{ "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": "2026-11-11T00:39:33.232860164Z", "lastOk": true, "lastStatus": 404, "lastMs": 37, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 39, "p95ms24h": 130, "samples24h": 72, "samples30d": 72, "days": [ { "date": "2026-11-10", "probes": 65, "ok": 65 }, { "date": "2026-11-11", "probes": 7, "ok": 7 } ], "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": "2026-11-11T00:39:33.232860164Z" }, "streak": { "days": 1, "from": "2026-11-10", "sinceWatching": true, "best": 1 } }, "answer": "Vercel AI Gateway scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 2 of 7 scored categories. Gemini 4 Carbon leads on schema \u0026 documentation and agent ergonomics.", "b": { "slug": "vercel-ai-gateway", "name": "Vercel AI Gateway", "vendor": "Vercel Inc.", "vendorUrl": "https://vercel.com", "kind": "router", "category": "inference", "summary": "Vercel AI Gateway is a hosted router for model APIs. One API key or Vercel OIDC token reaches models from OpenAI, Anthropic, Google and others through OpenAI-compatible, Anthropic-compatible and AI SDK interfaces, with budgets, request logs and provider failover.", "url": "https://www.anchorterminal.com/tools/vercel-ai-gateway", "markdownUrl": "https://www.anchorterminal.com/tools/vercel-ai-gateway.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vercel-ai-gateway.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vercel-ai-gateway.json", "dns": "vercel-ai-gateway.grade.anchorterminal.com", "repo": "https://github.com/vercel/ai", "license": "Proprietary service under Vercel's Terms of Service and AI Product Terms, with Token Pass terms on its docs page. Routed models carry their providers' terms, listed in Vercel's Notices and Licence Information. The `@ai-sdk/gateway` provider is Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://ai-gateway.vercel.sh/v1", "packages": [ { "registry": "npm", "name": "@ai-sdk/gateway" }, { "registry": "npm", "name": "ai" }, { "registry": "pypi", "name": "ai" } ], "auth": "mixed", "authNotes": "An AI Gateway API key as a Bearer token from any environment, or a Vercel OIDC token on Vercel deployments (12 hours locally, refreshed with `vercel env pull`). Keys belong to a team, can be limited to one project and given an expiry and a budget, and are created in the dashboard, with the Vercel CLI or by `POST /v1/api-keys` with a Vercel access token. A person creates the Vercel account in a browser. Token Pass needs its own Token Pass API key, and OIDC tokens cannot spend Token Pass credit.", "pricing": "usage", "pricingNotes": "Prepaid AI Gateway Credits at each provider's list price, with no markup or platform fee, including BYOK. A monthly free credit covers a subset of models and needs a valid payment method on the team. Credits expire a year after purchase. Add-ons are billed separately, and Token Pass is $30 a team a month on Pro for $80 of credit on two models, in early access (https://vercel.com/docs/ai-gateway/pricing, https://vercel.com/docs/ai-gateway/token-pass, checked 2026-10-17).", "priceSummary": "$30 / mo", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the AI Gateway docs, the pricing page, the Token Pass pages or the AI Gateway entries of the changelog sitemap. Payment is by prepaid credits bought with a card, or by invoice on Enterprise (checked 2026-10-17).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 29597661, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://vercel.com/docs/ai-gateway", "llmsTxt": "https://vercel.com/llms.txt", "openapi": "https://vercel.com/openapi.json", "capabilities": [ "inference.router", "inference.llm", "inference.fast", "inference.decision", "obs.gateway", "obs.traces", "embed.text", "image.generate", "video.generate" ], "tags": [ "hosted", "router", "usage-based", "prepaid", "free-tier", "openai-compatible", "anthropic-compatible", "llms-txt", "openapi", "typescript", "python", "oidc", "cli", "early-access", "status-page", "bug-bounty", "soc2", "iso27001" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 67.8, "grade": "B", "agentReady": false, "rank": 305, "ranked": true, "rankOf": 1518, "categoryRank": 16, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 83, "maintenance": 79, "payments": 20, "reliability": 79, "schema": 74, "security": 79, "transparency": 71 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "April 2026. Vercel's security bulletin says an attacker took over an employee's account through a compromised third-party AI tool, reached internal systems and decrypted non-sensitive environment variables of a limited subset of customers. AI Gateway was generally available then, and its docs have deployments keep AI Gateway and Token Pass API keys as environment variables. The bulletin documents remediation and marks the incident closed on 16 October 2026, so 3 of a possible 15 is taken, as for vercel-connect (https://vercel.com/kb/bulletin/vercel-april-2026-security-incident)." ], "verdict": "Token prices pass through with no markup, prompts are not stored by the gateway, and budgets, provider failover and per-request logs are built in. The free monthly credit needs a card on file, rate limits are not published as numbers, no SLA covers the API, and the contractual promise not to train on content applies to Enterprise subscriptions only.", "bestFor": "Teams that want one key, one bill, budgets and failover in front of many model providers, especially on Vercel with OIDC.", "strengths": [ "Token prices are each provider's list price with no markup or platform fee, including requests made with the customer's own provider keys", "The model list at `GET /v1/models` needs no key and gives prices, context windows, supported parameters and ZDR and no-training flags for 498 models", "Budgets per team, project, API key or team member reject spend with a 402, distinct from a 429 rate limit", "The gateway logs request