{ "data": { "a": { "slug": "gemini-4-carbon", "name": "Gemini 4 Carbon", "vendor": "Google", "vendorUrl": "https://ai.google.dev", "kind": "model", "category": "inference", "summary": "Gemini 4 Carbon is Google's strongest Gemini model, for long agentic coding, cybersecurity and research work, on the paid tier of the Gemini API with a 1,048,576-token limit shared between input and output.", "url": "https://www.anchorterminal.com/tools/gemini-4-carbon", "markdownUrl": "https://www.anchorterminal.com/tools/gemini-4-carbon.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gemini-4-carbon.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json", "dns": "gemini-4-carbon.grade.anchorterminal.com", "license": "Closed model, used through the Gemini API and Google's apps under Google's terms", "transports": [], "remoteUrl": "https://generativelanguage.googleapis.com/v1beta", "packages": [], "auth": "api-key", "authNotes": "An `x-goog-api-key` from AI Studio on a project with billing, since Carbon is on the paid tier only, per the Gemini API listing and Google's developer post. Google AI Ultra subscribers can also use it in AI Studio and Antigravity. The `gemini-4-carbon-cyber-permissive` variant needs a project approved through Google's Fairwind Program.", "pricing": "usage", "pricingNotes": "Google's announcement gives an introductory $2 per million input tokens and $10 output, cached input 95% off, then $4 and $20, with no end date for the introduction. Paid tier only, no free tier. Every processed token is billed, thinking included (checked 2026-11-10).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Paid use needs billing on a Cloud project, per the Gemini API listing (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/guides/gemini-4-carbon", "llmsTxt": "https://ai.google.dev/gemini-api/docs/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "multimodal", "reasoning", "long-context", "tool-calling", "usage-priced", "card-required", "closed-source", "llms-txt", "new" ], "lastRelease": "2026-11-10", "graded": true, "anchor": { "graded": true, "score": 62.6, "grade": "B", "agentReady": false, "rank": 555, "ranked": true, "rankOf": 1518, "categoryRank": 22, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 93, "maintenance": 83, "payments": 20, "reliability": 40, "schema": 85, "security": 55, "transparency": 72 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-10" }, "negative": 0, "verdict": "Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.", "bestFor": "Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.", "strengths": [ "Introductory price of $2 input and $10 output per million tokens, with cached input 95% off", "1,048,576 tokens shared between input and output, with long decodes for big outputs", "Function calling, structured output, Google Search grounding and background execution", "Thinking levels LOW, MEDIUM (default) and HIGH, and implicit caching on by default", "The same API, keys and SDKs as Gemini 4 Argon, so switching is a model ID" ], "weaknesses": [ "Paid tier only, with no free tier to try it on", "temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400", "No explicit context caching, and prefilled model turns aren't accepted", "The price goes to $4 and $20 after an introduction with no end date given", "Benchmark figures are Google's own, and the launch stage isn't stated" ], "agentNotes": [ "Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-carbon and an x-goog-api-key on a billed project", "Set thinking_level (LOW, MEDIUM or HIGH) instead of thinking_budget, and don't send temperature, top_p or top_k", "Count output against the same 1,048,576-token limit as the input, and set max_output_tokens for long answers", "Put static prompt content first so implicit caching applies; explicit caches aren't supported", "Use gemini-4-argon for most coding and knowledge work, and Carbon for the hardest long tasks, as Google suggests" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 62.6 } ], "editorialScores": { "ergonomics": 93, "maintenance": 83, "payments": 20, "reliability": 40, "schema": 85, "security": 55, "transparency": 55 }, "provenanceScore": 89, "checked": { "categories": { "ergonomics": "2026-11-10", "maintenance": "2026-11-10", "payments": "2026-11-10", "reliability": "2026-11-10", "schema": "2026-11-10", "security": "2026-11-10", "transparency": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-4-carbon:generateContent\" \\\n -H \"x-goog-api-key: $GEMINI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"contents\":[{\"parts\":[{\"text\":\"hello\"}]}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/gemini-4-carbon" }, "sameCompany": [ "vertex-ai", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-memory-bank", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "sameModel": [ "gemini-api" ], "area": "models", "unitPrices": [ { "item": "Gemini 4 Carbon input", "unit": "1m-tokens", "usd": 2, "note": "Introductory; $4 after, date not given" }, { "item": "Gemini 4 Carbon cached input", "unit": "1m-tokens", "usd": 0.1, "note": "95% off input" }, { "item": "Gemini 4 Carbon output", "unit": "1m-tokens", "usd": 10, "note": "Introductory; $20 after" } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.", "endpointOnVendorDomain": true, "terms": "https://ai.google.dev/gemini-api/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://aistudio.google.com/status", "changelog": "https://ai.google.dev/gemini-api/docs/changelog", "securityTxt": "valid", "checked": "2026-11-10", "score": 89 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gemini-4-carbon.json", "live": { "slug": "gemini-4-carbon", "probe": { "target": "https://generativelanguage.googleapis.com/v1beta", "method": "get", "lastAt": "2026-11-10T23:47:03.904361517Z", "lastOk": true, "lastStatus": 404, "lastMs": 35, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 41, "p95ms24h": 130, "samples24h": 63, "samples30d": 63, "days": [ { "date": "2026-11-10", "probes": 63, "ok": 63 } ], "since": "2026-11-10T17:42:25.910455739Z" }, "vendorStatus": { "page": "https://aistudio.google.com/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-10T23:00:42.593790699Z" }, "updatedAt": "2026-11-10T23:47:03.904361517Z" }, "streak": { "days": 0, "from": "2026-11-10", "sinceWatching": true, "best": 0 } }, "answer": "SambaCloud scores 64.9 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.", "b": { "slug": "sambanova", "name": "SambaCloud", "vendor": "SambaNova Systems, Inc.", "vendorUrl": "https://sambanova.ai", "kind": "model", "category": "inference", "summary": "SambaCloud is SambaNova's hosted inference API for open-weight models running on its own RDU processors. It answers OpenAI-style chat, completions and Responses calls and Anthropic-style Messages calls, with Python and TypeScript SDKs.", "url": "https://www.anchorterminal.com/tools/sambanova", "markdownUrl": "https://www.anchorterminal.com/tools/sambanova.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/sambanova.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/sambanova.json", "dns": "sambanova.grade.anchorterminal.com", "repo": "https://github.com/sambanova/sambanova-python", "license": "Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://api.sambanova.ai/v1", "packages": [ { "registry": "pypi", "name": "sambanova" }, { "registry": "npm", "name": "sambanova" } ], "auth": "api-key", "authNotes": "Self-serve Bearer key from the SambaCloud console at https://cloud.sambanova.ai/apis after a browser sign-up. The Messages routes also take the same key in `x-api-key`. Up to 25 keys per user, shown once, with no scopes.", "pricing": "freemium", "pricingNotes": "Free tier with no payment method, at 20 requests a minute, 20 requests a day and 200,000 tokens a day per model. Linking a card moves the account to the Developer tier, billed per token through Stripe, from $0.22 in and $0.59 out per 1M tokens on gpt-oss-120b (https://cloud.sambanova.ai/plans/pricing, checked 2026-10-08).", "priceSummary": "from $0.22 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI document or the pricing page (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 2, "npmWeekly": 76, "pypiWeekly": 6129, "asOf": "2026-10-08" }, "docsUrl": "https://docs.sambanova.ai/docs/en/get-started/overview", "rateLimitsUrl": "https://docs.sambanova.ai/docs/en/models/rate-limits", "llmsTxt": "https://docs.sambanova.ai/docs/llms.txt", "openapi": "https://raw.githubusercontent.com/sambanova/sambanova-inference-api-spec/refs/heads/main/openapi.documented.json", "capabilities": [ "inference.llm", "inference.open-weights", "inference.fast" ], "tags": [ "hosted", "model", "open-weights", "free-tier", "no-card", "openapi", "llms-txt", "openai-compatible", "anthropic-compatible", "python", "typescript", "status-page", "soc2" ], "lastRelease": "2026-10-27", "graded": true, "anchor": { "graded": true, "score": 64.9, "grade": "B", "agentReady": false, "rank": 448, "ranked": true, "rankOf": 1518, "categoryRank": 20, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 77, "payments": 