{ "data": { "a": { "slug": "cohere-chat", "name": "Cohere Chat API (Command models)", "vendor": "Cohere", "vendorUrl": "https://cohere.com", "kind": "model", "category": "inference", "summary": "Cohere's Chat API generates text with the Command family of models over REST (v2 chat), with tool use, structured outputs, citations and streaming. SDKs cover Python, TypeScript, Java and Go.", "url": "https://www.anchorterminal.com/tools/cohere-chat", "markdownUrl": "https://www.anchorterminal.com/tools/cohere-chat.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cohere-chat.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cohere-chat.json", "dns": "cohere-chat.grade.anchorterminal.com", "repo": "https://github.com/cohere-ai/cohere-python", "license": "Proprietary service under Cohere's Commercial SaaS Agreement. The SDKs are MIT", "transports": [ "http" ], "remoteUrl": "https://api.cohere.com/v2/chat", "packages": [ { "registry": "pypi", "name": "cohere", "main": true }, { "registry": "npm", "name": "cohere-ai", "main": true }, { "registry": "go", "name": "github.com/cohere-ai/cohere-go/v2" } ], "auth": "api-key", "authNotes": "Bearer API key from the dashboard, self-serve. A trial key is created at sign-up. A production key needs a team Owner to complete the Go to Production form and accept the SaaS agreement. Team roles are Owner and User. No key scopes or expiry were found in the docs.", "pricing": "freemium", "pricingNotes": "Trial keys are free with no card, limited to 20 chat requests a minute and 1,000 calls a month, and not for commercial use. Production keys bill per input and output token, monthly or at $250 outstanding. The pricing page lists Command R at $0.15 and $0.60 and Command R7B at $0.0375 and $0.15 per million input and output tokens, Command R+ 08-2024 at $2.50 and $10.00 among legacy prices, and Command A+ as free. No price is published for Command A, Reasoning, Vision or Translate. Production keys stay at trial limits on Command A+, Reasoning, Translate and Vision (checked 2026-11-02).", "priceSummary": "from $0.0375 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the OpenAPI file or the pricing page (checked 2026-10-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://docs.cohere.com/docs/chat-api", "rateLimitsUrl": "https://docs.cohere.com/docs/rate-limits", "llmsTxt": "https://docs.cohere.com/llms.txt", "openapi": "https://raw.githubusercontent.com/cohere-ai/cohere-developer-experience/main/cohere-openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "free-tier", "no-card", "openapi", "llms-txt", "openai-compatible", "python", "typescript", "java", "go", "status-page", "soc2", "bug-bounty" ], "lastRelease": "2026-09-09", "graded": true, "anchor": { "graded": true, "score": 65.6, "grade": "B", "agentReady": false, "rank": 411, "ranked": true, "rankOf": 1518, "categoryRank": 19, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 72, "payments": 35, "reliability": 67, "schema": 84, "security": 55, "transparency": 75 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-02" }, "negative": 0, "verdict": "A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.", "bestFor": "Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.", "strengths": [ "Public OpenAPI 3.1 file in the docs repository, last changed 29 September 2026, and a Markdown twin of every docs page", "A trial key is created at sign-up with no card, limited to 20 chat requests a minute and 1,000 calls a month", "Official SDKs for Python, TypeScript and Go, each tagged on 21 October 2026, and Java 1.12.0", "JSON Schema structured outputs, `strict_tools` (beta), citations, reasoning budgets and safety modes on the v2 chat request", "The trust centre lists SOC 2 Type II, ISO 27001, ISO 42001 and a bug bounty, with nine sub-processors, all in the US" ], "weaknesses": [ "Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault", "The pricing page lists per-token prices for Command R, R7B and R+ only. Command A, Reasoning, Vision and Translate have no published price", "The SaaS agreement of 8 April 2025 grants Cohere an irrevocable right to use API data to improve its services and to share it with third parties", "No Retry-After header, backoff guidance or idempotency key was found in the reviewed documentation", "The SaaS agreement forbids use of the services for benchmarking or competitive analysis. Recorded as a fact, and it matters before any probe is run" ], "agentNotes": [ "Call `POST https://api.cohere.com/v2/chat` with `Authorization: bearer \u003ckey\u003e`. `model` and `messages` are the only required fields", "Use `command-a-03-2025`, `command-r-08-2024`, `command-r-plus-08-2024` or `command-r7b-12-2024` for production traffic. Newer variants stay at trial limits on a production key, and only the R models have published prices", "Keep a trial key under 20 chat requests a minute and 1,000 calls a month, and do not use it for commercial work", "Set `response_format` with a `json_schema` for structured output, and tell the model to produce JSON when using `json_object` without a schema", "Ask the account Owner to turn off training under Data Controls in the dashboard before sending confidential prompts" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 65.6 } ], "editorialScores": { "ergonomics": 72, "maintenance": 72, "payments": 35, "reliability": 67, "schema": 84, "security": 55, "transparency": 66 }, "provenanceScore": 84, "checked": { "categories": { "ergonomics": "2026-11-02", "maintenance": "2026-11-02", "payments": "2026-11-02", "reliability": "2026-11-02", "schema": "2026-11-02", "security": "2026-11-02", "transparency": "2026-11-02" }, "last": "2026-11-02", "lastMoved": "2026-11-02", "oldest": "2026-11-02", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install cohere # or: npm i cohere-ai", "http": "curl --request POST \\\n --url https://api.cohere.ai/v2/chat \\\n --header 'accept: application/json' \\\n --header 'content-type: application/json' \\\n --header \"Authorization: bearer $CO_API_KEY\" \\\n --data '{\"model\":\"command-a-plus-05-2026\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/cohere-chat" }, "sameCompany": [ "cohere-embed", "cohere-transcribe-03-2026", "cohere-north", "north-mini-code-1-0" ], "area": "models", "unitPrices": [ { "item": "Command R input", "unit": "1m-tokens", "usd": 0.15 }, { "item": "Command R output", "unit": "1m-tokens", "usd": 0.6 }, { "item": "Command R7B input", "unit": "1m-tokens", "usd": 0.0375 }, { "item": "Command R7B output", "unit": "1m-tokens", "usd": 0.15 }, { "item": "Command R+ 08-2024 input", "unit": "1m-tokens", "usd": 2.5, "note": "Listed among legacy prices" }, { "item": "Command R+ 08-2024 output", "unit": "1m-tokens", "usd": 10, "note": "Listed among legacy prices" } ], "provenance": { "legalEntity": "Cohere Inc.", "domain": "cohere.com", "domainRegistered": "2000-03-07", "endpointOnVendorDomain": true, "terms": "https://cohere.com/saas-agreement", "privacy": "https://cohere.com/privacy", "statusPage": "https://status.cohere.com", "changelog": "https://docs.cohere.com/v2/changelog", "securityTxt": "none", "checked": "2026-10-09", "notes": [ "The Commercial SaaS Agreement (last updated 8 April 2025) names Cohere Inc., 171 John Street, Suite 200, Toronto, Ontario, and is governed by Ontario law.", "The privacy policy (last updated 1 May 2026) says it does not apply to customer inputs and outputs under an enterprise agreement, which the agreement and a DPA govern. The DPA is sent on request.", "The OpenAPI file names https://api.cohere.com as the server and the chat guide's examples call https://api.cohere.ai. Both are Cohere's.", "cohere.com/.well-known/security.txt answers 404. The trust centre holds a responsible disclosure policy for the bug bounty.", "status.cohere.ai redirects to status.cohere.com, whose robots.txt answers 404, so the host publishes no rules.", "RDAP for cohere.com gives a registration date of 2000-03-07." ], "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cohere-chat.json", "live": { "slug": "cohere-chat", "probe": { "target": "https://api.cohere.com/v2/chat", "method": "get", "lastAt": "2026-11-10T23:46:56.451373996Z", "lastOk": true, "lastStatus": 401, "lastMs": 140, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 148, "p95ms24h": 228, "samples24h": 244, "samples30d": 7904, "days": [ { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 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": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 248, "ok": 248 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 243, "ok": 243 }, { "date": "2026-11-10", "probes": 242, "ok": 242 } ], "since": "2026-10-09T00:00:00Z" }, "vendorStatus": { "page": "https://status.cohere.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-10T23:47:54.24927297Z" }, "versions": [ { "registry": "github", "name": "cohere-ai/cohere-python", "version": "7.3.2", "released": "2026-11-04", "seenAt": "2026-11-10T03:30:05.672657278Z" }, { "registry": "npm", "name": "cohere-ai", "version": "8.3.1", "seenAt": "2026-11-10T03:30:05.286409034Z" }, { "registry": "pypi", "name": "cohere", "version": "7.3.1", "released": "2026-11-04", "seenAt": "2026-11-10T03:30:05.172914961Z" } ], "githubStars": 408, "npmWeekly": 670578, "pypiWeekly": 2629269, "securityTxt": { "url": "https://cohere.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:07:22.890424476Z" }, "llmsTxt": { "url": "https://docs.cohere.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:42:42.882545869Z" }, "domain": { "domain": "cohere.com", "registered": "2000-03-07", "source": "https://rdap.verisign.com/com/v1/domain/cohere.com", "checkedAt": "2026-11-08T15:00:18.417824779Z" }, "pages": [ { "url": "https://docs.cohere.com/v2/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:16:22.626977823Z", "changedAt": "2026-11-05T12:29:46.428343553Z", "fingerprint": "de6e890a268c" }, { "url": "https://docs.cohere.com/docs/deprecations", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:16:20.523122795Z", "changedAt": "2026-11-05T12:29:44.384806051Z", "fingerprint": "a4d483f2b397" }, { "url": "https://cohere.com/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-10T16:12:18.314173073Z", "changedAt": "2026-11-06T13:24:23.148883162Z", "fingerprint": "1028bd69de2b" }, { "url": "https://cohere.com/saas-agreement", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:12:18.702746893Z", "changedAt": "2026-11-06T13:24:25.375763846Z", "fingerprint": "0bbd8836589f" } ], "models": { "command-r-08-2024": { "openrouterId": "cohere/command-r-08-2024", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "text" ], "promptCaching": false, "contextTokens": 128000, "maxOutput": 4000, "checkedAt": "2026-11-09T23:49:27.454762861Z" }, "command-r-plus-08-2024": { "openrouterId": "cohere/command-r-plus-08-2024", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "text" ], "promptCaching": false, "contextTokens": 128000, "maxOutput": 4000, "checkedAt": "2026-11-09T23:49:27.454762861Z" }, "command-r7b-12-2024": { "openrouterId": "cohere/command-r7b-12-2024", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "text" ], "promptCaching": false, "contextTokens": 128000, "maxOutput": 4000, "checkedAt": "2026-11-09T23:49:27.454762861Z" } }, "github": { "repo": "cohere-ai/cohere-python", "checkedAt": "2026-11-09T10:16:11.344772303Z", "stars": 407, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-04T20:35:32Z", "openIssues": 0, "openPRs": 21, "issuesOpened90d": 10, "issuesClosed90d": 10, "prsMerged90d": 8, "ci": { "branch": "main", "runs": 42, "success": 34, "failure": 8, "other": 0, "latest": "success", "latestAt": "2026-11-04T19:47:56Z" }, "replies": { "sampled": 25, "unanswered": 0, "medianDays": 9.2 } }, "updatedAt": "2026-11-10T23:47:54.24927297Z" }, "streak": { "days": 32, "from": "2026-10-09", "sinceWatching": true, "last": { "kind": "shutdown", "date": "2026-04-04", "what": "`embed-english-v2.0`, `embed-multilingual-v2.0`, `c4ai-aya-expanse-8b` and `c4ai-aya-vision-8b` retired", "source": "https://docs.cohere.com/docs/deprecations" }, "best": 32 } }, "answer": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 3 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.", "b": { "slug": "gemini-4-carbon", "name": "Gemini 4 Carbon", "vendor": "Google", "vendorUrl": "https://ai.google.dev", "kind": "model", "category": "inference", "summary": "Gemini 4 Carbon is Google's strongest Gemini model, for long agentic coding, cybersecurity and research work, on the paid tier of the Gemini API with a 1,048,576-token limit shared between input and output.", "url": "https://www.anchorterminal.com/tools/gemini-4-carbon", "markdownUrl": "https://www.anchorterminal.com/tools/gemini-4-carbon.