{
  "data": {
    "a": {
      "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": [
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              "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
      }
    },
    "answer": "Together AI Inference scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.",
    "b": {
      "slug": "together-inference",
      "name": "Together AI Inference",
      "vendor": "Together Computer, Inc.",
      "vendorUrl": "https://www.together.ai",
      "kind": "http-api",
      "category": "inference",
      "summary": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput. Model-dependent capabilities include tool calling, structured outputs and vision.",
      "url": "https://www.anchorterminal.com/tools/together-inference",
      "markdownUrl": "https://www.anchorterminal.com/tools/together-inference.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/together-inference.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/together-inference.json",
      "dns": "together-inference.grade.anchorterminal.com",
      "repo": "https://github.com/togethercomputer/together-py",
      "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.together.ai/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "together",
          "main": true
        },
        {
          "registry": "npm",
          "name": "together-ai",
          "main": true
        }
      ],
      "auth": "api-key",
      "authNotes": "Bearer API keys are scoped to projects, can expire and can be revoked separately. A key has full access to resources in its project. There are no per-key spending or rate limits; legacy default-project keys should be replaced.",
      "pricing": "paid",
      "pricingNotes": "Prepaid usage with a $15 minimum first credit purchase, then $5 minimum top-ups. No free trial. GPT OSS 120B is $0.15 per million input tokens and $0.60 per million output tokens. Dedicated hardware and provisioned throughput have separate rates.",
      "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": 10,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-19"
      },
      "docsUrl": "https://docs.together.ai",
      "llmsTxt": "https://docs.together.ai/llms.txt",
      "openapi": "https://docs.together.ai/openapi.yaml",
      "capabilities": [
        "inference.llm",
        "inference.open-weights"
      ],
      "tags": [
        "official",
        "http-api",
        "inference",
        "api-key",
        "openapi",
        "llms-txt",
        "paid"
      ],
      "lastRelease": "2026-10-23",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 67.8,
        "grade": "B",
        "agentReady": false,
        "rank": 304,
        "ranked": true,
        "rankOf": 1518,
        "categoryRank": 15,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 85,
          "maintenance": 65,
          "payments": 20,
          "reliability": 75,
          "schema": 93,
          "security": 70,
          "transparency": 74
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-01"
        },
        "negative": -3,
        "negativeNotes": [
          "2026-08-19 to 2026-08-27. Together removed GA serverless models with notice posted only on the day of removal. Changelog entries of 19, 21, 25 and 27 August say FLUX.1 schnell, Qwen2.5 7B, Kimi K2.6, Cogito v2.1 671B, Gemma 3n E4B, Llama Guard 4 12B, Nemotron 3 Ultra, Pearl's Gemma 4 31B, DeepSeek V4 Pro and Kimi K2.7 Code \"have been deprecated and are no longer available on serverless\", with no earlier entry announcing their removal and no preview label, while the deprecation policy promises 2 or 3 weeks' notice for serverless endpoints. Read at the floor, as fireworks-inference's same-day removals of 27 August were, -3 (https://docs.together.ai/docs/changelog.md)."
        ],
        "verdict": "A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted.",
        "bestFor": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.",
        "strengths": [
          "Public OpenAPI 3.1, Markdown documentation and Python and TypeScript SDKs",
          "Project-scoped API keys with optional expiry and per-key cost attribution",
          "Serverless, batch, dedicated and provisioned-throughput options",
          "Status page with a monitor per serverless model and 90 days of daily history",
          "US-only serverless processing through us-api.together.ai since 16 October 2026, at 1.25 times standard rates"
        ],
        "weaknesses": [
          "A $15 credit purchase is required before platform access; no free trial",
          "Prompt and response storage is on by default; zero data retention must be enabled for the organisation",
          "Serverless has no guaranteed capacity outside provisioned throughput, and API keys have no individual spend caps",
          "Serverless models removed on 19, 21, 25 and 27 August 2026 were announced in the changelog only on the day"
        ],
        "agentNotes": [
          "Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.",
          "For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.",
          "Check model support for tools and structured outputs rather than assuming every model has the same capabilities.",
          "Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.",
          "Check the deprecation schedule before choosing a model. Qwen3.8-2.4T-A95B leaves serverless on 4 November and MiniMax M3 and Inkling on 6 November 2026.",
          "Pin the SDK major version. Python SDK 3.0 and TypeScript SDK 1.0 (22 October 2026) drop `/v1` from the base URL and the `beta` paths"
        ],
        "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": 67.8
          }
        ],
        "editorialScores": {
          "ergonomics": 85,
          "maintenance": 65,
          "payments": 20,
          "reliability": 75,
          "schema": 93,
          "security": 70,
          "transparency": 65
        },
        "provenanceScore": 83,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-01",
            "maintenance": "2026-11-01",
