "rankOf": 1171, "categoryRank": 23, "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-spark-open", "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": "2026-10-19T09:34:35.84158745Z", "lastOk": true, "lastStatus": 404, "lastMs": 62, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 70, "p95ms24h": 174, "samples24h": 256, "samples30d": 1646, "days": [ { "date": "2026-10-12", "probes": 33, "ok": 33 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 102, "ok": 102 } ] }, "securityTxt": { "url": "https://meta.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-18T15:54:29.002676333Z" }, "llmsTxt": { "url": "https://dev.meta.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-18T14:25:27.504662791Z" }, "domain": { "domain": "meta.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/meta.ai", "checkedAt": "2026-10-18T13:39:00.851805812Z" }, "pages": [ { "url": "https://dev.meta.ai/legal/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-10-18T23:26:04.172620691Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0ef10c66f1b3" } ], "updatedAt": "2026-10-19T09:34:35.84158745Z" } }, "facts": [ { "a": "HTTP API", "b": "Model API", "name": "Kind" }, { "a": "Cerebras Systems Inc.", "b": "Meta", "name": "Vendor" }, { "a": "https://api.cerebras.ai/v1", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Paid", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "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": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-09", "b": "2026-10-12", "name": "Last release" }, { "a": "couldn't be read", "b": "", "name": "Terms last updated" }, { "a": "2024-08-27", "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": "170 stars", "b": "none", "name": "Popularity" }, { "a": "3.3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Cerebras Inference scores 68.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Cerebras Inference or Meta Model API?" }, { "answer": "Both need an API key.", "question": "Do Cerebras Inference and Meta Model API need an API key?" }, { "answer": "Yes. Cerebras Inference has a hosted endpoint at https://api.cerebras.ai/v1 and Meta Model API at https://api.meta.ai/v1.", "question": "Can an agent call Cerebras Inference and Meta Model API without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 70 against 40", "Schema \u0026 documentation, 93 against 60", "Agent ergonomics, 85 against 75", "Security \u0026 auth, 70 against 64", "Maintenance \u0026 community, 65 against 46", "Transparency \u0026 trust, 58 against 52" ], "also": null, "goodFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "slug": "cerebras-inference", "watchFor": "Trial access requires a verified payment method and ends after $5 or 30 days" }, { "aheadOn": null, "also": null, "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-cerebras-inference.json", "title": "Claude API vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference" }, { "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-cerebras-inference.json", "title": "Antseed vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/antseed-vs-cerebras-inference" }, { "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-cerebras-inference.json", "title": "BlockRun.AI vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-cerebras-inference" }, { "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/cerebras-inference-vs-cloudflare-ai-gateway.json", "title": "Cerebras Inference vs Cloudflare AI Gateway", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cloudflare-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cloudflare-workers-ai.json", "title": "Cerebras Inference vs Cloudflare Workers AI", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cloudflare-workers-ai" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cohere-chat.json", "title": "Cerebras Inference vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-deepinfra.json", "title": "Cerebras Inference vs DeepInfra", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-deepinfra" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-deepseek-api.json", "title": "Cerebras Inference vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-elorian-glimpse.json", "title": "Cerebras Inference vs Glimpse", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-elorian-glimpse" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference.json", "title": "Cerebras Inference vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-api.json", "title": "Cerebras Inference vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-groq.json", "title": "Cerebras Inference vs GroqCloud", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3.json", "title": "Cerebras Inference vs Jais 3", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-mistral-api.json", "title": "Cerebras Inference vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open.json", "title": "Cerebras Inference vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-nemotron-3-5-super-vl.json", "title": "Cerebras Inference vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai.json", "title": "Cerebras Inference vs Novita AI", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api.json", "title": "Cerebras Inference vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api" }, { 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"json": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.json", "title": "DeepSeek API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api.json", "title": "Glimpse vs Meta Model API", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api.json", "title": "Fireworks AI Inference vs Meta Model