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gemini-4-carbon.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json", "dns": "gemini-4-carbon.grade.anchorterminal.com", "license": "Closed model, used through the Gemini API and Google's apps under Google's terms", "transports": [], "remoteUrl": "https://generativelanguage.googleapis.com/v1beta", "packages": [], "auth": "api-key", "authNotes": "An `x-goog-api-key` from AI Studio on a project with billing, since Carbon is on the paid tier only, per the Gemini API listing and Google's developer post. Google AI Ultra subscribers can also use it in AI Studio and Antigravity. The `gemini-4-carbon-cyber-permissive` variant needs a project approved through Google's Fairwind Program.", "pricing": "usage", "pricingNotes": "Google's announcement gives an introductory $2 per million input tokens and $10 output, cached input 95% off, then $4 and $20, with no end date for the introduction. Paid tier only, no free tier. Every processed token is billed, thinking included (checked 2026-11-10).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Paid use needs billing on a Cloud project, per the Gemini API listing (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/guides/gemini-4-carbon", "llmsTxt": "https://ai.google.dev/gemini-api/docs/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "multimodal", "reasoning", "long-context", "tool-calling", "usage-priced", "card-required", "closed-source", "llms-txt", "new" ], "lastRelease": "2026-11-10", "graded": true, "anchor": { "graded": true, "score": 62.6, "grade": "B", "agentReady": false, "rank": 555, "ranked": true, "rankOf": 1518, "categoryRank": 22, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 93, "maintenance": 83, "payments": 20, "reliability": 40, "schema": 85, "security": 55, "transparency": 72 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-10" }, "negative": 0, "verdict": "Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.", "bestFor": "Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.", "strengths": [ "Introductory price of $2 input and $10 output per million tokens, with cached input 95% off", "1,048,576 tokens shared between input and output, with long decodes for big outputs", "Function calling, structured output, Google Search grounding and background execution", "Thinking levels LOW, MEDIUM (default) and HIGH, and implicit caching on by default", "The same API, keys and SDKs as Gemini 4 Argon, so switching is a model ID" ], "weaknesses": [ "Paid tier only, with no free tier to try it on", "temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400", "No explicit context caching, and prefilled model turns aren't accepted", "The price goes to $4 and $20 after an introduction with no end date given", "Benchmark figures are Google's own, and the launch stage isn't stated" ], "agentNotes": [ "Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-carbon and an x-goog-api-key on a billed project", "Set thinking_level (LOW, MEDIUM or HIGH) instead of thinking_budget, and don't send temperature, top_p or top_k", "Count output against the same 1,048,576-token limit as the input, and set max_output_tokens for long answers", "Put static prompt content first so implicit caching applies; explicit caches aren't supported", "Use gemini-4-argon for most coding and knowledge work, and Carbon for the hardest long tasks, as Google suggests" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 62.6 } ], "editorialScores": { "ergonomics": 93, "maintenance": 83, "payments": 20, "reliability": 40, "schema": 85, "security": 55, "transparency": 55 }, "provenanceScore": 89, "checked": { "categories": { "ergonomics": "2026-11-10", "maintenance": "2026-11-10", "payments": "2026-11-10", "reliability": "2026-11-10", "schema": "2026-11-10", "security": "2026-11-10", "transparency": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-4-carbon:generateContent\" \\\n -H \"x-goog-api-key: $GEMINI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"contents\":[{\"parts\":[{\"text\":\"hello\"}]}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/gemini-4-carbon" }, "sameCompany": [ "vertex-ai", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-memory-bank", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "sameModel": [ "gemini-api" ], "area": "models", "unitPrices": [ { "item": "Gemini 4 Carbon input", "unit": "1m-tokens", "usd": 2, "note": "Introductory; $4 after, date not given" }, { "item": "Gemini 4 Carbon cached input", "unit": "1m-tokens", "usd": 0.1, "note": "95% off input" }, { "item": "Gemini 4 Carbon output", "unit": "1m-tokens", "usd": 10, "note": "Introductory; $20 after" } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.", "endpointOnVendorDomain": true, "terms": "https://ai.google.dev/gemini-api/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://aistudio.google.com/status", "changelog": "https://ai.google.dev/gemini-api/docs/changelog", "securityTxt": "valid", "checked": "2026-11-10", "score": 89 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gemini-4-carbon.json", "live": { "slug": "gemini-4-carbon", "probe": { "target": "https://generativelanguage.googleapis.com/v1beta", "method": "get", "lastAt": "2026-11-10T23:47:03.904361517Z", "lastOk": true, "lastStatus": 404, "lastMs": 35, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 41, "p95ms24h": 130, "samples24h": 63, "samples30d": 63, "days": [ { "date": "2026-11-10", "probes": 63, "ok": 63 } ], "since": "2026-11-10T17:42:25.910455739Z" }, "vendorStatus": { "page": "https://aistudio.google.com/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-10T23:00:42.593790699Z" }, "updatedAt": "2026-11-10T23:47:03.904361517Z" }, "streak": { "days": 0, "from": "2026-11-10", "sinceWatching": true, "best": 0 } }, "edges": [ { "by": 27, "category": "reliability", "leads": "cohere-chat", "name": "Reliability", "reasons": { "a": "Hosted lines. status.cohere.com (incident.io) lists each Command model and the endpoints as components (20). Its feed, read on 2 November 2026, shows two incidents in the 90 days from 4 August. 