            "payments": "2026-11-01",
            "reliability": "2026-11-01",
            "schema": "2026-11-01",
            "security": "2026-11-01",
            "transparency": "2026-11-01"
          },
          "last": "2026-11-01",
          "lastMoved": "2026-11-01",
          "oldest": "2026-11-01",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "http": "curl 'https://api.together.ai/v1/chat/completions' -H \"Authorization: Bearer $TOGETHER_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"openai/gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/together-inference"
      },
      "sameCompany": [
        "together-fine-tuning",
        "together-gpu-clusters",
        "together-code-sandbox"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "GPT OSS 120B input",
          "unit": "1m-tokens",
          "usd": 0.15,
          "note": "Shared/serverless standard rate, per million tokens, checked 1 November 2026"
        },
        {
          "item": "GPT OSS 120B output",
          "unit": "1m-tokens",
          "usd": 0.6,
          "note": "Shared/serverless standard rate, per million tokens, checked 1 November 2026"
        }
      ],
      "provenance": {
        "legalEntity": "Together Computer, Inc.",
        "domain": "together.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://www.together.ai/terms-of-service",
        "privacy": "https://www.together.ai/privacy",
        "statusPage": "https://status.together.ai",
        "changelog": "https://docs.together.ai/docs/changelog",
        "securityTxt": "valid",
        "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.",
          "security.txt names the HackerOne programme and expires on 30 September 2028."
        ],
        "score": 83
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/together-inference.json",
      "live": {
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          "method": "get",
          "lastAt": "2026-11-10T23:47:30.912551409Z",
          "lastOk": true,
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          "samples24h": 244,
          "samples30d": 5570,
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              "probes": 252,
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              "probes": 253,
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              "probes": 250,
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              "probes": 252,
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              "date": "2026-10-27",
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              "date": "2026-10-28",
              "probes": 250,
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              "probes": 249,
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              "probes": 248,
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            {
              "date": "2026-11-06",
              "probes": 241,
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            {
              "date": "2026-11-08",
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            {
              "date": "2026-11-09",
              "probes": 243,
              "ok": 243
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            {
              "date": "2026-11-10",
              "probes": 242,
              "ok": 242
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          "since": "2026-10-19T00:00:00Z"
        },
        "vendorStatus": {
          "page": "https://status.together.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-11-03T15:50:27.832032204Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "togethercomputer/together-py",
            "version": "v3.1.1",
            "released": "2026-11-04",
            "seenAt": "2026-11-10T04:25:32.777071737Z"
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          {
            "registry": "pypi",
            "name": "together",
            "version": "3.1.1",
            "released": "2026-11-04",
            "seenAt": "2026-11-10T04:25:32.631692985Z"
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        "githubStars": 12,
        "npmWeekly": 99070,
        "pypiWeekly": 432642,
        "securityTxt": {
          "url": "https://together.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2028-09-30T00:00:00.000Z",
          "checkedAt": "2026-11-10T16:08:07.811051873Z"
        },
        "llmsTxt": {
          "url": "https://docs.together.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-10T15:44:59.235833106Z"
        },
        "domain": {
          "domain": "together.ai",
          "registered": "2017-12-16",
          "source": "https://rdap.identitydigital.services/rdap/domain/together.ai",
          "checkedAt": "2026-11-08T14:49:59.126665901Z"
        },
        "github": {
          "repo": "togethercomputer/together-py",
          "checkedAt": "2026-11-09T09:54:49.79539179Z",
          "stars": 12,
          "archived": false,
          "issuesEnabled": true,
          "pushedAt": "2026-11-08T04:08:32Z",
          "openIssues": 4,
          "openPRs": 45,
          "issuesOpened90d": 2,
          "issuesClosed90d": 1,
          "prsMerged90d": 96,
          "ci": {
            "branch": "main",
            "runs": 50,
            "success": 16,
            "failure": 0,
            "other": 34,
            "latest": "skipped",
            "latestAt": "2026-11-04T18:45:39Z"
          },
          "replies": {
            "sampled": 7,
            "unanswered": 4,
            "medianDays": 14.2
          }
        },
        "updatedAt": "2026-11-10T23:47:30.912551409Z"
      },
      "streak": {
        "days": 22,
        "from": "2026-10-19",
        "sinceWatching": true,
        "best": 22
      }
    },
    "edges": [
      {
        "by": 35,
        "category": "reliability",
        "leads": "together-inference",
        "name": "Reliability",
        "reasons": {
          "a": "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.",
          "b": "Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75."
