{ "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": "2026-11-11T00:56:52.090261664Z", "lastOk": true, "lastStatus": 404, "lastMs": 39, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 39, "p95ms24h": 130, "samples24h": 75, "samples30d": 75, "days": [ { "date": "2026-11-10", "probes": 65, "ok": 65 }, { "date": "2026-11-11", "probes": 10, "ok": 10 } ], "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": "2026-11-11T00:56:52.090261664Z" }, "streak": { "days": 1, "from": "2026-11-10", "sinceWatching": true, "best": 1 } }, "answer": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Novita AI's 53.9 (D), and leads in 5 of 7 scored categories. Novita AI leads on security \u0026 auth and payments \u0026 pricing.", "b": { "slug": "novita-ai", "name": "Novita AI", "vendor": "Novita AI", "vendorUrl": "https://novita.ai", "kind": "model", "category": "inference", "summary": "Novita AI is a hosted inference API for open-weight language models, with embeddings, reranking, image, video and speech models on the same key. It answers OpenAI-style calls at api.novita.ai with a Bearer key.", "url": "https://www.anchorterminal.com/tools/novita-ai", "markdownUrl": "https://www.anchorterminal.com/tools/novita-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/novita-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/novita-ai.json", "dns": "novita-ai.grade.anchorterminal.com", "repo": "https://github.com/novitalabs/novita-skills", "license": "Proprietary service under the Novita AI Terms of Service. The agent skill and the MCP server are MIT", "transports": [ "http" ], "remoteUrl": "https://api.novita.ai/openai", "packages": [ { "registry": "npm", "name": "novita-sdk" }, { "registry": "pypi", "name": "novita-client" }, { "registry": "npm", "name": "@novitalabs/novita-mcp-server" } ], "auth": "api-key", "authNotes": "Self-serve Bearer key from Key Management in the console after a browser sign-up. Keys start with `sk_`, are shown once, number up to 10 an account and take an expiry of 24 hours, 30 days, 90 days or none. A per-key model access policy and source IP allowlist can be set by API. `auth.md` also describes OAuth with PKCE after the user signs in and approves (https://docs.novita.ai/guides/llm-api-keys, https://novita.ai/auth.md).", "pricing": "usage", "pricingNotes": "Pay per token from prepaid credit. `deepseek/deepseek-v4.1-flash` costs $0.30 in and $1.20 out per 1M tokens, batch is 50 per cent off as an introductory price, and two models are listed as free. A voucher for new users is described without an amount, and whether a card is needed was not found (https://novita.ai/pricing, checked 2026-10-09).", "priceSummary": "from $0.05 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs index, the docs site map, the pricing page or the skill repository (checked 2026-10-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 6, "npmWeekly": 1363, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://docs.novita.ai/guides/introduction", "rateLimitsUrl": "https://docs.novita.ai/guides/llm-rate-limits", "llmsTxt": "https://docs.novita.ai/llms.txt", "openapi": "https://novita.ai/.well-known/openapi.json", "capabilities": [ "inference.llm", "inference.open-weights", "embed.text", "rerank", "image.generate", "video.generate", "speech.tts", "compute.batch" ], "tags": [ "hosted", "model", "open-weights", "usage-based", "llms-txt", "openai-compatible", "batch", "prompt-caching", "changelog" ], "lastRelease": "2026-10-22", "graded": true, "anchor": { "graded": true, "score": 53.9, "grade": "D", "agentReady": false, "rank": 940, "ranked": true, "rankOf": 1518, "categoryRank": 32, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 66, "payments": 35, "reliability": 28, "schema": 62, "security": 65, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "Per-token prices for about 140 language models are public, and each key can carry an expiry, a model allowlist and a source IP allowlist. No status page, SLA or security.txt was found, the per-model rate limit figures are drawn by script, and both vendor SDK repositories are archived while the docs still point to them.", "bestFor": "Agents that want many open-weight models at per-token prices behind one OpenAI-style key, with keys that can be limited by model, IP and expiry.", "strengths": [ "API keys take an expiry of 24 hours, 30 days or 90 days, a per-key model access policy and a per-key source IP allowlist, the last two settable by API", "The pricing page lists input, output and cache-read prices per 1M tokens with context size for each language model, readable without a login", "The terms commit to zero data retention and say content is not used to train Novita's models by default, with stated exceptions", "A billing page states which HTTP statuses are charged. 