'Multiple Endpoint Disruptions' on 1 September 2026, from 15:41 to 19:47 UTC, degraded the embeddings endpoint, embed-v4.0, two rerank models and `command-a-reasoning-08-2025` during a Google Cloud outage, rated minor and partial, and docs loading failed on 5 August. Nothing has been posted since 1 September, so minor incidents only (20). Chat limits are published per model, 20 requests a minute and 1,000 calls a month on a trial key and 500 a minute on a production key for Command A, R, R+ and R7B, while the four newest variants say contact sales (12 of 15). The errors page documents 429 with example messages that say to wait and try again later and links to the rate limits, with no Retry-After header, backoff timing or idempotency key, the reading cohere-embed takes of the same page (8 of 15). cohere.com/slo is titled Service Level Objective and its text is script-drawn, so it was unread and scores as absent (0). The v2 chat endpoint is the default docs version, but the sample response on the chat guide still carries `is_experimental` and the newest models are not open to production keys (7 of 10).", "b": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Carbon's launch stage isn't stated in Google's developer post, the Antigravity post or the Cloud developer guide read on 10 November, and the model ID carries no preview label, so half (5 of 10, a judgement call; Argon's GA earned the platform 10). 10 + 5 + 5 + 15 + 0 + 5 = 40." }, "scores": { "a": 67, "b": 40 } }, { "by": 21, "category": "ergonomics", "leads": "gemini-4-carbon", "name": "Agent ergonomics", "reasons": { "a": "Model reading. Function calling with `tool_choice` REQUIRED or NONE and `strict_tools`, which the reference marks beta (17 of 20). `response_format` takes `json_object` or a JSON Schema, with limits documented and no support in RAG mode (13 of 15). The usage object reports `cached_tokens`, and no guide or price for prompt caching was found (5 of 15). Context is 256,000 tokens on Command A and Command A Reasoning and 128,000 on Command A+ (10 of 15). `/v2/batches` runs a batch from an uploaded dataset, with no price or discount found (6 of 10). Official SDKs for Python, TypeScript, Java and Go (10). Error messages are specific and readable, with no stable error codes (11 of 15).", "b": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output (13 of 15). Implicit caching with durable caching on by default, cached input 95% off, explicit caches not supported, per the Cloud guide read on 10 November (15). 1,048,576 tokens shared between input and output (15). Batch at half price on the platform (10). Python and JavaScript SDKs (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 15 + 15 + 10 + 10 + 10 = 93." }, "scores": { "a": 72, "b": 93 } }, { "by": 15, "category": "payments", "leads": "cohere-chat", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 in the docs, the OpenAPI file or the pricing page (0). The docs say Command models are billed per input and output token. The pricing page, read on 2 November 2026, now carries per-unit prices in its own page data, Command R at $0.15 input and $0.60 output and Command R7B at $0.0375 and $0.15 per million tokens, with Command R+ 08-2024 at $2.50 and $10.00 among legacy prices and Command A+ shown as free. No price is published for Command A, Reasoning, Vision or Translate, so the line takes 15 rather than the full 20 (15 of 20). A trial key is created at sign-up and is free with no card (20). Sign-up is in a browser, and a production key needs an Owner to complete a Go to Production form (0).", "b": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Introductory prices published in Google's 28 October announcement without a login, $2 and $10, then $4 and $20; the Gemini API pricing page as read on 10 November showed no Carbon row, so the figures rest on the announcement (20). No free tier: Google's developer post puts Carbon on the paid tier (0). A Google account and AI Studio for a key (0). 0 + 20 + 0 + 0 = 20." }, "scores": { "a": 35, "b": 20 } }, { "by": 11, "category": "maintenance", "leads": "gemini-4-carbon", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. The last dated release on the Chat endpoint is still North Small Translate on 9 September 2026, 54 days before this check. The last Command model is Command A+ on 20 May 2026. Rerank 5 (21 October) and Embed 5 (30 September) aren't chat changes, so we score the 90-day band (20 of 30). The deprecations page defines Active, Legacy, Deprecated and Shutdown and promises email notice, with no minimum notice period (6 of 12). No chat model was retired or announced for retirement in the last 90 days. The newest entry on the page is still two Aya models retired on 4 April 2026 (8 of 8). Dated changelog with four entries since 4 August (27 August, 9 September, 30 September, 21 October), one of them for a chat model (12 of 15). SDK issue replies not sampled (5 of 10). Python SDK 7.2.0 and 7.3.0, TypeScript 8.2.0 (19 October) and 8.3.0, and Go v2.20.0 tagged on 21 October 2026, Java at 1.12.0 (15). The Python SDK is generated from the OpenAPI file and has a CI workflow, whose runs we did not read (6 of 10).", "b": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released to developers on 10 November 2026, with the platform's changelog (30). Deprecations with earliest dates and no stated minimum notice (4 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 4 + 4 + 15 + 5 + 15 + 10 = 83." }, "scores": { "a": 