{
  "data": {
    "a": {
      "slug": "gemini-4-hydrogen",
      "name": "Gemini 4 Hydrogen",
      "vendor": "Google",
      "vendorUrl": "https://ai.google.dev",
      "kind": "model",
      "category": "inference",
      "summary": "Gemini 4 Hydrogen is Google's fast, lower-cost Gemini 4 model for everyday coding and agent work, on every 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-hydrogen",
      "markdownUrl": "https://www.anchorterminal.com/tools/gemini-4-hydrogen.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gemini-4-hydrogen.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json",
      "dns": "gemini-4-hydrogen.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. Google's announcement puts Hydrogen on all tiers of AI Studio and the Gemini API, so a free-tier key with no billing works, per that post and the Gemini API listing's reading of the free tier. Paid Google AI Pro and Ultra subscribers can use it in Antigravity. On Google Cloud it's `gemini-4-hydrogen` on the Agent Platform, with Cloud credentials.",
      "pricing": "usage",
      "pricingNotes": "Google's announcement gives $1.50 per million input tokens and $7.50 output, flat across the whole 1M-token window, and names no introductory period, cached-input or batch price. Every processed token is billed, thinking included. Hydrogen's free-tier limits are on the Gemini API pricing page, now at aistudio.google.com, not yet read (checked 2026-11-13).",
      "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 2026-11-13).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-13"
      },
      "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/guides/gemini-4-hydrogen",
      "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",
        "free-tier",
        "closed-source",
        "llms-txt",
        "new"
      ],
      "lastRelease": "2026-11-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.9,
        "grade": "B",
        "agentReady": false,
        "rank": 546,
        "ranked": true,
        "rankOf": 1524,
        "categoryRank": 23,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 90,
          "maintenance": 85,
          "payments": 40,
          "reliability": 45,
          "schema": 85,
          "security": 50,
          "transparency": 72
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-13"
        },
        "negative": 0,
        "verdict": "Google's fast Gemini 4 model, on every tier of the Gemini API including the free one, at $1.50 and $7.50 per million tokens with a 1M-token budget, four thinking levels, function calling and structured output. Sampling parameters are ignored, explicit caching isn't supported, it's a short-term release with 45 days' notice on Cloud, and the benchmarks are Google's.",
        "bestFor": "Agents doing everyday coding, tool calls and document work at volume on the Gemini API, including ones that need to start on a free key, or as the executor beside Carbon or Argon.",
        "strengths": [
          "On the free tier of the Gemini API, unlike Carbon and Argon",
          "$1.50 input and $7.50 output per million tokens, flat across the 1M-token window",
          "1,048,576 tokens shared between input and output, with long decodes to the full budget",
          "Four thinking levels, function calling, structured output, code execution, grounding and computer use",
          "The same API, keys and SDKs as Argon and Carbon, plus an OpenAI-compatible surface, so switching is a model ID"
        ],
        "weaknesses": [
          "temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400",
          "No explicit context caching or prefilled model turns, and strict thought-signature rules on parallel calls",
          "A short-term release, with a minimum of 45 days' notice before retirement on Google Cloud",
          "Free-tier content is used to improve Google's products and may be read by people",
          "Benchmark figures are Google's own, and the model card says jailbreak resistance is still being improved"
        ],
        "agentNotes": [
          "Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-hydrogen and an x-goog-api-key",
          "Set thinking_level instead of thinking_budget; the default is HIGH, so set MEDIUM to keep 3.8 Flash's latency",
          "Don't send temperature, top_p, top_k, penalties or candidate_count above 1",
          "Pass every thought_signature back in its original part, on the first parallel functionCall only, or the call returns a 400",
          "Put static content of 4,096 tokens or more first so implicit caching applies, and keep confidential prompts off the free tier"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.9
          }
        ],
        "editorialScores": {
          "ergonomics": 90,
          "maintenance": 85,
          "payments": 40,
          "reliability": 45,
          "schema": 85,
          "security": 50,
          "transparency": 55
        },
        "provenanceScore": 89,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-13",
            "maintenance": "2026-11-13",
            "payments": "2026-11-13",
            "reliability": "2026-11-13",
            "schema": "2026-11-13",
            "security": "2026-11-13",
            "transparency": "2026-11-13"
          },
          "last": "2026-11-13",