metadata only. Prompt and response content is deleted when the request completes, per the FAQ and the ZDR page", "Failed provider attempts are retried on a model's other providers, and every routing attempt appears in the request logs" ], "weaknesses": [ "The free monthly credit needs a valid payment method on the team, and its amount is not stated in the reviewed docs", "No rate-limit numbers are published, and the Enterprise SLA excludes the APIs, so the inference API carries no uptime commitment", "The contractual promise not to train on AI Gateway content covers Enterprise subscriptions only. Provider no-training and ZDR filters are opt-in per request", "A failed BYOK request falls back to Vercel's credentials and is billed to credits, and the no-training filter is not applied to BYOK", "Token Pass is early access for Pro teams only, covers two models, has no failover and fails with a 403 once the $80 credit is spent" ], "agentNotes": [ "Read `GET https://ai-gateway.vercel.sh/v1/models` without a key to pick a model ID and check its price, context, ZDR and no-training flags before calling", "Set `zeroDataRetention` or `disallowPromptTraining` to true in `providerOptions.gateway` on sensitive requests. Default routing ignores provider retention and training policies", "Treat a 429 as retryable and honour `retry-after` when present. A 402 with `quota_for_entity_exceeded` is a spent budget, so do not retry it", "On a Token Pass key, a 403 with `no_providers_available` means spent credit or a model outside the pass. Retry with a standard AI Gateway key, which bills credits", "Set `inferenceRegion` when data residency matters. The default `global` may run inference outside the user's jurisdiction" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.8 } ], "editorialScores": { "ergonomics": 83, "maintenance": 79, "payments": 20, "reliability": 79, "schema": 74, "security": 79, "transparency": 55 }, "provenanceScore": 86, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pnpm add ai@latest", "http": "curl https://ai-gateway.vercel.sh/v1/chat/completions \\\n -H \"Authorization: Bearer $AI_GATEWAY_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"openai/gpt-6-astra\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Explain AI Gateway in one sentence.\"\n }\n ]\n }'" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/vercel-ai-gateway" }, "sameCompany": [ "vercel-sandbox", "vercel-connect" ], "area": "models", "unitPrices": [ { "item": "Token Pass subscription (Pro teams)", "unit": "month", "usd": 30, "note": "$80 of monthly credit on two featured models. Early access" }, { "item": "Team-wide Zero Data Retention", "unit": "1k-requests", "usd": 0.1, "note": "Pro and Enterprise. Per-request ZDR is free" }, { "item": "Team-wide provider allowlist", "unit": "1k-requests", "usd": 0.1, "note": "Successful requests, Pro and Enterprise" }, { "item": "Custom Reporting query", "unit": "1k-requests", "usd": 5, "note": "Queries to the reporting endpoint" }, { "item": "Custom Reporting write of a tag, user ID or quota entity ID", "unit": "1k-requests", "usd": 0.075, "note": "Each unique value in a request counts as one write" }, { "item": "AI Gateway trace delivered to a drain", "unit": "1k-requests", "usd": 0.05, "note": "Listed per 1,000 traces, Pro and Enterprise" }, { "item": "Trace egress", "unit": "gb", "usd": 0.5, "note": "Billed through Drains usage" } ], "provenance": { "legalEntity": "Vercel Inc.", "domain": "vercel.com", "domainRegistered": "1999-10-04", "endpointOnVendorDomain": false, "terms": "https://vercel.com/legal/terms", "privacy": "https://vercel.com/legal/privacy-policy", "statusPage": "https://www.vercel-status.com", "changelog": "https://vercel.com/changelog", "securityTxt": "valid", "checked": "2026-11-01", "notes": [ "The Terms of Service (last updated 19 October 2026) name Vercel Inc. The AI Product Terms (last updated 17 March 2026, effective 31 March 2026) have a section for AI Gateway and form part of those terms.", "The Privacy Notice is effective from 1 June 2026. The DPA (effective 31 March 2026) applies to Pro and Enterprise plans.", "https://vercel.com/.well-known/security.txt points to HackerOne and responsible.disclosure@vercel.com and expires 2027-09-28 (re-read 1 November 2026).", "The API answers at ai-gateway.vercel.sh, a Vercel domain other than vercel.com. Management calls go to api.vercel.com.", "RDAP gives vercel.com a registration date of 1999-10-04, long before Vercel, so the domain was bought later.", "AI Gateway is a component on the status page at www.vercel-status.com." ], "score": 86 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/vercel-ai-gateway.json", "live": { "slug": "vercel-ai-gateway", "probe": { "target": "https://ai-gateway.vercel.sh/v1", "method": "get", "lastAt": "2026-11-11T00:40:00.076837706Z", "lastOk": true, "lastStatus": 404, "lastMs": 157, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 38, "p95ms24h": 152, "samples24h": 244, "samples30d": 5938, "days": [ { "date": "2026-10-17", "probes": 21, "ok": 21 }, { "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": 250, "ok": 250 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "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": 7, "ok": 7 } ], "since": "2026-10-17T00:00:00Z" }, "vendorStatus": { "page": "https://www.vercel-status.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-11T00:36:26.482419444Z" }, "versions": [ { "registry": "github", "name": "vercel/ai", "version": "@ai-sdk/vue@2.0.287", "released": "2026-11-09", "seenAt": "2026-11-10T04:28:18.851601221Z" }, { "registry": "npm", "name": "@ai-sdk/gateway", "version": "4.0.139", "seenAt": "2026-11-10T04:28:16.650990819Z" }, { "registry": "npm", "name": "ai", "version": "7.0.166", "seenAt": "2026-11-10T04:28:17.464347865Z" }, { "registry": "pypi", "name": "ai", "version": "0.9.0", "released": "2026-11-04", "seenAt": "2026-11-10T04:28:18.662403397Z" } ], "githubStars": 27844, "npmWeekly": 43995943, "pypiWeekly": 45283, "securityTxt": { "url": "https://vercel.com/.well-known/security.txt", "state": "valid", "expires": "2027-09-28T12:00:00.000Z", "checkedAt": "2026-11-10T16:07:59.072520635Z" }, "llmsTxt": { "url": "https://vercel.