API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-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/jais-3-vs-meta-model-api.json", "title": "Jais 3 vs Meta Model API", "url": "https://www.anchorterminal.com/compare/jais-3-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-muse-spark-open.json", "title": "Meta Model API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl.json", "title": "Meta Model API vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl" }, { "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-reflection-beam.json", "title": "Meta Model API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus.json", "title": "Meta Model API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.json", "title": "Meta Model API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.json", "title": "Meta Model API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway" } ], "scores": [ { "by": 30, "cerebras-inference": 70, "edge": "cerebras-inference", "key": "reliability", "meta-model-api": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 33, "cerebras-inference": 93, "edge": "cerebras-inference", "key": "schema", "meta-model-api": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 10, "cerebras-inference": 85, "edge": "cerebras-inference", "key": "ergonomics", "meta-model-api": 75, "name": "Agent ergonomics", "weight": 13 }, { "by": 6, "cerebras-inference": 70, "edge": "cerebras-inference", "key": "security", "meta-model-api": 64, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "cerebras-inference": 20, "edge": "", "key": "payments", "meta-model-api": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 19, "cerebras-inference": 65, "edge": "cerebras-inference", "key": "maintenance", "meta-model-api": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 6, "cerebras-inference": 58, "edge": "cerebras-inference", "key": "transparency", "meta-model-api": 52, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Cerebras Inference scores 68.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 6 of 7 scored categories. Both do llm inference.", "tutorials": [], "verdicts": { "cerebras-inference": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "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/cerebras-inference-vs-meta-model-api", "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.min.md" }, "markdown": "Cerebras Inference scores 68.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Cerebras Inference: grade B, 68.4/100, rank #233 of 1171. Markdown https://www.anchorterminal.com/tools/cerebras-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json\n- Meta Model API: grade D, 52.2/100, rank #842 of 1171. 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 407 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Cerebras Inference (B)\n\nGood for: Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.\n\nAhead on:\n- Reliability, 70 against 40\n- Schema \u0026 documentation, 93 against 60\n- Agent ergonomics, 85 against 75\n- Security \u0026 auth, 70 against 64\n- Maintenance \u0026 community, 65 against 46\n- Transparency \u0026 trust, 58 against 52\n\nWatch for: Trial access requires a verified payment method and ends after $5 or 30 days\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\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 | Cerebras Inference | Meta Model API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 70 | 40 | Cerebras Inference +30 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 60 | Cerebras Inference +33 |\n| Agent ergonomics | 13% (16.2 this run) | 85 | 75 | Cerebras Inference +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 70 | 64 | Cerebras Inference +6 |\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) | 65 | 46 | Cerebras Inference +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 58 | 52 | Cerebras Inference +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **68.4 · B** | **52.2 · D** | |\n\n## Facts side by side\n\n| Fact | Cerebras Inference | Meta Model API |\n| --- | --- | --- |\n| Kind | HTTP API | Model API |\n| Vendor | Cerebras Systems Inc. | Meta |\n| Hosted endpoint | `https://api.cerebras.ai/v1` | `https://api.meta.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Paid | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | 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 | yes | yes |\n| Last release | 2026-10-09 | 2026-10-12 |\n| Terms last updated | couldn't be read | |\n| Privacy policy last updated | 2024-08-27 | 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| Popularity | 170 stars | none |\n| Agent reviews | 3.3/5 (4) | none |\n\n## Verdicts\n\n**Cerebras Inference.** An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.\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### Cerebras Inference\n\n1. Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.\n2. Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.\n3. Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.\n4. Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated.\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, Cerebras Inference or Meta Model API?\n\nCerebras Inference scores 68.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 6 of 7 scored categories.\n\n### Do Cerebras Inference and Meta Model API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Cerebras Inference and Meta Model API without installing anything?\n\nYes. Cerebras Inference has a hosted endpoint at https://api.cerebras.ai/v1 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/cerebras-inference-vs-meta-model-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cerebras-inference\", \"b\": \"meta-model-api\"}`. 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