          "oldest": "2026-11-13",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "http": "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-4-hydrogen: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-hydrogen"
      },
      "sameCompany": [
        "gemini-4-carbon",
        "vertex-ai",
        "embeddinggemma-2",
        "embeddinggemma-300m",
        "gemini-embedding",
        "vertex-ai-tuning",
        "cloud-run-gpus",
        "google-model-armor",
        "shieldgemma",
        "google-imagen",
        "gemini-omni-1-2-flash",
        "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",
        "puppeteer",
        "mcp-toolbox-databases",
        "google-maps-platform",
        "google-cloud-translation",
        "google-calendar-api",
        "firebase-cloud-messaging",
        "google-cloud-storage",
        "google-drive-api",
        "gemini-enterprise",
        "gemini-decision-1",
        "antigravity-cli",
        "gemini-cli",
        "harness2",
        "jules",
        "gemini-spark",
        "google-search-console",
        "google-ads-api",
        "google-forms",
        "google-sheets-api",
        "gmail-api",
        "google-people-api",
        "diffusiongemma-26b-a4b-it",
        "gemma-4-12b-it",
        "gemma-4-26b-a4b-it",
        "gemma-4-31b-it",
        "gemma-4-e2b-it",
        "gemma-4-e4b-it",
        "virustotal"
      ],
      "sameModel": [
        "gemini-api"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "Gemini 4 Hydrogen input",
          "unit": "1m-tokens",
          "usd": 1.5,
          "note": "Flat across the 1M window"
        },
        {
          "item": "Gemini 4 Hydrogen output",
          "unit": "1m-tokens",
          "usd": 7.5,
          "note": "Thinking tokens included"
        }
      ],
      "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": "2026-11-13",
        "score": 89
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/gemini-4-hydrogen.json",
      "live": {
        "slug": "gemini-4-hydrogen",
        "probe": {
          "target": "https://generativelanguage.googleapis.com/v1beta",
          "method": "get",
          "lastAt": "2026-11-14T00:27:54.542358891Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 29,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 33,
          "p95ms24h": 85,
          "samples24h": 37,
          "samples30d": 37,
          "days": [
            {
              "date": "2026-11-13",
              "probes": 32,
              "ok": 32
            },
            {
              "date": "2026-11-14",
              "probes": 5,
              "ok": 5
            }
          ],
          "since": "2026-11-13T20:58:02.850712558Z"
        },
        "vendorStatus": {
          "page": "https://aistudio.google.com/status",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-11-13T23:54:32.148379631Z"
        },
        "updatedAt": "2026-11-14T00:27:54.542358891Z"
      },
      "streak": {
        "days": 1,
        "from": "2026-11-13",
        "sinceWatching": true,
        "best": 1
      }
    },
    "answer": "Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Novita AI's 56.1 (C), 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": 56.1,
        "grade": "C",
        "agentReady": false,
        "rank": 937,
        "ranked": true,
        "rankOf": 1524,
        "categoryRank": 35,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 72,
          "maintenance": 66,
          "payments": 53,
          "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": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 56.1
          }
        ],
        "editorialScores": {
          "ergonomics": 72,
          "maintenance": 66,
          "payments": 53,
          "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": "2026-11-13",
          "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": "2026-11-14T00:28:04.387393325Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 169,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 190,
          "p95ms24h": 271,
          "samples24h": 238,
          "samples30d": 7649,
          "days": [
            {
              "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
            },
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          "source": "https://docs.novita.ai/changelog/15-10-26"
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    "edges": [
      {
        "by": 23,
        "category": "schema",
        "leads": "gemini-4-hydrogen",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "Model reading for gemini-4-hydrogen 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 Hydrogen takes, every parameter that's ignored or returns 400, the thought-signature rules and how to migrate from Gemini 3.8 Flash, though it doesn't document forced calls (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
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      },
      {
        "by": 19,
        "category": "maintenance",
        "leads": "gemini-4-hydrogen",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "Model reading for gemini-4-hydrogen 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 on 12 November 2026, recorded in Google Cloud's release notes; the Gemini API changelog, last updated 30 October, has no entry for it yet (30). Google Cloud states a minimum of 45 days' notice before Hydrogen is retired, short and stated for Cloud only; the Gemini API's deprecations give earliest dates with no stated minimum (6 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; the developer guide names the minimum google-genai, @google/genai, Go and Java versions (15). Runtimes stated (10). 30 + 6 + 4 + 15 + 5 + 15 + 10 = 85.",