40, "reliability": 85, "schema": 81, "security": 61, "transparency": 73 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -5, "negativeNotes": [ "2026-10-08. The models and rate-limit pages listed `MiniMax-M2.7` as a production model a week after its 1 October removal from SambaCloud, and the July 2026 release notes say `Mistral-Large-3-675B-Instruct-2512` was promoted to production. Neither was on the pricing page or in `/v1/models`, and the deprecations page has no entry for Mistral Large 3. Two points, since a keyed call was not made to confirm the ids fail; the docs couldn't be re-read on 1 November (https://docs.sambanova.ai/docs/en/models/sambacloud-models, https://api.sambanova.ai/v1/models).", "2026-10-27, -3. Python SDK 1.14.0 and TypeScript SDK 1.11.0, 1.x minor releases filed under `Features`, removed the documented `do_sample` parameter from the create methods and deleted the audio transcription and translation streaming types, so existing Python callers passing either now get a TypeError. Neither changelog, README nor commit gives notice, and 1.13.0 carried no deprecation warning. Read as box-api's unannounced breaking changes in minor SDK releases, the two packages folded into one term. The docs' release notes and deprecations page couldn't be read on 1 November (bot check); a dated notice there would lift it (https://github.com/sambanova/sambanova-python/commit/8b7cc8b44a82726ff1e759c65f4541adbebb464e, https://github.com/sambanova/sambanova-typescript/commit/128023023eb6ec3b63cabe1c45f0941eb9ba4b8d)" ], "verdict": "Per-token prices are readable without a login, a free tier needs no card, and no incident has been posted since 25 June 2026. A Data Processing Addendum now names 24 sub-processors. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the product page's privacy claim contradicts the terms.", "bestFor": "Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.", "strengths": [ "Public OpenAPI 3.1.1 document for all 10 operations, plus `llms.txt` and a Markdown copy of every docs page", "Per-token prices for every model on a pricing page that needs no login, and `GET /v1/models` answered without a key on 8 October 2026", "Free tier with no payment method at 20 requests a minute, 20 requests a day and 200,000 tokens a day per model", "One key works with the OpenAI client, the Anthropic client (`/v1/messages`, `x-api-key`) and SambaNova's own SDKs", "Status page with a component per model and no incident posted since 25 June 2026" ], "weaknesses": [ "Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026", "The docs listed `MiniMax-M2.7` as a production model on 8 October 2026, a week after it left SambaCloud", "`strict: true` on a JSON schema is accepted and has no effect, and the July 2026 notes record failing structured output on DeepSeek-V3.2", "Keys carry no scopes or project limits, and no key rotation guidance was found in the reviewed documentation", "The privacy policy dates from May 2023, and the product page says prompts are never collected while the DPA keeps them up to 30 days" ], "agentNotes": [ "Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs and status page have named models the API no longer serves", "Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model", "Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model", "Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing", "Drop `do_sample` before moving to Python SDK 1.14.0 or TypeScript 1.11.0. Those releases removed it" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 64.9 } ], "editorialScores": { "ergonomics": 67, "maintenance": 77, "payments": 40, "reliability": 85, "schema": 81, "security": 61, "transparency": 63 }, "provenanceScore": 82, "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": "pip install sambanova # or: npm install sambanova", "http": "curl https://api.sambanova.