72, "b": 83 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Cohere", "b": "Google", "name": "Vendor" }, { "a": "https://api.cohere.com/v2/chat", "b": "https://generativelanguage.googleapis.com/v1beta", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Freemium", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under Cohere's Commercial SaaS Agreement. The SDKs are MIT", "b": "Closed model, used through the Gemini API and Google's apps under Google's terms", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-09-09", "b": "2026-11-10", "name": "Last release" }, { "a": "2025-04-08", "b": "2026-04-28", "name": "Terms last updated" }, { "a": "2026-05-01", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "yes", "b": "yes", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "yes", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 3 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.", "question": "Which is better for AI agents, Cohere Chat API (Command models) or Gemini 4 Carbon?" }, { "answer": "Both need an API key.", "question": "Do Cohere Chat API (Command models) and Gemini 4 Carbon need an API key?" }, { "answer": "Yes. Cohere Chat API (Command models) has a hosted endpoint at https://api.cohere.com/v2/chat and Gemini 4 Carbon at https://generativelanguage.googleapis.com/v1beta.", "question": "Can an agent call Cohere Chat API (Command models) and Gemini 4 Carbon without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 67 against 40", "Payments \u0026 pricing, 35 against 20" ], "also": [ "Free to start without a card" ], "goodFor": "Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.", "slug": "cohere-chat", "watchFor": "Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault" }, { "aheadOn": [ "Agent ergonomics, 93 against 72", "Maintenance \u0026 community, 83 against 72" ], "also": null, "goodFor": "Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.", "slug": "gemini-4-carbon", "watchFor": "Paid tier only, with no free tier to try it on" } ], "history": { "cohere-chat": [ { "causes": [ "evidence", "correction" ], "date": "2026-11-02", "delta": 0.9, "from": 64.7, "fromGrade": "B", "to": 65.6, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-28", "delta": 0, "from": 64.7, "fromGrade": "B", "to": 64.7, "toGrade": "B" } ], "gemini-4-carbon": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.json", "title": "Amazon Bedrock vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.json", "title": "Amazon Bedrock vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.json", "title": "Claude API vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.json", "title": "Claude API vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-cohere-chat.json", "title": "Antseed vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/antseed-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.json", "title": "Antseed vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat.json", "title": "Azure OpenAI in Foundry Models vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-carbon.json", "title": "Azure OpenAI in Foundry Models vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-cohere-chat.json", "title": "BlockRun.AI vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.json", "title": "BlockRun.AI vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon" }, { "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-gemini-4-carbon.json", "title": "Cerebras Inference vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-cohere-chat.json", "title": "Claude Fable 5.2 vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-carbon.json", "title": "Claude Fable 5.2 vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-cohere-chat.json", "title": "Claude Mythos 5.2 vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-carbon.json", "title": "Claude Mythos 5.2 vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-cohere-chat.json", "title": "Cloudflare AI Gateway vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-carbon.json", "title": "Cloudflare AI Gateway vs Gemini 4 Carbon", "url": 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"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/cohere-chat-vs-minimax-api.json", "title": "Cohere Chat API (Command models) vs MiniMax API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-api.json", "title": "Cohere Chat API (Command models) vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember.json", "title": "Cohere Chat API (Command models) vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.json", "title": "Cohere Chat API (Command models) vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-nemotron-3-5-super-vl.json", "title": "Cohere Chat API (Command models) vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-novita-ai.json", "title": "Cohere Chat API (Command models) vs Novita AI", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api.json", "title": "Cohere Chat API (Command models) vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-openrouter.json", "title": "Cohere Chat API (Command models) vs OpenRouter", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-prism-inference.json", "title": "Cohere Chat API (Command models) vs Prism Inference", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-ramp-router.json", "title": "Cohere Chat API (Command models) vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam.json", "title": "Cohere Chat API (Command models) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-routerplus.json", "title": "Cohere Chat API (Command models) vs RouterPlus", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova.json", "title": "Cohere Chat API (Command models) vs SambaCloud", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.json", "title": "Cohere Chat API (Command models) vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-simplismart.json", "title": "Cohere Chat API (Command models) vs Simplismart", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api.json", "title": "Cohere Chat API (Command models) vs StepFun