          "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": 85,
          "b": 66
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      },
      {
        "by": 18,
        "category": "ergonomics",
        "leads": "gemini-4-hydrogen",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Model reading for gemini-4-hydrogen 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 to a response_schema, listed as supported on the Cloud model page (13 of 15). Implicit caching on prefixes of 4,096 tokens or more with durable caching on by default and explicit caches not supported, per the Cloud model page; the announcement names no cached-input price (12 of 15). 1,048,576 tokens shared between input and output, with background long decode up to 1M (15). Batch at half price on the platform (10). Python and JavaScript SDKs, and an OpenAI-compatible Chat Completions surface (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 12 + 15 + 10 + 10 + 10 = 90.",
          "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": 90,
          "b": 72
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      },
      {
        "by": 17,
        "category": "reliability",
        "leads": "gemini-4-hydrogen",
        "name": "Reliability",
        "reasons": {
          "a": "Model reading for gemini-4-hydrogen 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). Google Cloud's release notes and model page call Hydrogen generally available, a short-term release, under the same model ID; the Gemini API pages read don't name a stage, so full marks rest on Cloud's statement (10, a judgement call; Carbon, with no stage stated anywhere, got 5). 10 + 5 + 5 + 15 + 0 + 10 = 45.",
          "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": 45,
          "b": 28
        }
      },
      {
        "by": 15,
        "category": "security",
        "leads": "novita-ai",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "Model reading for gemini-4-hydrogen 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). Hydrogen is on the free tier, where Google's terms say content is used to improve products and may be read by humans; paid-tier content isn't (10 of 20, the platform's reading; Carbon, paid tier only, got 15). Abuse retention has no number and new paid projects store requests by default since 26 October; Google's prompt-injection figure (2.3 times more resilient on Gray Swan's benchmark) is its own, and the model card says jailbreak resistance is still being improved (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 10 + 5 + 15 + 5 = 50.",
          "b": "Model reading. Bearer keys with the `sk_` prefix, shown once, up to 10 an account, with an expiry of 24 hours, 30 days, 90 days or none fixed at creation, deletable in the console, and a per-key model access policy and source IP allowlist that can be set by API. OAuth with PKCE and the scopes `api` and `balance:read` is described in `auth.md`, with no token revocation endpoint. No documented way to send a key in a URL was found (26 of 30). The terms, re-read on 4 November and still updated 5 August 2026, say content is not used to train Novita's models or improve the services by default (17 of 20). The terms state zero data retention, with exceptions for law and for what is necessary to run or support the service, and allow automated safety screening. Batch input files are kept for 15 days (11 of 15). Billing can be queried per key, and budget, monitoring and metrics pages are listed in the docs index and were not read (7 of 15). The trust centre at trust.novita.ai is drawn by script and was not read. `/.well-known/security.txt` returns 404, and no disclosure policy or bug bounty was found (4 of 20). The key, retention and trust-centre readings are per the 9 October check, not re-read on 4 November."
        },
        "scores": {
          "a": 50,
          "b": 65
        }
      },
      {
        "by": 15,
        "category": "transparency",
        "leads": "gemini-4-hydrogen",
        "name": "Transparency \u0026 trust",
        "reasons": {
          "a": "Model reading for gemini-4-hydrogen 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). Free-tier content is used to improve products, paid-tier content isn't, abuse retention has no number, and request storage is on by default for new paid projects; the statements agree with each other (20 of 30). Deprecations table, and a stated 45-day minimum on Cloud (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). A DeepMind model card gives a March 2026 knowledge cutoff, automated safety results and Frontier Safety Framework outcomes, with the full safety report marked coming soon. 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
        }
      }
    ],
    "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": "2026-11-12",
        "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 Hydrogen scores 64.9 (B) on agent readiness against Novita AI's 56.1 (C), 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 Hydrogen or Novita AI?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Gemini 4 Hydrogen and Novita AI need an API key?"