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $SAMBANOVA_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"gpt-oss-120b\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/sambanova" }, "area": "models", "provenance": { "legalEntity": "SambaNova Systems, Inc.", "domain": "sambanova.ai", "domainRegistered": "2017-12-18", "endpointOnVendorDomain": true, "terms": "https://sambanova.ai/cloud-end-user-license-agreement", "privacy": "https://sambanova.ai/privacy-policy", "statusPage": "https://status.sambanova.ai", "changelog": "https://docs.sambanova.ai/docs/en/release-notes/sambacloud", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "The SambaCloud Terms of Service name SambaNova Systems, Inc., a Delaware corporation at 2460 N. First St, Suite #100, San Jose, CA 95131, and define the Service as the SambaCloud platform. The page carries no date. The legal index says it was last updated on 5 February 2026.", "The privacy policy is the company's only one. Its last revision is dated 27 May 2023, it covers the website, communications and related services, and it does not name SambaCloud or API inputs.", "A Data Processing Addendum (undated, with a sub-processor list) is linked from https://sambanova.ai/legal-agreements on 1 November 2026. No SLA or acceptable use policy is linked.", "https://sambanova.ai/.well-known/security.txt returns 404 (1 November 2026).", "RDAP for sambanova.ai gives a registration date of 2017-12-18.", "The API answers at api.sambanova.ai and the console at cloud.sambanova.ai.", "docs.sambanova.ai, which holds the changelog, answered robots.txt with a bot check on 1 November 2026; the changelog URL is kept from 8 October." ], "score": 82 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/sambanova.json", "live": { "slug": "sambanova", "probe": { "target": "https://api.sambanova.ai/v1", "method": "get", "lastAt": "2026-11-10T23:47:24.426682191Z", "lastOk": true, "lastStatus": 405, "lastMs": 382, "authRequired": false, "uptime24h": 100, "uptime30d": 99.66, "p50ms24h": 428, "p95ms24h": 693, "samples24h": 244, "samples30d": 7904, "days": [ { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 244 }, { "date": "2026-10-13", "probes": 248, "ok": 247 }, { "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": 252 }, { "date": "2026-10-18", "probes": 256, "ok": 254 }, { "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": 250 }, { "date": "2026-10-25", "probes": 250, "ok": 249 }, { "date": "2026-10-26", "probes": 252, "ok": 251 }, { "date": "2026-10-27", "probes": 249, "ok": 248 }, { "date": "2026-10-28", "probes": 250, "ok": 249 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 249, "ok": 247 }, { "date": "2026-10-31", "probes": 251, "ok": 246 }, { "date": "2026-11-01", "probes": 249, "ok": 248 }, { "date": "2026-11-02", "probes": 250, "ok": 247 }, { "date": "2026-11-03", "probes": 248, "ok": 247 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 238 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 243, "ok": 243 }, { "date": "2026-11-10", "probes": 242, "ok": 242 } ], "since": "2026-10-09T00:00:00Z" }, "vendorStatus": { "page": "https://status.sambanova.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-10T23:37:30.634444249Z" }, "versions": [ { "registry": "github", "name": "sambanova/sambanova-python", "version": "v1.14.0", "released": "2026-10-27", "seenAt": "2026-11-10T04:15:56.437680062Z" }, { "registry": "npm", "name": "sambanova", "version": "1.11.0", "seenAt": "2026-11-10T04:15:54.68395763Z" }, { "registry": "pypi", "name": "sambanova", "version": "1.14.0", "released": "2026-10-27", "seenAt": "2026-11-10T04:15:54.492912655Z" } ], "githubStars": 2, "npmWeekly": 181, "pypiWeekly": 8081, "securityTxt": { "url": "https://sambanova.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:07:46.293278227Z" }, "llmsTxt": { "url": "https://docs.sambanova.ai/docs/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:44:32.676028341Z" }, "domain": { "domain": "sambanova.ai", "registered": "2017-12-18", "source": "https://rdap.identitydigital.services/rdap/domain/sambanova.ai", "checkedAt": "2026-11-08T14:52:17.293765489Z" }, "pages": [ { "url": "https://docs.sambanova.ai/docs/en/release-notes/sambacloud", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:18:34.708766362Z", "changedAt": "2026-11-07T14:07:53.11787435Z", "fingerprint": "639e478e95cf" }, { "url": "https://docs.sambanova.ai/docs/en/models/deprecations", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-10T16:18:32.198329995Z", "changedAt": "2026-11-07T14:07:50.629389308Z", "fingerprint": "c32bdc3792a4" }, { "url": "https://cloud.sambanova.ai/plans/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-10T16:11:50.466878466Z", "changedAt": "2026-11-10T16:11:50.466878466Z", "fingerprint": "f590e375a721" }, { "url": "https://sambanova.