400, 401, 403, 429, 500, 503 and 504 are not, and 200 and 499 are", "A dated changelog with nine entries between 1 September and 22 October 2026, each retirement naming a UTC time and a replacement" ], "weaknesses": [ "No status page or SLA was found on the home page, the docs index or the docs site map. The home page states 99.5% uptime with no supporting document", "The rate limit page explains five tiers by monthly top-up, and the RPM and TPM figures per model are drawn by script and were not readable", "`xiaomimimo/mimo-v2.5` and `-pro` were retired at 00:00 UTC on 23 October 2026 on a notice dated 22 October", "The Python and JavaScript SDK repositories are archived, last changed in November 2024 and March 2025, and the SDK docs page still tells users to install them", "The terms name the contracting party only as Novita AI, with no corporate form or address, and no DPA or sub-processor list was found", "The terms bar automated or non-human access that extracts data from the site and its linked channels, docs included" ], "agentNotes": [ "Set the OpenAI client base URL to `https://api.novita.ai/openai` and send the key as `Authorization: Bearer`. Keys start with `sk_`", "Do not close a connection to stop generation. A request that reached the model is billed in full under status 499, so cap output with `max_tokens`", "On 429, check whether the code is `RATE_LIMIT_EXCEEDED` or `TOKEN_LIMIT_EXCEEDED` and back off exponentially. No `Retry-After` header is documented", "Read the changelog for retirement notices before pinning a model id. One retirement in October 2026 came with 11 days' notice", "Ask the account owner for a key with an expiry, a model access policy and an IP allowlist. Keys are created and deleted only in the console" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.9 } ], "editorialScores": { "ergonomics": 72, "maintenance": 66, "payments": 35, "reliability": 28, "schema": 62, "security": 65, "transparency": 42 }, "provenanceScore": 71, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install openai # or: npm install openai", "http": "curl \"https://api.novita.ai/openai/v1/chat/completions\" \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $NOVITA_API_KEY\" \\\n -d '{\"model\":\"deepseek/deepseek-v4.1-flash\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/novita-ai" }, "area": "models", "provenance": { "legalEntity": "Novita AI", "domain": "novita.ai", "domainRegistered": "2023-09-18", "endpointOnVendorDomain": true, "terms": "https://novita.ai/legal/terms-of-service", "privacy": "https://novita.ai/legal/privacy-policy", "statusPage": "", "changelog": "https://docs.novita.ai/changelog", "securityTxt": "none", "checked": "2026-10-09", "notes": [ "The Terms of Service, updated 5 August 2026, name the party only as Novita AI, with no corporate form or address. They cover the site and the services sold through it, the inference APIs included, under Delaware law with arbitration.", "The Privacy Policy, effective 13 May 2026, covers the website and services and says it does not apply to content processed on behalf of customers, which it leaves to customer agreements.", "The Acceptable Use Policy, effective 5 August 2026, is part of the terms.", "No status page was found on the home page, the pricing page, the docs index or the docs site map.", "https://novita.ai/.well-known/security.txt returns 404.", "RDAP for novita.ai gives a registration date of 2023-09-18.", "The API answers at api.novita.ai and the docs at docs.novita.ai. `auth.md` names a token endpoint at api-server.novita.ai.", "No SLA, DPA or sub-processor list was found. The trust centre at trust.novita.ai is drawn by script and was not read." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/novita-ai.json", "live": { "slug": "novita-ai", "probe": { "target": "https://api.novita.ai/openai", "method": "get", "lastAt": "2026-11-11T00:57:02.134217448Z", "lastOk": true, "lastStatus": 404, "lastMs": 178, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 193, "p95ms24h": 299, "samples24h": 245, "samples30d": 7669, "days": [ { "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": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "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": 244, "ok": 244 }, { "date": "2026-11-11", "probes": 10, "ok": 10 } ], "since": "2026-10-09T00:00:00Z" }, "versions": [ { "registry": "npm", "name": "@novitalabs/novita-mcp-server", "version": "1.0.2", "seenAt": "2026-11-10T04:03:04.389327486Z" }, { "registry": "npm", "name": "novita-sdk", "version": "3.1.3", "seenAt": "2026-11-10T04:03:03.777014054Z" }, { "registry": "pypi", "name": "novita-client", "version": "0.7.1", "released": "2024-11-08", "seenAt": "2026-11-10T04:03:04.174393413Z" } ], "githubStars": 6, "npmWeekly": 1134, "pypiWeekly": 596, "securityTxt": { "url": "https://novita.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:08:57.539714857Z" }, "llmsTxt": { "url": "https://docs.novita.