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:45:00.65431693Z" }, "domain": { "domain": "vercel.com", "registered": "1999-10-04", "source": "https://rdap.verisign.com/com/v1/domain/vercel.com", "checkedAt": "2026-11-08T15:11:10.088686399Z" }, "pages": [ { "url": "https://vercel.com/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:34:33.339720599Z", "changedAt": "2026-11-10T16:34:33.339720599Z", "fingerprint": "2410474f21d8" }, { "url": "https://ai-gateway.vercel.sh/v1/models", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:09:23.127668128Z", "changedAt": "0001-01-01T00:00:00Z" }, { "url": "https://vercel.com/changelog/laya-decision-model-now-available-on-ai-gateway-free-through-october-31", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:34:35.564574013Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6bbbff189272" }, { "url": "https://vercel.com/changelog/tako-search-is-free-on-ai-gateway-through-september-30th", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:34:37.989880889Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "196bc432bb9c" }, { "url": "https://vercel.com/docs/ai-gateway/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-10T16:34:40.049709019Z", "changedAt": "2026-11-08T15:15:23.859461119Z", "fingerprint": "f0fe41c0ebfa" }, { "url": "https://vercel.com/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-10T16:34:45.896997544Z", "changedAt": "2026-10-28T04:46:11.674155692Z", "fingerprint": "c545eb853c20" }, { "url": "https://vercel.com/legal/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:34:48.92996188Z", "changedAt": "2026-10-28T04:46:13.475126487Z", "fingerprint": "100a29fa0aba" } ], "github": { "repo": "vercel/ai", "checkedAt": "2026-11-09T09:55:49.824362486Z", "stars": 27827, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-09T02:57:28Z", "openIssues": 480, "openPRs": 1033, "issuesOpened90d": 1082, "issuesClosed90d": 1417, "prsMerged90d": 2739, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-11-09T02:56:36Z" }, "advisories": [ { "ghsa": "GHSA-g3x3-7q3h-gmhj", "severity": "medium", "published": "2026-10-01T19:22:11Z" }, { "ghsa": "GHSA-4mqq-99j3-3hmv", "severity": "high", "published": "2026-09-28T17:44:55Z" }, { "ghsa": "GHSA-222v-gj5h-ff73", "severity": "high", "published": "2026-08-20T21:21:04Z" }, { "ghsa": "GHSA-vmqp-7rwf-cq3w", "severity": "medium", "published": "2026-08-14T01:39:36Z" }, { "ghsa": "GHSA-qw9h-448j-6rph", "cve": "CVE-2026-64650", "severity": "medium", "published": "2026-07-20T20:16:06Z" }, { "ghsa": "GHSA-g48p-5rr5-8rgq", "cve": "CVE-2026-64651", "severity": "medium", "published": "2026-07-20T20:15:50Z" } ], "replies": { "sampled": 25, "unanswered": 12, "medianDays": 0.8 } }, "updatedAt": "2026-11-11T00:40:00.076837706Z" }, "streak": { "days": 6, "from": "2026-11-05", "last": { "kind": "shutdown", "date": "2026-11-05", "what": "`spacexai/grok-voice-think-fast-2.0` is retired from AI Gateway (`deprecated_at` in the model list)", "source": "https://ai-gateway.vercel.sh/v1/models" }, "next": { "kind": "shutdown", "date": "2026-11-13", "what": "`poolside/laguna-s-2.1` is retired from AI Gateway (`deprecated_at` in the model list)", "source": "https://ai-gateway.vercel.sh/v1/models" }, "best": 14 } }, "edges": [ { "by": 39, "category": "reliability", "leads": "vercel-ai-gateway", "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. AI Gateway is a component on www.vercel-status.com (20). The history feed, re-read on 1 November 2026, has 25 entries from 23 July to 23 October, so it covers the whole 90 days from 3 August. None names AI Gateway in its title or text. The Drains, Logs and Observability incidents (6, 17 and 20 August, 16 to 17 September, 10 October in Washington, which names delayed logs, metrics and traces in general, and 23 October) name no AI Gateway surface, and none reports requests failing. Component tags sit in the status API, which robots.txt disallows, so they were not used. A readable page that posts incidents, none touching the product, is a clean record, as vercel-connect's incidents were read from the same feed (30). The rate-limit page, re-read on 1 November, says it describes behaviour rather than fixed numbers. The paid tier has no gateway limit, and the free tier's per-model limits are not published (5 of 15). A 429 has a documented JSON body, some carry `retry-after`, the docs give backoff code and separate a 429 from a 402 budget rejection, and failed provider attempts are retried on other providers (14 of 15). The Enterprise SLA excludes the APIs and CLI, and no SLA naming AI Gateway was found (0). Generally available since 21 August 2025. Token Pass is early access and the Python SDK is in beta (10)." }, "scores": { "a": 40, "b": 79 } }, { "by": 24, "category": "security", "leads": "vercel-ai-gateway", "name": "Security \u0026 auth", "reasons": { "a": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Carbon is on the paid tier only, and Google's terms say paid-tier content isn't used to improve products; AI Studio use under a Google AI Ultra subscription falls under terms we didn't read, so 15 of 20 (a judgement call; the platform's 10 is for its free tier). Abuse retention with no number, and new paid projects store requests by default since 26 October (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 15 + 5 + 15 + 5 = 55.", "b": "Router, read on the model lines. AI Gateway API keys belong to a team, can be limited to one project and given an expiry and a budget, are deactivated when their creator leaves the team, and can be revoked without authentication by reporting a leaked