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-10T16:30:11.699508189Z", "changedAt": "2026-10-31T06:20:00.89176957Z", "fingerprint": "c3c533d959fb" }, { "url": "https://sambanova.ai/cloud-end-user-license-agreement", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:30:09.538539167Z", "changedAt": "2026-10-31T06:19:58.778199001Z", "fingerprint": "3a3a2cdc3ec3" } ], "github": { "repo": "sambanova/sambanova-python", "checkedAt": "2026-11-09T10:59:07.519511812Z", "stars": 2, "archived": false, "issuesEnabled": false, "pushedAt": "2026-10-27T18:08:31Z", "openIssues": 0, "openPRs": 0, "issuesOpened90d": 0, "issuesClosed90d": 0, "prsMerged90d": 5, "ci": { "branch": "main", "runs": 50, "success": 28, "failure": 0, "other": 22, "latest": "skipped", "latestAt": "2026-10-27T18:08:25Z" } }, "updatedAt": "2026-11-10T23:47:24.426682191Z" }, "streak": { "days": 32, "from": "2026-10-09", "sinceWatching": true, "last": { "kind": "shutdown", "date": "2026-10-01", "what": "`MiniMax-M2.7` leaves SambaCloud and stays on SambaStack and SambaManaged only. Move to `MiniMax-M3`", "source": "https://docs.sambanova.ai/docs/en/models/deprecations" }, "best": 32 } }, "edges": [ { "by": 45, "category": "reliability", "leads": "sambanova", "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. Status page at status.sambanova.ai on Statuspage, with components for the API gateway, the Playground and each model, read from the page itself on 1 November (20). Its history.atom feed, read on 1 November (the 8 October reading came from the /api/ path, which robots.txt disallows, and is struck), has nothing newer than an 8-minute Playground login fault on 25 June 2026, so nothing is posted for the window from 3 August (30). Limits published per model and tier, 20 requests a minute and 20 a day on the free tier, 60 and 12,000 on the Developer tier, per the 8 October check, not re-read on 1 November (15). `x-ratelimit-*` headers on every response, the error table says to retry `queue_full` after a delay, and the SDKs retry 429 and server errors twice with backoff, per the 8 October check. No `Retry-After` header was found in the docs or the OpenAPI document (10 of 15). No SLA found on the legal page, re-read on 1 November, or in the terms (0). Three production models are generally available, the rest previews, per the 8 October check (10). 20+30+15+10+0+10 = 85." }, "scores": { "a": 40, "b": 85 } }, { "by": 26, "category": "ergonomics", "leads": "gemini-4-carbon", "name": "Agent ergonomics", "reasons": { "a": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output (13 of 15). Implicit caching with durable caching on by default, cached input 95% off, explicit caches not supported, per the Cloud guide read on 10 November (15). 1,048,576 tokens shared between input and output (15). Batch at half price on the platform (10). Python and JavaScript SDKs (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 15 + 15 + 10 + 10 + 10 = 93.", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `tool_choice` to force a function, on six listed models, and a July 2026 fix for tool calls that were buffered when streaming (17 of 20). `json_object` and `json_schema` output, best effort only, with a known failure on DeepSeek-V3.2 recorded in July 2026 (8 of 15). Automatic prompt caching on the MiniMax models only, with cached input on MiniMax-M3.1-Flash at a tenth of the input price on the 1 November pricing page, a 4,096-token minimum and no guaranteed persistence (10 of 15). 131,072-token context on four of six models, 1M on the MiniMax-M3 preview, and output capped at 7,168 tokens on DeepSeek and 3,072 on Llama 3.3 70B (8 of 15). No batch API found in the docs index or the OpenAPI document (0 of 10). Official SDKs for Python and TypeScript, and the OpenAI and Anthropic clients work with a changed base URL (10). Errors carry `type`, `param`, `code` and `request_id` (14 of 15)." }, "scores": { "a": 93, "b": 67 } }, { "by": 20, "category": "payments", "leads": "sambanova", "name": "Payments \u0026 pricing", "reasons": { "a": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Introductory prices published in Google's 28 October announcement without a login, $2 and $10, then $4 and $20; the Gemini API pricing page as read on 10 November showed no Carbon row, so the figures rest on the announcement (20). No free tier: Google's developer post puts Carbon on the paid tier (0). A Google account and AI Studio for a key (0). 