        },
        "scores": {
          "a": 40,
          "b": 75
        }
      },
      {
        "by": 18,
        "category": "maintenance",
        "leads": "gemini-4-carbon",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "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.",
          "b": "Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0)."
        },
        "scores": {
          "a": 83,
          "b": 65
        }
      },
      {
        "by": 15,
        "category": "security",
        "leads": "together-inference",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "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. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Carbon is on the paid tier only, and Google's terms say paid-tier content isn't used to improve products; AI Studio use under a Google AI Ultra subscription falls under terms we didn't read, so 15 of 20 (a judgement call; the platform's 10 is for its free tier). Abuse retention with no number, and new paid projects store requests by default since 26 October (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 15 + 5 + 15 + 5 = 55.",
          "b": "Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20)."
        },
        "scores": {
          "a": 55,
          "b": 70
        }
      },
      {
        "by": 8,
        "category": "schema",
        "leads": "together-inference",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "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. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.",
          "b": "Public OpenAPI 3.1 (25), llms.txt and Markdown docs (10), endpoint and model-capability guidance (16 of 20), typed inputs and constraints (13 of 15), examples and documented errors (14 of 15), and versioned endpoints with a dated changelog (15)."
        },
        "scores": {
          "a": 85,
          "b": 93
        }
      },
      {
        "by": 8,
        "category": "ergonomics",
        "leads": "gemini-4-carbon",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "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.",
          "b": "Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15)."
        },
        "scores": {
          "a": 93,
          "b": 85
        }
      }
    ],
    "facts": [
      {
        "a": "Model API",
        "b": "HTTP API",
        "name": "Kind"
      },
      {
        "a": "Google",
        "b": "Together Computer, Inc.",
        "name": "Vendor"
      },
      {
        "a": "https://generativelanguage.googleapis.com/v1beta",
        "b": "https://api.together.ai/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Paid",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Closed model, used through the Gemini API and Google's apps under Google's terms",
        "b": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-11-10",
        "b": "2026-10-23",
        "name": "Last release"
      },
      {
        "a": "2026-04-28",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "2026-10-01",
        "b": "no date given",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "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": "none",
        "b": "10 stars",
        "name": "Popularity"
      },
      {
        "a": "none",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Together AI Inference scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.",
        "question": "Which is better for AI agents, Gemini 4 Carbon or Together AI Inference?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Gemini 4 Carbon and Together AI Inference need an API key?"
      },
      {
        "answer": "Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Together AI Inference at https://api.together.ai/v1.",
        "question": "Can an agent call Gemini 4 Carbon and Together AI Inference without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Agent ergonomics, 93 against 85",
          "Maintenance \u0026 community, 83 against 65"
        ],
        "also": [
          "No incidents deducted, where Together AI Inference loses 3 points for them"
        ],
        "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"
      },
      {
        "aheadOn": [
          "Reliability, 75 against 40",
          "Schema \u0026 documentation, 93 against 85",
          "Security \u0026 auth, 70 against 55"
        ],
        "also": null,
        "goodFor": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.",
        "slug": "together-inference",
        "watchFor": "A $15 credit purchase is required before platform access; no free trial"
      }
    ],
    "history": {
      "gemini-4-carbon": null,
      "together-inference": [
        {
          "causes": [
            "evidence",
            "correction"
          ],
          "date": "2026-11-01",
          "delta": 0,
          "from": 67.8,
          "fromGrade": "B",
          "to": 67.8,
          "toGrade": "B"
        },
        {
          "causes": [
            "method"
          ],
          "date": "2026-10-27",
          "delta": 0,
          "from": 67.8,
          "fromGrade": "B",
          "to": 67.8,
          "toGrade": "B"
        }
      ]
    },
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
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      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.json",
        "title": "Amazon Bedrock vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference"
      },
      {
        "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/anthropic-api-vs-together-inference.json",
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        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference"
      },
      {
        "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/antseed-vs-together-inference.json",
        "title": "Antseed vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-together-inference"
      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.json",
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        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference"
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        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.json",
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        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon"
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        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon.json",
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        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon"