      },
      {
        "answer": "Yes. Gemini 4 Hydrogen 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 Hydrogen and Novita AI without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 45 against 28",
          "Schema \u0026 documentation, 85 against 62",
          "Agent ergonomics, 90 against 72",
          "Maintenance \u0026 community, 85 against 66",
          "Transparency \u0026 trust, 72 against 57"
        ],
        "also": null,
        "goodFor": "Agents doing everyday coding, tool calls and document work at volume on the Gemini API, including ones that need to start on a free key, or as the executor beside Carbon or Argon.",
        "slug": "gemini-4-hydrogen",
        "watchFor": "temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400"
      },
      {
        "aheadOn": [
          "Security \u0026 auth, 65 against 50",
          "Payments \u0026 pricing, 53 against 40"
        ],
        "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-hydrogen": null,
      "novita-ai": [
        {
          "causes": [
            "method"
          ],
          "date": "2026-11-13",
          "delta": 2.2,
          "from": 53.9,
          "fromGrade": "D",
          "to": 56.1,
          "toGrade": "C"
        },
        {
          "causes": [
            "evidence"
          ],
          "date": "2026-11-04",
          "delta": 0.4,
          "from": 53.5,
          "fromGrade": "D",
          "to": 53.9,
          "toGrade": "D"
        },
        {
          "causes": [
            "method"
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        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-novita-ai.json",
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai.json",
        "title": "DeepSeek API vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai"
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        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-hydrogen.json",
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      {
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        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-hydrogen.json",
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        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-hugging-face-inference-providers.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-hy4.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-meta-model-api.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-prism-inference.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-reflection-beam.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-sambanova.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-siliconflow.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-simplismart.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-prism-inference.json",
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        "url": "https://www.anchorterminal.com/compare/novita-ai-vs-prism-inference"
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      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-ramp-router.json",
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        "url": "https://www.anchorterminal.com/compare/novita-ai-vs-ramp-router"
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-routerplus.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.json",
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      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-simplismart.json",
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      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-stepfun-api.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-swe-2-flash.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-tencent-tokenhub.json",
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      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-vercel-ai-gateway.json",
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api.json",
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-novita-ai.json",
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    "scores": [
      {
        "by": 17,
        "edge": "gemini-4-hydrogen",
        "gemini-4-hydrogen": 45,
        "key": "reliability",
        "name": "Reliability",
        "novita-ai": 28,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 23,
        "edge": "gemini-4-hydrogen",
        "gemini-4-hydrogen": 85,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "novita-ai": 62,
        "weight": 13
      },
      {
        "by": 18,
        "edge": "gemini-4-hydrogen",
        "gemini-4-hydrogen": 90,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "novita-ai": 72,
        "weight": 13
      },
      {
        "by": 15,
        "edge": "novita-ai",
        "gemini-4-hydrogen": 50,
        "key": "security",
        "name": "Security \u0026 auth",
        "novita-ai": 65,
        "weight": 14
      },
      {
        "by": 13,
        "edge": "novita-ai",
        "gemini-4-hydrogen": 40,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "novita-ai": 53,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 19,
        "edge": "gemini-4-hydrogen",
        "gemini-4-hydrogen": 85,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "novita-ai": 66,
        "weight": 7
      },
      {
        "by": 15,
        "edge": "gemini-4-hydrogen",
        "gemini-4-hydrogen": 72,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "novita-ai": 57,
        "weight": 7
      }
    ],
    "summary": "Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Novita AI's 56.1 (C), 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-hydrogen": "Google's fast Gemini 4 model, on every tier of the Gemini API including the free one, at $1.50 and $7.50 per million tokens with a 1M-token budget, four thinking levels, function calling and structured output. Sampling parameters are ignored, explicit caching isn't supported, it's a short-term release with 45 days' notice on Cloud, and the benchmarks are Google's.",
      "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-hydrogen-vs-novita-ai",