key. Keys carry no per-model or read-only scope apart from the Token Pass key type. On Vercel, project OIDC tokens replace long-lived keys (24 of 30). Vercel says it does not train on prompts, and the AI Product Terms make that a warranty only for Enterprise subscriptions. Provider training is filtered only when `disallowPromptTraining` or ZDR is set, the filter does not apply to BYOK, and the terms say Stealth Model providers may train on inputs (12 of 20). The gateway does not keep prompt or response content. Provider ZDR is free per request on Pro and Enterprise and not available on Hobby, and BYOK keys are skipped under ZDR unless marked (12 of 15). Per-request logs record status, provider attempts, tokens, cost and authentication method, with routing details kept 30 days and Trace Drains and spend reports on paid plans (13 of 15). Valid security.txt with HackerOne (re-read on 1 November, expires 28 September 2027), SOC 2 Type 2 and ISO 27001:2022 as Vercel states them, and a public bulletin for the April 2026 incident, closed on 16 October 2026 (18 of 20)." }, "scores": { "a": 55, "b": 79 } }, { "by": 11, "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": "Router, scored on the API lines. Vercel's OpenAPI 3.0.3 document has AI Gateway management paths (budgets, routing rules, virtual model configs, routers) and `POST /api-keys`. It does not cover the inference routes on ai-gateway.vercel.sh or `/v1/models`, `/v1/credits`, `/v1/generation` and `/v1/report`, which follow the OpenAI and Anthropic formats and the REST reference page (12 of 25). Every docs page is served as Markdown, and vercel.com/llms.txt lists AI Gateway and the keyless model list (10). The docs say when to use AI Gateway, which API format suits which client, and what each control leaves out, such as BYOK spend outside budgets (16 of 20). `providerOptions.gateway` fields are documented in tables with types, and the model list names each model's supported parameters. The request bodies have no published schema of their own (9 of 15). cURL, TypeScript and Python examples on most pages, and error tables in the FAQ, the REST reference and the Token Pass pages. The Chat Completions error list omits 402 (13 of 15). Paths carry `/v1`, the changelog is dated, with 95 entries naming AI Gateway from 3 August to 30 October 2026, and `@ai-sdk/gateway` keeps a CHANGELOG. The changelog sitemap dates one AI Gateway entry to 25 March 2025, before the alpha (14 of 15)." }, "scores": { "a": 85, "b": 74 } }, { "by": 10, "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": "Router, read on the model lines. Tool calling is documented on all six surfaces and 303 of 498 models carry the tool-use tag on 1 November, with behaviour depending on the model routed (16 of 20). Structured output is documented per surface and tagged on 278 models (13 of 15). `caching: 'auto'` adds Anthropic cache markers, `cache_ttl` asks for one-hour entries, `x-session-affinity` keeps a conversation on one provider, and cache-read prices are listed per model (14 of 15). 162 models list a context of one million tokens or more, a judgement call since a router has no default model (15). The SDK source has a `gateway-batch.ts` file, but no batch endpoint or batch discount was found in the docs (2 of 10). The AI SDK for TypeScript, the AI SDK for Python in beta, and the OpenAI and Anthropic SDKs with a changed base URL (10). Errors return `message` and `type`, an exceeded budget answers 402 apart from a 429, the SDK has ten typed `Gateway*Error` classes, and the FAQ maps each status to a fix (13 of 15)." }, "scores": { "a": 93, "b": 83 } } ], "facts": [ { "a": "Model API", "b": "Model router", "name": "Kind" }, { "a": "Google", "b": "Vercel Inc.", "name": "Vendor" }, { "a": "https://generativelanguage.googleapis.com/v1beta", "b": "https://ai-gateway.vercel.sh/v1", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "OAuth or 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 Vercel's Terms of Service and AI Product Terms, with Token Pass terms on its docs page. Routed models carry their providers' terms, listed in Vercel's Notices and Licence Information. The `@ai-sdk/gateway` provider is Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-10", "b": "2026-10-30", "name": "Last release" }, { "a": "2026-04-28", "b": "2026-06-01", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "2026-06-01", "name": "Privacy policy last updated" }, { "a": "yes", "b": "yes, with an opt-out", "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": "not found in the text", "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": "29.6M npm/wk", "name": "Popularity" }, { "a": "none", "b": "3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Vercel AI Gateway scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 2 of 7 scored categories. Gemini 4 Carbon leads on schema \u0026 documentation and agent ergonomics.", "question": "Which is better for AI agents, Gemini 4 Carbon or Vercel AI Gateway?" }, { "answer": "Gemini 4 Carbon needs an API key. Vercel AI Gateway takes an API key or an OAuth sign-in.", "question": "Do Gemini 4 Carbon and Vercel AI Gateway need an API key?" }, { "answer": "Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Vercel AI Gateway at https://ai-gateway.vercel.sh/v1.", "question": "Can an agent call Gemini 4 Carbon and Vercel AI Gateway without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 85 against 74", "Agent ergonomics, 93 against 83" ], "also": [ "No incidents deducted, where Vercel AI Gateway loses 3 points for them" ], "goodFor": "Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.", "slug": "gemini-4-carbon", "watchFor": "Paid tier only, with no free tier to try it on" }, { "aheadOn": [ "Reliability, 79 against 40", "Security \u0026 auth, 79 against 55" ], "also": null, "goodFor": "Teams that want one key, one bill, budgets and failover in front of many