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:43:57.403398324Z" }, "domain": { "domain": "novita.ai", "registered": "2023-09-18", "source": "https://rdap.identitydigital.services/rdap/domain/novita.ai", "checkedAt": "2026-11-08T15:09:04.153769958Z" }, "pages": [ { "url": "https://docs.novita.ai/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:17:49.78902817Z", "changedAt": "2026-11-05T12:31:01.945166318Z", "fingerprint": "e2d99c9e9a69" }, { "url": "https://docs.novita.ai/changelog/01-09-26", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:17:52.046799669Z", "changedAt": "2026-11-05T12:31:04.147817719Z", "fingerprint": "ad3fcb405ac0" }, { "url": "https://docs.novita.ai/changelog/15-10-26", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:17:54.167752354Z", "changedAt": "2026-11-05T12:31:06.019590386Z", "fingerprint": "6762cf636177" }, { "url": "https://docs.novita.ai/changelog/19-10-26", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:17:56.243628439Z", "changedAt": "2026-11-05T12:31:08.033030134Z", "fingerprint": "e9f1f056be2d" }, { "url": "https://docs.novita.ai/changelog/20-09-26", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:17:58.160803267Z", "changedAt": "2026-11-05T12:31:10.054667236Z", "fingerprint": "80cc4fc7a38f" }, { "url": "https://docs.novita.ai/changelog/22-10-26", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:18:00.139304715Z", "changedAt": "2026-11-05T12:31:12.159835023Z", "fingerprint": "89b36db84558" }, { "url": "https://docs.novita.ai/changelog/28-09-26", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:18:02.160776196Z", "changedAt": "2026-11-05T12:31:14.098885581Z", "fingerprint": "0ab7ce953778" }, { "url": "https://novita.ai/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-10T16:26:25.109415798Z", "changedAt": "2026-11-10T16:26:25.109415798Z", "fingerprint": "26c2eff6f1d7" }, { "url": "https://novita.ai/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-10T16:26:20.606543698Z", "changedAt": "2026-10-28T04:39:20.568611227Z", "fingerprint": "d50a56d160b7" }, { "url": "https://novita.ai/legal/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:26:23.05100628Z", "changedAt": "2026-10-28T04:39:23.076821771Z", "fingerprint": "cacda80faa75" } ], "models": { "deepseek/deepseek-v4.1-flash": { "openrouterId": "deepseek/deepseek-v4.1-flash", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 943718, "checkedAt": "2026-11-10T23:49:27.674722665Z" }, "openai/gpt-oss-120b": { "openrouterId": "openai/gpt-oss-120b", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 131072, "maxOutput": 65536, "checkedAt": "2026-11-10T23:49:27.674722665Z" }, "qwen/qwen3.8-flash": { "openrouterId": "qwen/qwen3.8-flash", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text", "video" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 131072, "checkedAt": "2026-11-10T23:49:27.674722665Z" } }, "github": { "repo": "novitalabs/novita-skills", "checkedAt": "2026-11-09T10:46:41.126832119Z", "stars": 6, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-05T08:40:25Z", "openIssues": 0, "openPRs": 0, "issuesOpened90d": 0, "issuesClosed90d": 0, "prsMerged90d": 2 }, "updatedAt": "2026-11-11T00:57:02.134217448Z" }, "streak": { "days": 13, "from": "2026-10-29", "last": { "kind": "shutdown", "date": "2026-10-29", "what": "`baidu/ernie-4.5-21B-a3b` goes offline. Move to `deepseek/deepseek-v4.1-flash`", "source": "https://docs.novita.ai/changelog/15-10-26" }, "best": 14 } }, "edges": [ { "by": 23, "category": "schema", "leads": "gemini-4-carbon", "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": "Model reading. The OpenAPI 3.1.0 document at `/.well-known/openapi.json` is a 964-byte discovery file with four paths and no schemas, and the API reference is written by hand (6 of 25). `llms.txt` on both hosts, a Markdown copy of every docs page and an `llms-full.txt` (10). Guides for function calling, structured output, prompt caching, batch and reasoning say what each is for, and the chat reference describes 136 request and response fields (14 of 20). Fields are typed with required flags and defaults. Enums and ranges are stated in prose only (10 of 15). Curl and Python examples on each guide, error tables by product, a common errors guide and a table of which statuses are billed. The FAQ says `json_schema` and `top_logprobs` are unsupported while the reference and a guide document both (10 of 15). A dated changelog with 84 entries since February 2024. The API has no version scheme beyond `/v1` (12 of 15). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs." }, "scores": { "a": 85, "b": 62 } }, { "by": 21, "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": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). `tools` with a `strict` flag and a worked example. The list of models that support it is drawn by script, and `tool_choice` is absent from the chat reference (13 of 20). `response_format` takes `json_object` and `json_schema` with `strict` in the reference, while the FAQ says only `json_object` works (9 of 15). Prompt caching is automatic on supported models, cache-read prices are on the pricing page and `cached_tokens` is returned in usage (12 of 15). Context of 1M tokens on DeepSeek V4, GLM 5.3 and Kimi K3 per the pricing page. Output caps were not read (12 of 15). OpenAI-style files and batches with a 24-hour window, one model per file and an introductory 50 per cent discount (10). The OpenAI client works with a changed base URL. Both vendor SDK repositories are archived (5 of 10). Named error codes, a 429 that separates request and token limits, and a `trace_id` for support (11 of 15). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs." }, "scores": { "a": 93, "b": 72 } }, { "by": 17, "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": "Model reading. Changelog entries per the 27 October reading of each entry page, not re-read on 4 November because Novita's terms bar automated access to the site and its linked channels. The newest entry is dated 22 October 2026 (30). Retirement notices carry a UTC time and a replacement, with notice of 1 day (22 October for `xiaomimimo/mimo-v2.5` at 00:00 UTC on 23 October) to 29 days (1 September for multimodal models on 30 September). No written notice period was found (6 of 12). Nine dated entries in the 90 days from 6 August (1, 8, 18, 20, 23 and 28 September, 15, 19 and 22 October), each read on its own page (8 of 8). A dated changelog, a Discord server and a support address per the 9 October check (12 of 15). `novitalabs/python-sdk` and `novitalabs/javascript-sdk` are archived, unchanged since 8 November 2024 and 4 March 2025, and issue replies were not examined (2 of 10). The docs rely on the OpenAI client, the SDK page still named the two archived packages on 9 October, and the skill repository is unchanged since 24 September 2026 (5 of 15). The JavaScript SDK repository has a publish workflow only and the Python one has none (3 of 10). 30 + 6 + 8 + 12 + 2 + 5 + 3 = 66." }, "scores": { "a": 83, "b": 66 } }, { "by": 15, "category": "payments", "leads": "novita-ai", "name": "Payments \u0026 pricing", "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. 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.", "b": "No machine payment protocol was found in the docs index, the site map, the pricing page or the skill repository (0). Per-token prices for each model on the pricing page without a login, such as `deepseek/deepseek-v4.1-flash` at $0.30 in and $1.20 out per 1M tokens (20). Two language models are listed as free and the FAQ describes a voucher for new users. Whether a card is needed to use either was not stated in the pages read (15 of 20). A person signs up in a browser, keys are created only in the console, and the OAuth route needs the user to sign in and approve (0). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs." }, "scores": { "a": 20, "b": 35 } }, { "by": 15, "category": "transparency", "leads": "gemini-4-carbon", "name": "Transparency \u0026 trust", "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. Closed service with clear terms, SDKs Apache-2.0 (15). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.", "b": "Closed service. The terms set Delaware law and arbitration but name the party only as Novita AI, with no corporate form or address. The skill and the MCP server are MIT (10 of 30). The terms state zero data retention and no training by default, and the privacy policy lists retention periods (account data for the life of the account plus 7 years, technical data 2 years). The privacy policy says it does not cover content processed for customers and points to customer agreements. No DPA was found (16 of 30). Retirement notices in the changelog carry a UTC time and a replacement. The terms reserve the right to discontinue any service without notice (12 of 20). The privacy policy names categories of recipients only and transfers that include the United States. No sub-processor list was found (4 of 20). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs." }, "scores": { "a": 72, "b": 57 } }, { "by": 12, "category": "reliability", "leads": "gemini-4-carbon", "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": "Hosted reading. No status page was found. None is linked from the home page, the pricing page, the docs introduction, either `llms.txt` or the docs site map (0), so there is no incident record to read (0). The rate limit page documents five account tiers set by monthly top-ups, from under $50 to $10,000 and over, and limits counted in RPM and TPM per model. The figures per model are drawn by script and were not readable, so this line takes part marks (8 of 15). 429 with `RATE_LIMIT_EXCEEDED` or `TOKEN_LIMIT_EXCEEDED`, advice to throttle and use exponential backoff, and a billing page that says 429, 500, 503 and 504 are not charged. No `Retry-After` header was found (10 of 15). No SLA was found. The home page states 99.5% uptime, and the terms say availability is not guaranteed (0). Generally available (10). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs." }, "scores": { "a": 40, "b": 28 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Google", "b": "Novita AI", "name": "Vendor" }, { "a": "https://generativelanguage.googleapis.com/v1beta", "b": "https://api.novita.ai/openai", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Closed model, used through the Gemini API and Google's apps under Google's terms", "b": "Proprietary service under the Novita AI Terms of Service. The agent skill and the MCP server are MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-10", "b": "2026-10-22", "name": "Last release" }, { "a": "2026-04-28", "b": "2026-08-05", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "2026-05-13", "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": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "6 stars, 1.4k npm/wk", "name": "Popularity" } ], "faq": [ { "answer": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Novita AI's 53.9 (D), and leads in 5 of 7 scored categories. Novita AI leads on security \u0026 auth and payments \u0026 pricing.", "question": "Which is better for AI agents, Gemini 4 Carbon or Novita AI?" }, { "answer": "Both need an API key.", "question": "Do Gemini 4 Carbon and Novita AI need an API key?" }, { "answer": "Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Novita AI at https://api.novita.ai/openai.", "question": "Can an agent call Gemini 4 Carbon and Novita AI without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 40 against 28", "Schema \u0026 documentation, 85 against 62", "Agent ergonomics, 93 against 72", "Maintenance \u0026 community, 83 against 66", "Transparency \u0026 trust, 72 against 57" ], "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" }, { "aheadOn": [ "Security \u0026 auth, 65 against 55", "Payments \u0026 pricing, 35 against 20" ], "also": null, "goodFor": "Agents that want many open-weight models at per-token prices behind one OpenAI-style key, with keys that can be limited by model, IP and expiry.", "slug": "novita-ai", "watchFor": "No status page or SLA was found on the home page, the docs index or the docs site map. The home page states 99.5% uptime with no supporting document" } ], "history": { "gemini-4-carbon": null, "novita-ai": [ { "causes": [ "evidence" ], "date": "2026-11-04", "delta": 0.4, "from": 53.5, "fromGrade": "D", "to": 53.9, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0, "from": 53.5, "fromGrade": "D", "to": 53.5, "toGrade": "D" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "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/amazon-bedrock-vs-novita-ai.json", "title": "Amazon Bedrock vs Novita AI", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai" }, { "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-novita-ai.json", "title": "Claude API vs Novita AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai" }, { "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-novita-ai.json", "title": "Antseed vs Novita AI", "url": "https://www.anchorterminal.com/compare/antseed-vs-novita-ai" }, { "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/azure-openai-vs-novita-ai.json", "title": 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"DeepSeek API vs Novita AI", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai" }, { "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/eden-ai-vs-novita-ai.json", "title": "Eden AI vs Novita AI", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai" }, { "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/elorian-glimpse-vs-novita-ai.json", "title": "Glimpse vs Novita AI", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-novita-ai" }, { "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/fireworks-inference-vs-novita-ai.json", "title": "Fireworks AI Inference vs Novita AI", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-novita-ai" }, { "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-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" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-novita-ai.json", "title": "Gemini Developer API vs Novita AI", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-novita-ai.json", "title": "GroqCloud vs Novita AI", "url": "https://www.anchorterminal.com/compare/groq-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai.json", "title": "Hugging Face Inference Providers vs Novita AI", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-novita-ai.json", "title": "Inkling 2 Small vs Novita AI", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-novita-ai.json", "title": "Jais 3 vs Novita AI", "url": "https://www.anchorterminal.com/compare/jais-3-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.json", "title": "Meta Model API vs Novita AI", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-novita-ai.json", "title": "MiniMax API vs Novita AI", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai.json", "title": "Mistral AI API vs Novita AI", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai.json", "title": "Muse Ember vs Novita AI", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.json", "title": "Muse Spark Open vs Novita AI", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api.json", "title": "Novita AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-openrouter.json", "title": "Novita AI vs OpenRouter", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-prism-inference.json", "title": "Novita AI vs Prism Inference", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-ramp-router.json", "title": "Novita AI vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.json", "title": "Novita AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-routerplus.json", "title": "Novita AI vs