API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-swe-2-flash.json", "title": "Cohere Chat API (Command models) vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-tencent-tokenhub.json", "title": "Cohere Chat API (Command models) vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference.json", "title": "Cohere Chat API (Command models) vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway.json", "title": "Cohere Chat API (Command models) vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.json", "title": "Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api.json", "title": "Cohere Chat API (Command models) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.json", "title": "DeepInfra vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon.json", "title": "DeepSeek API vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon.json", "title": "Eden AI vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon.json", "title": "Glimpse vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-carbon.json", "title": "Fireworks AI Inference vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-gemini-api.json", "title": "Gemini 4 Carbon vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-groq.json", "title": "Gemini 4 Carbon vs GroqCloud", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-hugging-face-inference-providers.json", "title": "Gemini 4 Carbon vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-inkling-2-small.json", "title": "Gemini 4 Carbon vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-jais-3.json", "title": "Gemini 4 Carbon vs Jais 3", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-meta-model-api.json", "title": "Gemini 4 Carbon vs Meta Model API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api.json", "title": "Gemini 4 Carbon vs MiniMax API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api.json", "title": "Gemini 4 Carbon vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember.json", "title": "Gemini 4 Carbon vs Muse Ember", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.json", "title": "Gemini 4 Carbon vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl.json", "title": "Gemini 4 Carbon vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.json", "title": "Gemini 4 Carbon vs Novita AI", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openai-api.json", "title": "Gemini 4 Carbon vs OpenAI API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openrouter.json", "title": "Gemini 4 Carbon vs OpenRouter", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-prism-inference.json", "title": "Gemini 4 Carbon vs Prism Inference", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-ramp-router.json", "title": "Gemini 4 Carbon vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.json", "title": "Gemini 4 Carbon vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus.json", "title": "Gemini 4 Carbon vs RouterPlus", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.json", "title": "Gemini 4 Carbon vs SambaCloud", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow.json", "title": "Gemini 4 Carbon vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.json", "title": "Gemini 4 Carbon vs Simplismart", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.json", "title": "Gemini 4 Carbon vs StepFun API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.json", "title": "Gemini 4 Carbon vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.json", "title": "Gemini 4 Carbon vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.json", "title": "Gemini 4 Carbon vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.json", "title": "Gemini 4 Carbon vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.json", "title": "Gemini 4 Carbon vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api.json", "title": "Gemini 4 Carbon vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api" } ], "panel": null, "scores": [ { "by": 27, "cohere-chat": 67, "edge": "cohere-chat", "gemini-4-carbon": 40, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 1, "cohere-chat": 84, "edge": "gemini-4-carbon", "gemini-4-carbon": 85, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 21, "cohere-chat": 72, "edge": "gemini-4-carbon", "gemini-4-carbon": 93, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 0, "cohere-chat": 55, "edge": "", "gemini-4-carbon": 55, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 15, "cohere-chat": 35, "edge": "cohere-chat", "gemini-4-carbon": 20, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 11, "cohere-chat": 72, "edge": "gemini-4-carbon", "gemini-4-carbon": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 3, "cohere-chat": 75, "edge": "cohere-chat", "gemini-4-carbon": 72, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 3 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "cohere-chat": "A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.", "gemini-4-carbon": "Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon", "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.min.md" }, "markdown": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 3 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community. Both do llm inference.\n\n- Cohere Chat API (Command models): grade B, 65.6/100, rank #411 of 1518. Markdown https://www.anchorterminal.com/tools/cohere-chat.md · JSON https://www.anchorterminal.com/api/v1/tools/cohere-chat.json\n- Gemini 4 Carbon: grade B, 62.6/100, rank #555 of 1518. Markdown https://www.anchorterminal.com/tools/gemini-4-carbon.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 1000 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Cohere Chat API (Command models) (B)\n\nGood for: Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.\n\nAhead on:\n- Reliability, 67 against 40\n- Payments \u0026 pricing, 35 against 20\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault\n\n### Gemini 4 Carbon (B)\n\nGood for: Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.