model providers, especially on Vercel with OIDC.", "slug": "vercel-ai-gateway", "watchFor": "The free monthly credit needs a valid payment method on the team, and its amount is not stated in the reviewed docs" } ], "history": { "gemini-4-carbon": null, "vercel-ai-gateway": [ { "causes": [ "correction" ], "date": "2026-11-01", "delta": 1, "from": 66.8, "fromGrade": "B", "to": 67.8, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 66.7, "fromGrade": "B", "to": 66.8, "toGrade": "B" } ] }, "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-vercel-ai-gateway.json", "title": "Amazon Bedrock vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway" }, { "json": 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"title": "Gemini 4 Carbon vs MiniMax API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api.json", "title": "Gemini 4 Carbon vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember.json", "title": "Gemini 4 Carbon vs Muse Ember", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.json", "title": "Gemini 4 Carbon vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl.json", "title": "Gemini 4 Carbon vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.json", "title": "Gemini 4 Carbon vs Novita AI", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openai-api.json", "title": "Gemini 4 Carbon vs OpenAI API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openrouter.json", "title": "Gemini 4 Carbon vs OpenRouter", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-prism-inference.json", "title": "Gemini 4 Carbon vs Prism Inference", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-ramp-router.json", "title": "Gemini 4 Carbon vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.json", "title": "Gemini 4 Carbon vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus.json", "title": "Gemini 4 Carbon vs RouterPlus", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.json", "title": "Gemini 4 Carbon vs SambaCloud", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow.json", "title": "Gemini 4 Carbon vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.json", "title": "Gemini 4 Carbon vs Simplismart", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.json", "title": "Gemini 4 Carbon vs StepFun API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.json", "title": "Gemini 4 Carbon vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.json", "title": "Gemini 4 Carbon vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.json", "title": "Gemini 4 Carbon vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-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-vercel-ai-gateway.json", "title": "Gemini Developer API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway.json", "title": "GroqCloud vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway.json", "title": "Inkling 2 Small vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.json", "title": "Jais 3 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.json", "title": "Meta Model API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway.json", "title": "MiniMax API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-vercel-ai-gateway.json", "title": "Mistral AI API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway.json", "title": "Muse Ember vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway.json", "title": "Muse Spark Open vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vercel-ai-gateway.json", "title": "Nemotron 3.5 Super VL vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vercel-ai-gateway" }, { "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/openai-api-vs-vercel-ai-gateway.json", "title": "OpenAI API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-vercel-ai-gateway.json", "title": "OpenRouter vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/openrouter-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway.json", "title": "Beam 1.0 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-vercel-ai-gateway.json", "title": "SambaCloud vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/sambanova-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway.json", "title": "SiliconFlow vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway.json", "title": "Simplismart vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-vercel-ai-gateway.json", "title": "StepFun API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vercel-ai-gateway.json", "title": "SWE-2 Flash vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway.json", "title": "Together AI Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.json", "title": "Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api.json", "title": "Vercel AI Gateway vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-vercel-ai-gateway.json", "title": "Antseed vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/antseed-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway.json", "title": "Eden AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/litellm-vs-vercel-ai-gateway.json", "title": "LiteLLM vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/litellm-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-vercel-ai-gateway.json", "title": "Router.com (Ramp Router) vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-vercel-ai-gateway.json", "title": "RouterPlus vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/routerplus-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vercel-ai-gateway.json", "title": "Tencent Cloud TokenHub vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-vercel-ai-gateway.json", "title": "Prism Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-vercel-ai-gateway" } ], "panel": null, "scores": [ { "by": 39, "edge": "vercel-ai-gateway", "gemini-4-carbon": 40, "key": "reliability", "name": "Reliability", "vercel-ai-gateway": 79, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "edge": "gemini-4-carbon", "gemini-4-carbon": 85, "key": "schema", "name": "Schema \u0026 documentation", "vercel-ai-gateway": 74, "weight": 13 }, { "by": 10, "edge": "gemini-4-carbon", "gemini-4-carbon": 93, "key": "ergonomics", "name": "Agent ergonomics", "vercel-ai-gateway": 83, "weight": 13 }, { "by": 24, "edge": "vercel-ai-gateway", "gemini-4-carbon": 55, "key": "security", "name": "Security \u0026 auth", "vercel-ai-gateway": 79, "weight": 14 }, { "by": 0, "edge": "", "gemini-4-carbon": 20, "key": "payments", "name": "Payments \u0026 pricing", "vercel-ai-gateway": 20, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 4, "edge": "gemini-4-carbon", "gemini-4-carbon": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "vercel-ai-gateway": 79, "weight": 7 }, { "by": 1, "edge": "gemini-4-carbon", "gemini-4-carbon": 72, "key": "transparency", "name": "Transparency \u0026 trust", "vercel-ai-gateway": 71, "weight": 7 } ], "summary": "Vercel AI Gateway scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 2 of 7 scored categories. Gemini 4 Carbon leads on schema \u0026 documentation and agent ergonomics. 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.", "vercel-ai-gateway": "Token prices pass through with no markup, prompts are not stored by the gateway, and budgets, provider failover and per-request logs are built in. The free monthly credit needs a card on file, rate limits are not published as numbers, no SLA covers the API, and the contractual promise not to train on content applies to Enterprise subscriptions only." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway", "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.min.md" }, "markdown": "Vercel AI Gateway scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 2 of 7 scored categories. Gemini 4 Carbon leads on schema \u0026 documentation and agent ergonomics. 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- Vercel AI Gateway: grade B, 67.8/100, rank #305 of 1518. Markdown https://www.anchorterminal.com/tools/vercel-ai-gateway.md · JSON https://www.anchorterminal.com/api/v1/tools/vercel-ai-gateway.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- Schema \u0026 documentation, 85 against 74\n- Agent ergonomics, 93 against 83\n\nAlso in its favour:\n- No incidents deducted, where Vercel AI Gateway loses 3 points for them\n\nWatch for: Paid tier only, with no free tier to try it on\n\n### Vercel AI Gateway (B)\n\nGood for: Teams that want one key, one bill, budgets and failover in front of many model providers, especially on Vercel with OIDC.\n\nAhead on:\n- Reliability, 79 against 40\n- Security \u0026 auth, 79 against 55\n\nWatch for: The free monthly credit needs a valid payment method on the team, and its amount is not stated in the reviewed docs\n\n\n## Why the edge\n\n### Reliability: Vercel AI Gateway +39\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- Vercel AI Gateway (79): Hosted reading. AI Gateway is a component on www.vercel-status.com (20). The history feed, re-read on 1 November 2026, has 25 entries from 23 July to 23 October, so it covers the whole 90 days from 3 August. None names AI Gateway in its title or text. The Drains, Logs and Observability incidents (6, 17 and 20 August, 16 to 17 September, 10 October in Washington, which names delayed logs, metrics and traces in general, and 23 October) name no AI Gateway surface, and none reports requests failing. Component tags sit in the status API, which robots.txt disallows, so they were not used. A readable page that posts incidents, none touching the product, is a clean record, as vercel-connect's incidents were read from the same feed (30). The rate-limit page, re-read on 1 November, says it describes behaviour rather than fixed numbers. The paid tier has no gateway limit, and the free tier's per-model limits are not published (5 of 15). A 429 has a documented JSON body, some carry `retry-after`, the docs give backoff code and separate a 429 from a 402 budget rejection, and failed provider attempts are retried on other providers (14 of 15). The Enterprise SLA excludes the APIs and CLI, and no SLA naming AI Gateway was found (0). Generally available since 21 August 2025. Token Pass is early access and the Python SDK is in beta (10).\n\n### Security \u0026 auth: Vercel AI Gateway +24\n\n- Gemini 4 Carbon (55): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Carbon is on the paid tier only, and Google's terms say paid-tier content isn't used to improve products; AI Studio use under a Google AI Ultra subscription falls under terms we didn't read, so 15 of 20 (a judgement call; the platform's 10 is for its free tier). Abuse retention with no number, and new paid projects store requests by default since 26 October (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 15 + 5 + 15 + 5 = 55.\n- Vercel AI Gateway (79): Router, read on the model lines. AI Gateway API keys belong to a team, can be limited to one project and given an expiry and a budget, are deactivated when their creator leaves the team, and can be revoked without authentication by reporting a leaked key. Keys carry no per-model or read-only scope apart from the Token Pass key type. On Vercel, project OIDC tokens replace long-lived keys (24 of 30). Vercel says it does not train on prompts, and the AI Product Terms make that a warranty only for Enterprise subscriptions. Provider training is filtered only when `disallowPromptTraining` or ZDR is set, the filter does not apply to BYOK, and the terms say Stealth Model providers may train on inputs (12 of 20). The gateway does not keep prompt or response content. Provider ZDR is free per request on Pro and Enterprise and not available on Hobby, and BYOK keys are skipped under ZDR unless marked (12 of 15). Per-request logs record status, provider attempts, tokens, cost and authentication method, with routing details kept 30 days and Trace Drains and spend reports on paid plans (13 of 15). Valid security.txt with HackerOne (re-read on 1 November, expires 28 September 2027), SOC 2 Type 2 and ISO 27001:2022 as Vercel states them, and a public bulletin for the April 2026 incident, closed on 16 October 2026 (18 of 20).