RouterPlus", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.json", "title": "Novita AI vs SambaCloud", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.json", "title": "Novita AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-simplismart.json", "title": "Novita AI vs Simplismart", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-stepfun-api.json", "title": "Novita AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-swe-2-flash.json", "title": "Novita AI vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-tencent-tokenhub.json", "title": "Novita AI vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.json", "title": "Novita AI vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-vercel-ai-gateway.json", "title": "Novita AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai.json", "title": "Novita AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api.json", "title": "Novita AI vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-novita-ai.json", "title": "Nemotron 3.5 Super VL vs Novita AI", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-novita-ai" } ], "panel": null, "scores": [ { "by": 12, "edge": "gemini-4-carbon", "gemini-4-carbon": 40, "key": "reliability", "name": "Reliability", "novita-ai": 28, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 23, "edge": "gemini-4-carbon", "gemini-4-carbon": 85, "key": "schema", "name": "Schema \u0026 documentation", "novita-ai": 62, "weight": 13 }, { "by": 21, "edge": "gemini-4-carbon", "gemini-4-carbon": 93, "key": "ergonomics", "name": "Agent ergonomics", "novita-ai": 72, "weight": 13 }, { "by": 10, "edge": "novita-ai", "gemini-4-carbon": 55, "key": "security", "name": "Security \u0026 auth", "novita-ai": 65, "weight": 14 }, { "by": 15, "edge": "novita-ai", "gemini-4-carbon": 20, "key": "payments", "name": "Payments \u0026 pricing", "novita-ai": 35, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 17, "edge": "gemini-4-carbon", "gemini-4-carbon": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "novita-ai": 66, "weight": 7 }, { "by": 15, "edge": "gemini-4-carbon", "gemini-4-carbon": 72, "key": "transparency", "name": "Transparency \u0026 trust", "novita-ai": 57, "weight": 7 } ], "summary": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Novita AI's 53.9 (D), and leads in 5 of 7 scored categories. Novita AI leads on security \u0026 auth and payments \u0026 pricing. 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.", "novita-ai": "Per-token prices for about 140 language models are public, and each key can carry an expiry, a model allowlist and a source IP allowlist. No status page, SLA or security.txt was found, the per-model rate limit figures are drawn by script, and both vendor SDK repositories are archived while the docs still point to them." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai", "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.min.md" }, "markdown": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Novita AI's 53.9 (D), and leads in 5 of 7 scored categories. Novita AI leads on security \u0026 auth and payments \u0026 pricing. 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- Novita AI: grade D, 53.9/100, rank #940 of 1518. Markdown https://www.anchorterminal.com/tools/novita-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/novita-ai.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- Reliability, 40 against 28\n- Schema \u0026 documentation, 85 against 62\n- Agent ergonomics, 93 against 72\n- Maintenance \u0026 community, 83 against 66\n- Transparency \u0026 trust, 72 against 57\n\nWatch for: Paid tier only, with no free tier to try it on\n\n### Novita AI (D)\n\nGood for: Agents that want many open-weight models at per-token prices behind one OpenAI-style key, with keys that can be limited by model, IP and expiry.\n\nAhead on:\n- Security \u0026 auth, 65 against 55\n- Payments \u0026 pricing, 35 against 20\n\nWatch for: No status page or SLA was found on the home page, the docs index or the docs site map. The home page states 99.5% uptime with no supporting document\n\n\n## Why the edge\n\n### Schema \u0026 documentation: Gemini 4 Carbon +23\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- Novita AI (62): Model reading. The OpenAPI 3.1.0 document at `/.well-known/openapi.json` is a 964-byte discovery file with four paths and no schemas, and the API reference is written by hand (6 of 25). `llms.txt` on both hosts, a Markdown copy of every docs page and an `llms-full.txt` (10). Guides for function calling, structured output, prompt caching, batch and reasoning say what each is for, and the chat reference describes 136 request and response fields (14 of 20). Fields are typed with required flags and defaults. Enums and ranges are stated in prose only (10 of 15). Curl and Python examples on each guide, error tables by product, a common errors guide and a table of which statuses are billed. The FAQ says `json_schema` and `top_logprobs` are unsupported while the reference and a guide document both (10 of 15). A dated changelog with 84 entries since February 2024. The API has no version scheme beyond `/v1` (12 of 15). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs.\n\n### Agent ergonomics: Gemini 4 Carbon +21\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- Novita AI (72): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). `tools` with a `strict` flag and a worked example. The list of models that support it is drawn by script, and `tool_choice` is absent from the chat reference (13 of 20). `response_format` takes `json_object` and `json_schema` with `strict` in the reference, while the FAQ says only `json_object` works (9 of 15). Prompt caching is automatic on supported models, cache-read prices are on the pricing page and `cached_tokens` is returned in usage (12 of 15). Context of 1M tokens on DeepSeek V4, GLM 5.3 and Kimi K3 per the pricing page. Output caps were not read (12 of 15). OpenAI-style files and batches with a 24-hour window, one model per file and an introductory 50 per cent discount (10). The OpenAI client works with a changed base URL. Both vendor SDK repositories are archived (5 of 10). Named error codes, a 429 that separates request and token limits, and a `trace_id` for support (11 of 15). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs.\n\n### Maintenance \u0026 community: Gemini 4 Carbon +17\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- Novita AI (66): Model reading. Changelog entries per the 27 October reading of each entry page, not re-read on 4 November because Novita's terms bar automated access to the site and its linked channels. The newest entry is dated 22 October 2026 (30). Retirement notices carry a UTC time and a replacement, with notice of 1 day (22 October for `xiaomimimo/mimo-v2.5` at 00:00 UTC on 23 October) to 29 days (1 September for multimodal models on 30 September). No written notice period was found (6 of 12). Nine dated entries in the 90 days from 6 August (1, 8, 18, 20, 23 and 28 September, 15, 19 and 22 October), each read on its own page (8 of 8). A dated changelog, a Discord server and a support address per the 9 October check (12 of 15). `novitalabs/python-sdk` and `novitalabs/javascript-sdk` are archived, unchanged since 8 November 2024 and 4 March 2025, and issue replies were not examined (2 of 10). The docs rely on the OpenAI client, the SDK page still named the two archived packages on 9 October, and the skill repository is unchanged since 24 September 2026 (5 of 15). The JavaScript SDK repository has a publish workflow only and the Python one has none (3 of 10). 30 + 6 + 8 + 12 + 2 + 5 + 3 = 66.\n\n### Payments \u0026 pricing: Novita AI +15\n\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- Novita AI (35): No machine payment protocol was found in the docs index, the site map, the pricing page or the skill repository (0). Per-token prices for each model on the pricing page without a login, such as `deepseek/deepseek-v4.1-flash` at $0.30 in and $1.20 out per 1M tokens (20). Two language models are listed as free and the FAQ describes a voucher for new users. Whether a card is needed to use either was not stated in the pages read (15 of 20). A person signs up in a browser, keys are created only in the console, and the OAuth route needs the user to sign in and approve (0). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs.\n\n### Transparency \u0026 trust: Gemini 4 Carbon +15\n\n- Gemini 4 Carbon (72): 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. Closed service with clear terms, SDKs Apache-2.0 (15). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.\n- Novita AI (57): Closed service. The terms set Delaware law and arbitration but name the party only as Novita AI, with no corporate form or address. The skill and the MCP server are MIT (10 of 30). The terms state zero data retention and no training by default, and the privacy policy lists retention periods (account data for the life of the account plus 7 years, technical data 2 years). The privacy policy says it does not cover content processed for customers and points to customer agreements. No DPA was found (16 of 30). Retirement notices in the changelog carry a UTC time and a replacement. The terms reserve the right to discontinue any service without notice (12 of 20). The privacy policy names categories of recipients only and transfers that include the United States. No sub-processor list was found (4 of 20). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs.\n\n### Reliability: Gemini 4 Carbon +12\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- Novita AI (28): Hosted reading. No status page was found. None is linked from the home page, the pricing page, the docs introduction, either `llms.txt` or the docs site map (0), so there is no incident record to read (0). The rate limit page documents five account tiers set by monthly top-ups, from under $50 to $10,000 and over, and limits counted in RPM and TPM per model. The figures per model are drawn by script and were not readable, so this line takes part marks (8 of 15). 