    "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-novita-ai.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-novita-ai.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-novita-ai.min.md"
  },
  "markdown": "Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Novita AI's 56.1 (C), 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 Hydrogen: grade B, 64.9/100, rank #546 of 1524. Markdown https://www.anchorterminal.com/tools/gemini-4-hydrogen.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json\n- Novita AI: grade C, 56.1/100, rank #937 of 1524. 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 1044 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Gemini 4 Hydrogen (B)\n\nGood for: Agents doing everyday coding, tool calls and document work at volume on the Gemini API, including ones that need to start on a free key, or as the executor beside Carbon or Argon.\n\nAhead on:\n- Reliability, 45 against 28\n- Schema \u0026 documentation, 85 against 62\n- Agent ergonomics, 90 against 72\n- Maintenance \u0026 community, 85 against 66\n- Transparency \u0026 trust, 72 against 57\n\nWatch for: temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400\n\n### Novita AI (C)\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 50\n- Payments \u0026 pricing, 53 against 40\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 Hydrogen +23\n\n- Gemini 4 Hydrogen (85): Model reading for gemini-4-hydrogen 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 Hydrogen takes, every parameter that's ignored or returns 400, the thought-signature rules and how to migrate from Gemini 3.8 Flash, though it doesn't document forced calls (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### Maintenance \u0026 community: Gemini 4 Hydrogen +19\n\n- Gemini 4 Hydrogen (85): Model reading for gemini-4-hydrogen 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 on 12 November 2026, recorded in Google Cloud's release notes; the Gemini API changelog, last updated 30 October, has no entry for it yet (30). Google Cloud states a minimum of 45 days' notice before Hydrogen is retired, short and stated for Cloud only; the Gemini API's deprecations give earliest dates with no stated minimum (6 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; the developer guide names the minimum google-genai, @google/genai, Go and Java versions (15). Runtimes stated (10). 30 + 6 + 4 + 15 + 5 + 15 + 10 = 85.\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### Agent ergonomics: Gemini 4 Hydrogen +18\n\n- Gemini 4 Hydrogen (90): Model reading for gemini-4-hydrogen 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 to a response_schema, listed as supported on the Cloud model page (13 of 15). Implicit caching on prefixes of 4,096 tokens or more with durable caching on by default and explicit caches not supported, per the Cloud model page; the announcement names no cached-input price (12 of 15). 1,048,576 tokens shared between input and output, with background long decode up to 1M (15). Batch at half price on the platform (10). Python and JavaScript SDKs, and an OpenAI-compatible Chat Completions surface (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 12 + 15 + 10 + 10 + 10 = 90.\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### Reliability: Gemini 4 Hydrogen +17\n\n- Gemini 4 Hydrogen (45): Model reading for gemini-4-hydrogen 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). Google Cloud's release notes and model page call Hydrogen generally available, a short-term release, under the same model ID; the Gemini API pages read don't name a stage, so full marks rest on Cloud's statement (10, a judgement call; Carbon, with no stage stated anywhere, got 5). 10 + 5 + 5 + 15 + 0 + 10 = 45.\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### Security \u0026 auth: Novita AI +15\n\n- Gemini 4 Hydrogen (50): Model reading for gemini-4-hydrogen 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). Hydrogen is on the free tier, where Google's terms say content is used to improve products and may be read by humans; paid-tier content isn't (10 of 20, the platform's reading; Carbon, paid tier only, got 15). Abuse retention has no number and new paid projects store requests by default since 26 October; Google's prompt-injection figure (2.3 times more resilient on Gray Swan's benchmark) is its own, and the model card says jailbreak resistance is still being improved (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 10 + 5 + 15 + 5 = 50.\n- Novita AI (65): Model reading. Bearer keys with the `sk_` prefix, shown once, up to 10 an account, with an expiry of 24 hours, 30 days, 90 days or none fixed at creation, deletable in the console, and a per-key model access policy and source IP allowlist that can be set by API. OAuth with PKCE and the scopes `api` and `balance:read` is described in `auth.md`, with no token revocation endpoint. No documented way to send a key in a URL was found (26 of 30). The terms, re-read on 4 November and still updated 5 August 2026, say content is not used to train Novita's models or improve the services by default (17 of 20). The terms state zero data retention, with exceptions for law and for what is necessary to run or support the service, and allow automated safety screening. Batch input files are kept for 15 days (11 of 15). Billing can be queried per key, and budget, monitoring and metrics pages are listed in the docs index and were not read (7 of 15). The trust centre at trust.novita.ai is drawn by script and was not read. `/.well-known/security.txt` returns 404, and no disclosure policy or bug bounty was found (4 of 20). The key, retention and trust-centre readings are per the 9 October check, not re-read on 4 November.\n\n### Transparency \u0026 trust: Gemini 4 Hydrogen +15\n\n- Gemini 4 Hydrogen (72): Model reading for gemini-4-hydrogen 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). Free-tier content is used to improve products, paid-tier content isn't, abuse retention has no number, and request storage is on by default for new paid projects; the statements agree with each other (20 of 30). Deprecations table, and a stated 45-day minimum on Cloud (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). A DeepMind model card gives a March 2026 knowledge cutoff, automated safety results and Frontier Safety Framework outcomes, with the full safety report marked coming soon. 