\n\n### Schema \u0026 documentation: Gemini 4 Carbon +11\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- Vercel AI Gateway (74): Router, scored on the API lines. Vercel's OpenAPI 3.0.3 document has AI Gateway management paths (budgets, routing rules, virtual model configs, routers) and `POST /api-keys`. It does not cover the inference routes on ai-gateway.vercel.sh or `/v1/models`, `/v1/credits`, `/v1/generation` and `/v1/report`, which follow the OpenAI and Anthropic formats and the REST reference page (12 of 25). Every docs page is served as Markdown, and vercel.com/llms.txt lists AI Gateway and the keyless model list (10). The docs say when to use AI Gateway, which API format suits which client, and what each control leaves out, such as BYOK spend outside budgets (16 of 20). `providerOptions.gateway` fields are documented in tables with types, and the model list names each model's supported parameters. The request bodies have no published schema of their own (9 of 15). cURL, TypeScript and Python examples on most pages, and error tables in the FAQ, the REST reference and the Token Pass pages. The Chat Completions error list omits 402 (13 of 15). Paths carry `/v1`, the changelog is dated, with 95 entries naming AI Gateway from 3 August to 30 October 2026, and `@ai-sdk/gateway` keeps a CHANGELOG. The changelog sitemap dates one AI Gateway entry to 25 March 2025, before the alpha (14 of 15).\n\n### Agent ergonomics: Gemini 4 Carbon +10\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- Vercel AI Gateway (83): Router, read on the model lines. Tool calling is documented on all six surfaces and 303 of 498 models carry the tool-use tag on 1 November, with behaviour depending on the model routed (16 of 20). Structured output is documented per surface and tagged on 278 models (13 of 15). `caching: 'auto'` adds Anthropic cache markers, `cache_ttl` asks for one-hour entries, `x-session-affinity` keeps a conversation on one provider, and cache-read prices are listed per model (14 of 15). 162 models list a context of one million tokens or more, a judgement call since a router has no default model (15). The SDK source has a `gateway-batch.ts` file, but no batch endpoint or batch discount was found in the docs (2 of 10). The AI SDK for TypeScript, the AI SDK for Python in beta, and the OpenAI and Anthropic SDKs with a changed base URL (10). Errors return `message` and `type`, an exceeded budget answers 402 apart from a 429, the SDK has ten typed `Gateway*Error` classes, and the FAQ maps each status to a fix (13 of 15).\n\n## Score by category\n\n| Category | Weight | Gemini 4 Carbon | Vercel AI Gateway | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 79 | Vercel AI Gateway +39 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 74 | Gemini 4 Carbon +11 |\n| Agent ergonomics | 13% (16.2 this run) | 93 | 83 | Gemini 4 Carbon +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 79 | Vercel AI Gateway +24 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 79 | Gemini 4 Carbon +4 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 71 | Gemini 4 Carbon +1 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **62.6 · B** | **67.8 · B** | |\n\n## Facts side by side\n\n| Fact | Gemini 4 Carbon | Vercel AI Gateway |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | Google | Vercel Inc. |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://ai-gateway.vercel.sh/v1` |\n| Transports | | HTTP |\n| Auth | API key | OAuth or 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 Vercel's Terms of Service and AI Product Terms, with Token Pass terms on its docs page. Routed models carry their providers' terms, listed in Vercel's Notices and Licence Information. The `@ai-sdk/gateway` provider is Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-10 | 2026-10-30 |\n| Terms last updated | 2026-04-28 | 2026-06-01 |\n| Privacy policy last updated | 2026-10-01 | 2026-06-01 |\n| Customer content may train models | yes | yes, with an opt-out |\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 | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | none | 29.6M npm/wk |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### Gemini 4 Carbon\n\nNo score change since it was listed.\n\n### Vercel AI Gateway\n\n- +1.0 on 1 November 2026: correction\n- +0.1 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**Vercel AI Gateway.** Token prices pass through with no markup, prompts are not stored by the gateway, and budgets, provider failover and per-request logs are built in. The free monthly credit needs a card on file, rate limits are not published as numbers, no SLA covers the API, and the contractual promise not to train on content applies to Enterprise subscriptions only.\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### Vercel AI Gateway\n\n1. Read `GET https://ai-gateway.vercel.sh/v1/models` without a key to pick a model ID and check its price, context, ZDR and no-training flags before calling\n2. Set `zeroDataRetention` or `disallowPromptTraining` to true in `providerOptions.gateway` on sensitive requests. Default routing ignores provider retention and training policies\n3. Treat a 429 as retryable and honour `retry-after` when present. A 402 with `quota_for_entity_exceeded` is a spent budget, so do not retry it\n4. On a Token Pass key, a 403 with `no_providers_available` means spent credit or a model outside the pass. Retry with a standard AI Gateway key, which bills credits\n5. Set `inferenceRegion` when data residency matters. The default `global` may run inference outside the user's jurisdiction\n\n## Questions\n\n### Which is better for AI agents, Gemini 4 Carbon or Vercel AI Gateway?