\n\nAhead on:\n- Agent ergonomics, 93 against 72\n- Maintenance \u0026 community, 83 against 72\n\nWatch for: Paid tier only, with no free tier to try it on\n\n\n## Why the edge\n\n### Reliability: Cohere Chat API (Command models) +27\n\n- Cohere Chat API (Command models) (67): Hosted lines. status.cohere.com (incident.io) lists each Command model and the endpoints as components (20). Its feed, read on 2 November 2026, shows two incidents in the 90 days from 4 August. 'Multiple Endpoint Disruptions' on 1 September 2026, from 15:41 to 19:47 UTC, degraded the embeddings endpoint, embed-v4.0, two rerank models and `command-a-reasoning-08-2025` during a Google Cloud outage, rated minor and partial, and docs loading failed on 5 August. Nothing has been posted since 1 September, so minor incidents only (20). Chat limits are published per model, 20 requests a minute and 1,000 calls a month on a trial key and 500 a minute on a production key for Command A, R, R+ and R7B, while the four newest variants say contact sales (12 of 15). The errors page documents 429 with example messages that say to wait and try again later and links to the rate limits, with no Retry-After header, backoff timing or idempotency key, the reading cohere-embed takes of the same page (8 of 15). cohere.com/slo is titled Service Level Objective and its text is script-drawn, so it was unread and scores as absent (0). The v2 chat endpoint is the default docs version, but the sample response on the chat guide still carries `is_experimental` and the newest models are not open to production keys (7 of 10).\n- Gemini 4 Carbon (40): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Carbon's launch stage isn't stated in Google's developer post, the Antigravity post or the Cloud developer guide read on 10 November, and the model ID carries no preview label, so half (5 of 10, a judgement call; Argon's GA earned the platform 10). 10 + 5 + 5 + 15 + 0 + 5 = 40.\n\n### Agent ergonomics: Gemini 4 Carbon +21\n\n- Cohere Chat API (Command models) (72): Model reading. Function calling with `tool_choice` REQUIRED or NONE and `strict_tools`, which the reference marks beta (17 of 20). `response_format` takes `json_object` or a JSON Schema, with limits documented and no support in RAG mode (13 of 15). The usage object reports `cached_tokens`, and no guide or price for prompt caching was found (5 of 15). Context is 256,000 tokens on Command A and Command A Reasoning and 128,000 on Command A+ (10 of 15). `/v2/batches` runs a batch from an uploaded dataset, with no price or discount found (6 of 10). Official SDKs for Python, TypeScript, Java and Go (10). Error messages are specific and readable, with no stable error codes (11 of 15).\n- Gemini 4 Carbon (93): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output (13 of 15). Implicit caching with durable caching on by default, cached input 95% off, explicit caches not supported, per the Cloud guide read on 10 November (15). 1,048,576 tokens shared between input and output (15). Batch at half price on the platform (10). Python and JavaScript SDKs (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 15 + 15 + 10 + 10 + 10 = 93.\n\n### Payments \u0026 pricing: Cohere Chat API (Command models) +15\n\n- Cohere Chat API (Command models) (35): No x402, MPP or L402 in the docs, the OpenAPI file or the pricing page (0). The docs say Command models are billed per input and output token. The pricing page, read on 2 November 2026, now carries per-unit prices in its own page data, Command R at $0.15 input and $0.60 output and Command R7B at $0.0375 and $0.15 per million tokens, with Command R+ 08-2024 at $2.50 and $10.00 among legacy prices and Command A+ shown as free. No price is published for Command A, Reasoning, Vision or Translate, so the line takes 15 rather than the full 20 (15 of 20). A trial key is created at sign-up and is free with no card (20). Sign-up is in a browser, and a production key needs an Owner to complete a Go to Production form (0).\n- Gemini 4 Carbon (20): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Introductory prices published in Google's 28 October announcement without a login, $2 and $10, then $4 and $20; the Gemini API pricing page as read on 10 November showed no Carbon row, so the figures rest on the announcement (20). No free tier: Google's developer post puts Carbon on the paid tier (0). A Google account and AI Studio for a key (0). 0 + 20 + 0 + 0 = 20.\n\n### Maintenance \u0026 community: Gemini 4 Carbon +11\n\n- Cohere Chat API (Command models) (72): Model reading. The last dated release on the Chat endpoint is still North Small Translate on 9 September 2026, 54 days before this check. The last Command model is Command A+ on 20 May 2026. Rerank 5 (21 October) and Embed 5 (30 September) aren't chat changes, so we score the 90-day band (20 of 30). The deprecations page defines Active, Legacy, Deprecated and Shutdown and promises email notice, with no minimum notice period (6 of 12). No chat model was retired or announced for retirement in the last 90 days. The newest entry on the page is still two Aya models retired on 4 April 2026 (8 of 8). Dated changelog with four entries since 4 August (27 August, 9 September, 30 September, 21 October), one of them for a chat model (12 of 15). SDK issue replies not sampled (5 of 10). Python SDK 7.2.0 and 7.3.0, TypeScript 8.2.0 (19 October) and 8.3.0, and Go v2.20.0 tagged on 21 October 2026, Java at 1.12.0 (15). The Python SDK is generated from the OpenAPI file and has a CI workflow, whose runs we did not read (6 of 10).\n- Gemini 4 Carbon (83): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released to developers on 10 November 2026, with the platform's changelog (30). Deprecations with earliest dates and no stated minimum notice (4 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 4 + 4 + 15 + 5 + 15 + 10 = 83.