0 + 20 + 0 + 0 = 20.", "b": "No machine payment protocol (0). Per-token prices on the pricing page, read without a login on 1 November, such as gpt-oss-120b at $0.22 in and $0.59 out per 1M tokens (20). Free tier with no payment method, per the 8 October check (20). A person signs up in the console to get a key (0)." }, "scores": { "a": 20, "b": 40 } }, { "by": 6, "category": "security", "leads": "sambanova", "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": "Model reading. Bearer keys from the console, up to 25 per user and shown once. No scopes, project limits or rotation guidance were found, and the key travels in a header, never in the URL (18 of 30). The terms let SambaNova access, store and process Customer Content solely to supply the service and for no other purposes, which rules out training without naming it (18 of 20). The DPA's Annex I, read on 1 November, keeps prompts, inputs and completions no more than 30 days for security, fraud and abuse monitoring. No zero-retention option was found in the pages read, and the product page says SambaCloud never sees or collects prompts, against that retention and terms that grant a right to store content and to use query logs (10 of 15, between deepseek-api's 5 and siliconflow's 6 with no period stated and the 15 groq, mistral-api and xai-api take for 30 days with a zero-retention route). The console has a Usage page. No request logs or audit log were found in the docs (5 of 15). The trust centre states SOC 2 Type 2 and ISO 27001. No security.txt, disclosure policy or bug bounty was found, and the SDK's SECURITY.md sends service reports to a general address (10 of 20)." }, "scores": { "a": 55, "b": 61 } }, { "by": 6, "category": "maintenance", "leads": "gemini-4-carbon", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released to developers on 10 November 2026, with the platform's changelog (30). Deprecations with earliest dates and no stated minimum notice (4 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 4 + 4 + 15 + 5 + 15 + 10 = 83.", "b": "Model reading. The OpenAPI document and both SDKs (Python 1.14.0, TypeScript 1.11.0) were updated on 27 October 2026, adding `MiniMax-M3.1-Flash`, which is on the pricing page on 1 November (30). Production models get a notice of at least two to three weeks. The recorded removals to June had 14 days or less, and MiniMax-M2.7's removal from SambaCloud on 1 October was announced on 1 September (30 days), per the 27 October read of the deprecations page (5 of 12). One removal in the window from 3 August (MiniMax-M2.7) after 13 model ids left between 9 March and 9 June 2026 (4 of 8). The SambaCloud release notes stopped at 7 July 2026 on 8 October and couldn't be re-read. The community forum had staff replies, per the 8 October check (10 of 15). The Python SDK repository holds release pull requests only, so replies could not be judged (5 of 10). Python 1.14.0 and TypeScript 1.11.0, both 27 October 2026 (15). CI, release-please, a lock file and gitleaks scanning (8 of 10). 30+5+4+10+5+15+8 = 77." }, "scores": { "a": 83, "b": 77 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Google", "b": "SambaNova Systems, Inc.", "name": "Vendor" }, { "a": "https://generativelanguage.googleapis.com/v1beta", "b": "https://api.sambanova.ai/v1", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "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 SambaCloud Terms of Service. The SDKs and the OpenAPI document are 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": "2026-10-27", "name": "Last release" }, { "a": "2026-04-28", "b": "no date given", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "2023-05-27", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2 stars, 76 npm/wk, 6.1k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "SambaCloud scores 64.9 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.", "question": "Which is better for AI agents, Gemini 4 Carbon or SambaCloud?" }, { "answer": "Both need an API key.", "question": "Do Gemini 4 Carbon and SambaCloud need an API key?" }, { "answer": "Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and SambaCloud at https://api.sambanova.ai/v1.", "question": "Can an agent call Gemini 4 Carbon and SambaCloud without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Agent ergonomics, 93 against 67", "Maintenance \u0026 community, 83 against 77" ], "also": [ "No incidents deducted, where SambaCloud loses 5 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, 85 against 40", "Security \u0026 auth, 61 against 55", "Payments \u0026 pricing, 40 against 20" ], "also": [ "Free to start without a card" ], "goodFor": "Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.", "slug": "sambanova", "watchFor": "Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026" } ], "history": { "gemini-4-carbon": null, "sambanova": [ { "causes": [ "evidence", "event" ], "date": "2026-11-01", "delta": -1.5, "from": 66.4, "fromGrade": "B", "to": 64.9, "toGrade": "B" }, { "causes": [ "correction" ], "date": "2026-10-28", "delta": -0.1, "from": 66.5, "fromGrade": "B", "to": 66.4, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 66.4, "fromGrade": "B", "to": 66.5, "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": 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"https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.json", "title": "Gemini 4 Carbon vs Simplismart", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.json", "title": "Gemini 4 Carbon vs StepFun API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.json", "title": "Gemini 4 Carbon vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.json", "title": "Gemini 4 Carbon vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.json", "title": "Gemini 4 Carbon vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.json", "title": "Gemini 4 Carbon vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.json", "title": "Gemini 4 Carbon vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api.json", "title": "Gemini 4 Carbon vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.json", "title": "Gemini Developer API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-sambanova.json", "title": "GroqCloud vs SambaCloud", "url": "https://www.anchorterminal.com/compare/groq-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova.json", "title": "Hugging Face Inference Providers vs SambaCloud", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sambanova.json", "title": "Inkling 2 Small vs SambaCloud", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-sambanova.json", "title": "Jais 3 vs SambaCloud", "url": "https://www.anchorterminal.com/compare/jais-3-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json", "title": "Meta Model API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-sambanova.json", "title": "MiniMax API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.json", "title": "Mistral AI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-sambanova.json", "title": "Muse Ember vs SambaCloud", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.json", "title": "Muse Spark Open vs SambaCloud", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.json", "title": "Novita AI vs SambaCloud", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova.json", "title": "OpenAI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-sambanova.json", "title": "OpenRouter vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openrouter-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-sambanova.json", "title": "Router.com (Ramp Router) vs SambaCloud", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.json", "title": "Beam 1.0 vs SambaCloud", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-sambanova.json", "title": "RouterPlus vs SambaCloud", "url": "https://www.anchorterminal.com/compare/routerplus-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.json", "title": "SambaCloud vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-simplismart.json", "title": "SambaCloud vs Simplismart", "url": "https://www.anchorterminal.com/compare/sambanova-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api.json", "title": "SambaCloud vs StepFun API", "url": "https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-swe-2-flash.json", "title": "SambaCloud vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/sambanova-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-tencent-tokenhub.json", "title": "SambaCloud vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/sambanova-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-together-inference.json", "title": "SambaCloud vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/sambanova-vs-together-inference" }, { "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/sambanova-vs-vertex-ai.json", "title": "SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api.json", "title": "SambaCloud vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-sambanova.json", "title": "Nemotron 3.5 Super VL vs SambaCloud", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.json", "title": "Prism Inference vs SambaCloud", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-sambanova" } ], "panel": null, "scores": [ { "by": 45, "edge": "sambanova", "gemini-4-carbon": 40, "key": "reliability", "name": "Reliability", "sambanova": 85, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 4, "edge": "gemini-4-carbon", "gemini-4-carbon": 85, "key": "schema", "name": "Schema \u0026 documentation", "sambanova": 