\n\nVercel AI Gateway scores 67.8 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 2 of 7 scored categories. Gemini 4 Carbon leads on schema \u0026 documentation and agent ergonomics.\n\n### Do Gemini 4 Carbon and Vercel AI Gateway need an API key?\n\nGemini 4 Carbon needs an API key. Vercel AI Gateway takes an API key or an OAuth sign-in.\n\n### Can an agent call Gemini 4 Carbon and Vercel AI Gateway without installing anything?\n\nYes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Vercel AI Gateway at https://ai-gateway.vercel.sh/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-4-carbon\", \"b\": \"vercel-ai-gateway\"}`. From a terminal: `anchor compare gemini-4-carbon vercel-ai-gateway`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json and https://www.anchorterminal.com/api/v1/tools/vercel-ai-gateway.json\n\n## Other comparisons with Gemini 4 Carbon or Vercel AI Gateway\n\n- [Amazon Bedrock vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.md)\n- [Amazon Bedrock vs Vercel AI Gateway](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Claude API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- [Azure OpenAI in Foundry Models vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-carbon.md)\n- [Azure OpenAI in Foundry Models vs Vercel AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway.md)\n- [BlockRun.AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.md)\n- [BlockRun.AI vs Vercel AI Gateway](https://www.anchorterminal.com/compare/blockrun-ai-vs-vercel-ai-gateway.md)\n- [Cerebras Inference vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon.md)\n- [Cerebras Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/cerebras-inference-vs-vercel-ai-gateway.md)\n- [Claude Fable 5.2 vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-carbon.md)\n- [Claude Fable 5.2 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-vercel-ai-gateway.md)\n- [Claude Mythos 5.2 vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-carbon.md)\n- [Claude Mythos 5.2 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-vercel-ai-gateway.md)\n- [Cloudflare AI Gateway vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-carbon.md)\n- [Cloudflare AI Gateway vs Vercel AI Gateway](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vercel-ai-gateway.md)\n- [Cloudflare Workers AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-carbon.md)\n- [Cloudflare Workers AI vs Vercel AI Gateway](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vercel-ai-gateway.md)\n- [Cohere Chat API (Command models) vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.md)\n- [Cohere Chat API (Command models) vs Vercel AI Gateway](https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway.md)\n- [DeepInfra vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.md)\n- 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RouterPlus](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus.md)\n- [Gemini 4 Carbon vs SambaCloud](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.md)\n- [Gemini 4 Carbon vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow.md)\n- [Gemini 4 Carbon vs Simplismart](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.md)\n- [Gemini 4 Carbon vs StepFun API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.md)\n- [Gemini 4 Carbon vs SWE-2 Flash](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.md)\n- [Gemini 4 Carbon vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.md)\n- [Gemini 4 Carbon vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.md)\n- [Gemini 4 Carbon vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.md)\n- [Gemini 4 Carbon vs xAI API (Grok)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api.md)\n- [Gemini Developer API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/gemini-api-vs-vercel-ai-gateway.md)\n- [GroqCloud vs Vercel AI Gateway](https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway.md)\n- [Inkling 2 Small vs Vercel AI Gateway](https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway.md)\n- [Jais 3 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.md)\n- [Meta Model API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.md)\n- [MiniMax API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway.md)\n- [Mistral AI API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/mistral-api-vs-vercel-ai-gateway.md)\n- 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Gateway](https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway.md)\n- [Hugging Face Inference Providers vs Vercel AI Gateway](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.md)\n- [LiteLLM vs Vercel AI Gateway](https://www.anchorterminal.com/compare/litellm-vs-vercel-ai-gateway.md)\n- [Router.com (Ramp Router) vs Vercel AI Gateway](https://www.anchorterminal.com/compare/ramp-router-vs-vercel-ai-gateway.md)\n- [RouterPlus vs Vercel AI Gateway](https://www.anchorterminal.com/compare/routerplus-vs-vercel-ai-gateway.md)\n- [Tencent Cloud TokenHub vs Vercel AI Gateway](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vercel-ai-gateway.md)\n- [Prism Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/prism-inference-vs-vercel-ai-gateway.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 Vercel AI Gateway", "url": "" } ], "description": "Vercel AI Gateway scores 67.8 (B) to Gemini 4 Carbon's 62.6 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Gemini 4 Carbon B 62.6", "Vercel AI Gateway B 67.8", "scores" ], "h1": "Gemini 4 Carbon vs Vercel AI Gateway", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/gemini-4-carbon-vs-vercel-ai-gateway", "published": "2026-10-01", "section": "tools", "title": "Gemini 4 Carbon vs Vercel AI Gateway for AI agents (2026)", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway" }, "tokens": { "markdown": 6700, "slim": 930 }, "version": 1 }