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## Score by category\n\n| Category | Weight | Gemini 4 Hydrogen | Novita AI | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 45 | 28 | Gemini 4 Hydrogen +17 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 62 | Gemini 4 Hydrogen +23 |\n| Agent ergonomics | 13% (16.2 this run) | 90 | 72 | Gemini 4 Hydrogen +18 |\n| Security \u0026 auth | 14% (17.5 this run) | 50 | 65 | Novita AI +15 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 53 | Novita AI +13 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 85 | 66 | Gemini 4 Hydrogen +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 57 | Gemini 4 Hydrogen +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.9 · B** | **56.1 · C** | |\n\n## Facts side by side\n\n| Fact | Gemini 4 Hydrogen | 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 | 2026-11-12 | 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 Hydrogen\n\nNo score change since it was listed.\n\n### Novita AI\n\n- +2.2 on 13 November 2026 (D to C): checklist\n- +0.4 on 4 November 2026: new evidence\n- no change on 27 October 2026: checklist\n\n## Verdicts\n\n**Gemini 4 Hydrogen.** Google's fast Gemini 4 model, on every tier of the Gemini API including the free one, at $1.50 and $7.50 per million tokens with a 1M-token budget, four thinking levels, function calling and structured output. Sampling parameters are ignored, explicit caching isn't supported, it's a short-term release with 45 days' notice on Cloud, and the benchmarks are Google's.\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 Hydrogen\n\n1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-hydrogen and an x-goog-api-key\n2. Set thinking_level instead of thinking_budget; the default is HIGH, so set MEDIUM to keep 3.8 Flash's latency\n3. Don't send temperature, top_p, top_k, penalties or candidate_count above 1\n4. Pass every thought_signature back in its original part, on the first parallel functionCall only, or the call returns a 400\n5. Put static content of 4,096 tokens or more first so implicit caching applies, and keep confidential prompts off the free tier\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 Hydrogen or Novita AI?\n\nGemini 4 Hydrogen scores 64.9 (B) on agent readiness against Novita AI's 56.1 (C), and leads in 5 of 7 scored categories. Novita AI leads on security \u0026 auth and payments \u0026 pricing.\n\n### Do Gemini 4 Hydrogen and Novita AI need an API key?\n\nBoth need an API key.\n\n### Can an agent call Gemini 4 Hydrogen and Novita AI without installing anything?\n\nYes. Gemini 4 Hydrogen 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-hydrogen-vs-novita-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-novita-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-4-hydrogen\", \"b\": \"novita-ai\"}`. From a terminal: `anchor compare gemini-4-hydrogen novita-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json and https://www.anchorterminal.com/api/v1/tools/novita-ai.json\n\n## Other comparisons with Gemini 4 Hydrogen or Novita AI\n\n- [Amazon Bedrock vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-hydrogen.md)\n- [Amazon Bedrock vs Novita AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai.md)\n- [Claude API vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-hydrogen.md)\n- [Claude API vs Novita AI](https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai.md)\n- [Antseed vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-hydrogen.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 Hydrogen](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-hydrogen.md)\n- [Azure OpenAI in Foundry Models vs Novita AI](https://www.anchorterminal.com/compare/azure-openai-vs-novita-ai.md)\n- [BlockRun.AI vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-hydrogen.md)\n- [BlockRun.AI vs Novita AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-novita-ai.md)\n- [Cerebras Inference vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-hydrogen.md)\n- [Cerebras Inference vs Novita AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai.md)\n- [Claude Fable 5.2 vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-hydrogen.md)\n- [Claude Fable 5.2 vs Novita AI](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-novita-ai.md)\n- [Claude Mythos 5.2 vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-hydrogen.md)\n- [Claude Mythos 5.2 vs Novita AI](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-novita-ai.md)\n- [Cloudflare AI Gateway vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-hydrogen.md)\n- [Cloudflare AI Gateway vs Novita AI](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-novita-ai.md)\n- [Cloudflare Workers AI vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-hydrogen.md)\n- [Cloudflare Workers AI vs Novita AI](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-novita-ai.md)\n- [Cohere Chat API (Command models) vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-hydrogen.md)\n- [Cohere Chat API (Command models) vs Novita AI](https://www.anchorterminal.com/compare/cohere-chat-vs-novita-ai.md)\n- [DeepInfra vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-hydrogen.md)\n- [DeepInfra vs Novita AI](https://www.anchorterminal.com/compare/deepinfra-vs-novita-ai.md)\n- [DeepSeek API vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-hydrogen.md)\n- [DeepSeek API vs Novita AI](https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai.md)\n- [Eden AI vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-hydrogen.md)\n- [Eden AI vs Novita AI](https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai.md)\n- [Glimpse vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-hydrogen.md)\n- [Glimpse vs Novita AI](https://www.anchorterminal.com/compare/elorian-glimpse-vs-novita-ai.md)\n- [Fireworks AI Inference vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-hydrogen.md)\n- [Fireworks AI Inference vs Novita 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