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        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference.json",
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        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference"
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      {
        "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.json",
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        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-carbon.json",
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        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-carbon"
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        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.json",
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        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon"
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      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference.json",
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        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference"
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      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.json",
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        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-together-inference.json",
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        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon"
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        "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",
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    "scores": [
      {
        "by": 35,
        "edge": "together-inference",
        "gemini-4-carbon": 40,
        "key": "reliability",
        "name": "Reliability",
        "together-inference": 75,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 8,
        "edge": "together-inference",
        "gemini-4-carbon": 85,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "together-inference": 93,
        "weight": 13
      },
      {
        "by": 8,
        "edge": "gemini-4-carbon",
        "gemini-4-carbon": 93,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "together-inference": 85,
        "weight": 13
      },
      {
        "by": 15,
        "edge": "together-inference",
        "gemini-4-carbon": 55,
        "key": "security",
        "name": "Security \u0026 auth",
        "together-inference": 70,
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "gemini-4-carbon": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "together-inference": 20,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 18,
        "edge": "gemini-4-carbon",
        "gemini-4-carbon": 83,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "together-inference": 65,
        "weight": 7
      },
      {
        "by": 2,
        "edge": "together-inference",
        "gemini-4-carbon": 72,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "together-inference": 74,
        "weight": 7
      }
    ],
    "summary": "Together AI Inference scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community. Both do llm inference.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "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.",
      "together-inference": "A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted."
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  "markdown": "Together AI Inference scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community. Both do llm inference.\n\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- Together AI Inference: grade B, 67.8/100, rank #304 of 1518. Markdown https://www.anchorterminal.com/tools/together-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/together-inference.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### 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 85\n- Maintenance \u0026 community, 83 against 65\n\nAlso in its favour:\n- No incidents deducted, where Together AI Inference loses 3 points for them\n\nWatch for: Paid tier only, with no free tier to try it on\n\n### Together AI Inference (B)\n\nGood for: Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.\n\nAhead on:\n- Reliability, 75 against 40\n- Schema \u0026 documentation, 93 against 85\n- Security \u0026 auth, 70 against 55\n\nWatch for: A $15 credit purchase is required before platform access; no free trial\n\n\n## Why the edge\n\n### Reliability: Together AI Inference +35\n\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- Together AI Inference (75): Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75.\n\n### Maintenance \u0026 community: Gemini 4 Carbon +18\n\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- Together AI Inference (65): Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0).\n\n### Security \u0026 auth: Together AI Inference +15\n\n- Gemini 4 Carbon (55): 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. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Carbon is on the paid tier only, and Google's terms say paid-tier content isn't used to improve products; AI Studio use under a Google AI Ultra subscription falls under terms we didn't read, so 15 of 20 (a judgement call; the platform's 10 is for its free tier). Abuse retention with no number, and new paid projects store requests by default since 26 October (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 15 + 5 + 15 + 5 = 55.\n- Together AI Inference (70): Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20).\n\n### Schema \u0026 documentation: Together AI Inference +8\n\n- Gemini 4 Carbon (85): 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. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.\n- Together AI Inference (93): Public OpenAPI 3.1 (25), llms.txt and Markdown docs (10), endpoint and model-capability guidance (16 of 20), typed inputs and constraints (13 of 15), examples and documented errors (14 of 15), and versioned endpoints with a dated changelog (15).\n\n### Agent ergonomics: Gemini 4 Carbon +8\n\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- Together AI Inference (85): Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15).