429 with `RATE_LIMIT_EXCEEDED` or `TOKEN_LIMIT_EXCEEDED`, advice to throttle and use exponential backoff, and a billing page that says 429, 500, 503 and 504 are not charged. No `Retry-After` header was found (10 of 15). No SLA was found. The home page states 99.5% uptime, and the terms say availability is not guaranteed (0). Generally available (10). Per the 9 October check, not re-read on 4 November, as the terms bar automated access to the site and docs.\n\n## Score by category\n\n| Category | Weight | Gemini 4 Carbon | Novita AI | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 28 | Gemini 4 Carbon +12 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 62 | Gemini 4 Carbon +23 |\n| Agent ergonomics | 13% (16.2 this run) | 93 | 72 | Gemini 4 Carbon +21 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 65 | Novita AI +10 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 35 | Novita AI +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 66 | Gemini 4 Carbon +17 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 57 | Gemini 4 Carbon +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **62.6 · B** | **53.9 · D** | |\n\n## Facts side by side\n\n| Fact | Gemini 4 Carbon | Novita AI |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Google | Novita AI |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.novita.ai/openai` |\n| Transports | | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | Proprietary service under the Novita AI Terms of Service. The agent skill and the MCP server are MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-10 | 2026-10-22 |\n| Terms last updated | 2026-04-28 | 2026-08-05 |\n| Privacy policy last updated | 2026-10-01 | 2026-05-13 |\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 | not found in the text |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | none | 6 stars, 1.4k npm/wk |\n\n## How the scores have moved\n\n### Gemini 4 Carbon\n\nNo score change since it was listed.\n\n### Novita AI\n\n- +0.4 on 4 November 2026: new evidence\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**Novita AI.** Per-token prices for about 140 language models are public, and each key can carry an expiry, a model allowlist and a source IP allowlist. No status page, SLA or security.txt was found, the per-model rate limit figures are drawn by script, and both vendor SDK repositories are archived while the docs still point to them.\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### Novita AI\n\n1. Set the OpenAI client base URL to `https://api.novita.ai/openai` and send the key as `Authorization: Bearer`. Keys start with `sk_`\n2. Do not close a connection to stop generation. A request that reached the model is billed in full under status 499, so cap output with `max_tokens`\n3. On 429, check whether the code is `RATE_LIMIT_EXCEEDED` or `TOKEN_LIMIT_EXCEEDED` and back off exponentially. No `Retry-After` header is documented\n4. Read the changelog for retirement notices before pinning a model id. One retirement in October 2026 came with 11 days' notice\n5. Ask the account owner for a key with an expiry, a model access policy and an IP allowlist. Keys are created and deleted only in the console\n\n## Questions\n\n### Which is better for AI agents, Gemini 4 Carbon or Novita AI?\n\nGemini 4 Carbon scores 62.6 (B) on agent readiness against Novita AI's 53.9 (D), and leads in 5 of 7 scored categories. Novita AI leads on security \u0026 auth and payments \u0026 pricing.\n\n### Do Gemini 4 Carbon and Novita AI need an API key?\n\nBoth need an API key.\n\n### Can an agent call Gemini 4 Carbon and Novita AI without installing anything?\n\nYes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Novita AI at https://api.novita.ai/openai.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-4-carbon\", \"b\": \"novita-ai\"}`. From a terminal: `anchor compare gemini-4-carbon novita-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json and https://www.anchorterminal.com/api/v1/tools/novita-ai.json\n\n## Other comparisons with Gemini 4 Carbon or Novita AI\n\n- [Amazon Bedrock vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.md)\n- [Amazon Bedrock vs Novita AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Claude API vs Novita AI](https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- [Antseed vs Novita AI](https://www.anchorterminal.com/compare/antseed-vs-novita-ai.md)\n- [Azure OpenAI in Foundry Models vs Gemini 4 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AI](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-novita-ai.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": "2026-11-11", "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": "Gemini 4 Carbon vs Novita AI", "url": "" } ], "description": "Gemini 4 Carbon scores 62.6 (B) to Novita AI's 53.9 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Gemini 4 Carbon B 62.6", "Novita AI D 53.9", "scores" ], "h1": "Gemini 4 Carbon vs Novita AI", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/gemini-4-carbon-vs-novita-ai", "published": "2026-10-01", "section": "tools", "title": "Gemini 4 Carbon vs Novita AI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai" }, "tokens": { "markdown": 6850, "slim": 980 }, "version": 1 }