\n\n## Score by category\n\n| Category | Weight | Cohere Chat API (Command models) | Gemini 4 Carbon | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 67 | 40 | Cohere Chat API (Command models) +27 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 84 | 85 | Gemini 4 Carbon +1 |\n| Agent ergonomics | 13% (16.2 this run) | 72 | 93 | Gemini 4 Carbon +21 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 55 | even |\n| Payments \u0026 pricing | 10% (12.5 this run) | 35 | 20 | Cohere Chat API (Command models) +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 72 | 83 | Gemini 4 Carbon +11 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 75 | 72 | Cohere Chat API (Command models) +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **65.6 · B** | **62.6 · B** | |\n\n## Facts side by side\n\n| Fact | Cohere Chat API (Command models) | Gemini 4 Carbon |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Cohere | Google |\n| Hosted endpoint | `https://api.cohere.com/v2/chat` | `https://generativelanguage.googleapis.com/v1beta` |\n| Transports | HTTP | |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under Cohere's Commercial SaaS Agreement. The SDKs are MIT | Closed model, used through the Gemini API and Google's apps under Google's terms |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-09 | 2026-11-10 |\n| Terms last updated | 2025-04-08 | 2026-04-28 |\n| Privacy policy last updated | 2026-05-01 | 2026-10-01 |\n| Customer content may train models | yes | yes |\n| Terms restrict automated access | not found in the text | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### Cohere Chat API (Command models)\n\n- +0.9 on 2 November 2026: new evidence, correction\n- no change on 28 October 2026: checklist\n\n### Gemini 4 Carbon\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Cohere Chat API (Command models).** A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.\n\n**Gemini 4 Carbon.** Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.\n\n## Before you call either\n\n### Cohere Chat API (Command models)\n\n1. Call `POST https://api.cohere.com/v2/chat` with `Authorization: bearer \u003ckey\u003e`. `model` and `messages` are the only required fields\n2. Use `command-a-03-2025`, `command-r-08-2024`, `command-r-plus-08-2024` or `command-r7b-12-2024` for production traffic. Newer variants stay at trial limits on a production key, and only the R models have published prices\n3. Keep a trial key under 20 chat requests a minute and 1,000 calls a month, and do not use it for commercial work\n4. Set `response_format` with a `json_schema` for structured output, and tell the model to produce JSON when using `json_object` without a schema\n5. Ask the account Owner to turn off training under Data Controls in the dashboard before sending confidential prompts\n\n### Gemini 4 Carbon\n\n1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-carbon and an x-goog-api-key on a billed project\n2. Set thinking_level (LOW, MEDIUM or HIGH) instead of thinking_budget, and don't send temperature, top_p or top_k\n3. Count output against the same 1,048,576-token limit as the input, and set max_output_tokens for long answers\n4. Put static prompt content first so implicit caching applies; explicit caches aren't supported\n5. Use gemini-4-argon for most coding and knowledge work, and Carbon for the hardest long tasks, as Google suggests\n\n## Questions\n\n### Which is better for AI agents, Cohere Chat API (Command models) or Gemini 4 Carbon?\n\nCohere Chat API (Command models) scores 65.6 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 3 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.\n\n### Do Cohere Chat API (Command models) and Gemini 4 Carbon need an API key?\n\nBoth need an API key.\n\n### Can an agent call Cohere Chat API (Command models) and Gemini 4 Carbon without installing anything?\n\nYes. Cohere Chat API (Command models) has a hosted endpoint at https://api.cohere.com/v2/chat and Gemini 4 Carbon at https://generativelanguage.googleapis.com/v1beta.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cohere-chat\", \"b\": \"gemini-4-carbon\"}`. From a terminal: `anchor compare cohere-chat gemini-4-carbon`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cohere-chat.json and https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json\n\n## Other comparisons with Cohere Chat API (Command models) or Gemini 4 Carbon\n\n- [Amazon Bedrock vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.md)\n- [Amazon Bedrock vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.md)\n- [Claude API vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Antseed vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/antseed-vs-cohere-chat.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- 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[Gemini 4 Carbon vs SambaCloud](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.md)\n- [Gemini 4 Carbon vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow.md)\n- [Gemini 4 Carbon vs Simplismart](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.md)\n- [Gemini 4 Carbon vs StepFun API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.md)\n- [Gemini 4 Carbon vs SWE-2 Flash](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.md)\n- [Gemini 4 Carbon vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.md)\n- [Gemini 4 Carbon vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.md)\n- [Gemini 4 Carbon vs Vercel AI Gateway](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.md)\n- [Gemini 4 Carbon vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.md)\n- [Gemini 4 Carbon vs xAI API (Grok)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Cohere Chat API (Command models) vs Gemini 4 Carbon", "url": "" } ], "description": "Cohere Chat scores 65.6 (B) to Gemini 4 Carbon's 62.6 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Cohere Chat API (Command models) B 65.6", "Gemini 4 Carbon B 62.6", "scores" ], "h1": "Cohere Chat API (Command models) vs Gemini 4 Carbon", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/cohere-chat-vs-gemini-4-carbon", "published": "2026-10-01", "section": "tools", "title": "Cohere Chat vs Gemini 4 Carbon for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon" }, "tokens": { "markdown": 6350, "slim": 880 }, "version": 1 }