\n\n## Score by category\n\n| Category | Weight | Gemini 4 Carbon | Together AI Inference | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 75 | Together AI Inference +35 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 93 | Together AI Inference +8 |\n| Agent ergonomics | 13% (16.2 this run) | 93 | 85 | Gemini 4 Carbon +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 70 | Together AI Inference +15 |\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) | 83 | 65 | Gemini 4 Carbon +18 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 74 | Together AI Inference +2 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **62.6 · B** | **67.8 · B** | |\n\n## Facts side by side\n\n| Fact | Gemini 4 Carbon | Together AI Inference |\n| --- | --- | --- |\n| Kind | Model API | HTTP API |\n| Vendor | Google | Together Computer, Inc. |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.together.ai/v1` |\n| Transports |  | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Paid |\n| x402 | no | no |\n| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-10 | 2026-10-23 |\n| Terms last updated | 2026-04-28 | no date given |\n| Privacy policy last updated | 2026-10-01 | no date given |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | none | 10 stars |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### Gemini 4 Carbon\n\nNo score change since it was listed.\n\n### Together AI Inference\n\n- no change on 1 November 2026: new evidence, correction\n- no change on 27 October 2026: checklist\n\n## Verdicts\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**Together AI Inference.** A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted.\n\n## Before you call either\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### Together AI Inference\n\n1. Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.\n2. For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.\n3. Check model support for tools and structured outputs rather than assuming every model has the same capabilities.\n4. Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.\n5. Check the deprecation schedule before choosing a model. Qwen3.8-2.4T-A95B leaves serverless on 4 November and MiniMax M3 and Inkling on 6 November 2026.\n6. Pin the SDK major version. Python SDK 3.0 and TypeScript SDK 1.0 (22 October 2026) drop `/v1` from the base URL and the `beta` paths\n\n## Questions\n\n### Which is better for AI agents, Gemini 4 Carbon or Together AI Inference?\n\nTogether AI Inference scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.\n\n### Do Gemini 4 Carbon and Together AI Inference need an API key?\n\nBoth need an API key.\n\n### Can an agent call Gemini 4 Carbon and Together AI Inference without installing anything?\n\nYes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Together AI Inference at https://api.together.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-4-carbon\", \"b\": \"together-inference\"}`. From a terminal: `anchor compare gemini-4-carbon together-inference`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json and https://www.anchorterminal.com/api/v1/tools/together-inference.json\n\n## Other comparisons with Gemini 4 Carbon or Together AI Inference\n\n- [Amazon Bedrock vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.md)\n- [Amazon Bedrock vs Together AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Claude API vs Together AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- [Antseed vs Together AI Inference](https://www.anchorterminal.com/compare/antseed-vs-together-inference.md)\n- [Azure 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API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api.md)\n- [Gemini 4 Carbon vs Mistral AI API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api.md)\n- [Gemini 4 Carbon vs Muse Ember](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember.md)\n- [Gemini 4 Carbon vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.md)\n- [Gemini 4 Carbon vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl.md)\n- [Gemini 4 Carbon vs Novita AI](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.md)\n- [Gemini 4 Carbon vs OpenAI API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openai-api.md)\n- [Gemini 4 Carbon vs OpenRouter](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openrouter.md)\n- [Gemini 4 Carbon vs Prism Inference](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-prism-inference.md)\n- [Gemini 4 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Together AI Inference](https://www.anchorterminal.com/compare/jais-3-vs-together-inference.md)\n- [Meta Model API vs Together AI Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.md)\n- [MiniMax API vs Together AI Inference](https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.md)\n- [Mistral AI API vs Together AI Inference](https://www.anchorterminal.com/compare/mistral-api-vs-together-inference.md)\n- [Muse Ember vs Together AI Inference](https://www.anchorterminal.com/compare/muse-ember-vs-together-inference.md)\n- [Muse Spark Open vs Together AI Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.md)\n- [Novita AI vs Together AI Inference](https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.md)\n- [OpenAI API vs Together AI Inference](https://www.anchorterminal.com/compare/openai-api-vs-together-inference.md)\n- [OpenRouter vs Together AI Inference](https://www.anchorterminal.com/compare/openrouter-vs-together-inference.md)\n- [Prism Inference vs Together AI Inference](https://www.anchorterminal.com/compare/prism-inference-vs-together-inference.md)\n- [Router.com (Ramp Router) vs Together AI Inference](https://www.anchorterminal.com/compare/ramp-router-vs-together-inference.md)\n- [Beam 1.0 vs Together AI Inference](https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.md)\n- [RouterPlus vs Together AI Inference](https://www.anchorterminal.com/compare/routerplus-vs-together-inference.md)\n- [SambaCloud vs Together AI Inference](https://www.anchorterminal.com/compare/sambanova-vs-together-inference.md)\n- [SiliconFlow vs Together AI Inference](https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.md)\n- [Simplismart vs Together AI Inference](https://www.anchorterminal.com/compare/simplismart-vs-together-inference.md)\n- [StepFun API vs Together AI Inference](https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.md)\n- [SWE-2 Flash vs Together AI Inference](https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference.md)\n- [Tencent Cloud TokenHub vs Together AI Inference](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference.md)\n- [Together AI Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway.md)\n- [Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md)\n- [Together AI Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/together-inference-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs Together AI Inference](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference.md)\n",
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