81, "weight": 13 }, { "by": 26, "edge": "gemini-4-carbon", "gemini-4-carbon": 93, "key": "ergonomics", "name": "Agent ergonomics", "sambanova": 67, "weight": 13 }, { "by": 6, "edge": "sambanova", "gemini-4-carbon": 55, "key": "security", "name": "Security \u0026 auth", "sambanova": 61, "weight": 14 }, { "by": 20, "edge": "sambanova", "gemini-4-carbon": 20, "key": "payments", "name": "Payments \u0026 pricing", "sambanova": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 6, "edge": "gemini-4-carbon", "gemini-4-carbon": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "sambanova": 77, "weight": 7 }, { "by": 1, "edge": "sambanova", "gemini-4-carbon": 72, "key": "transparency", "name": "Transparency \u0026 trust", "sambanova": 73, "weight": 7 } ], "summary": "SambaCloud scores 64.9 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "gemini-4-carbon": "Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.", "sambanova": "Per-token prices are readable without a login, a free tier needs no card, and no incident has been posted since 25 June 2026. A Data Processing Addendum now names 24 sub-processors. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the product page's privacy claim contradicts the terms." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova", "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.min.md" }, "markdown": "SambaCloud scores 64.9 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community. Both do llm inference.\n\n- Gemini 4 Carbon: grade B, 62.6/100, rank #555 of 1518. Markdown https://www.anchorterminal.com/tools/gemini-4-carbon.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json\n- SambaCloud: grade B, 64.9/100, rank #448 of 1518. Markdown https://www.anchorterminal.com/tools/sambanova.md · JSON https://www.anchorterminal.com/api/v1/tools/sambanova.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 1000 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Gemini 4 Carbon (B)\n\nGood for: Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.\n\nAhead on:\n- Agent ergonomics, 93 against 67\n- Maintenance \u0026 community, 83 against 77\n\nAlso in its favour:\n- No incidents deducted, where SambaCloud loses 5 points for them\n\nWatch for: Paid tier only, with no free tier to try it on\n\n### SambaCloud (B)\n\nGood for: Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.\n\nAhead on:\n- Reliability, 85 against 40\n- Security \u0026 auth, 61 against 55\n- Payments \u0026 pricing, 40 against 20\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026\n\n\n## Why the edge\n\n### Reliability: SambaCloud +45\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- SambaCloud (85): Hosted reading. Status page at status.sambanova.ai on Statuspage, with components for the API gateway, the Playground and each model, read from the page itself on 1 November (20). Its history.atom feed, read on 1 November (the 8 October reading came from the /api/ path, which robots.txt disallows, and is struck), has nothing newer than an 8-minute Playground login fault on 25 June 2026, so nothing is posted for the window from 3 August (30). Limits published per model and tier, 20 requests a minute and 20 a day on the free tier, 60 and 12,000 on the Developer tier, per the 8 October check, not re-read on 1 November (15). `x-ratelimit-*` headers on every response, the error table says to retry `queue_full` after a delay, and the SDKs retry 429 and server errors twice with backoff, per the 8 October check. No `Retry-After` header was found in the docs or the OpenAPI document (10 of 15). No SLA found on the legal page, re-read on 1 November, or in the terms (0). Three production models are generally available, the rest previews, per the 8 October check (10). 20+30+15+10+0+10 = 85.\n\n### Agent ergonomics: Gemini 4 Carbon +26\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- SambaCloud (67): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `tool_choice` to force a function, on six listed models, and a July 2026 fix for tool calls that were buffered when streaming (17 of 20). `json_object` and `json_schema` output, best effort only, with a known failure on DeepSeek-V3.2 recorded in July 2026 (8 of 15). Automatic prompt caching on the MiniMax models only, with cached input on MiniMax-M3.1-Flash at a tenth of the input price on the 1 November pricing page, a 4,096-token minimum and no guaranteed persistence (10 of 15). 131,072-token context on four of six models, 1M on the MiniMax-M3 preview, and output capped at 7,168 tokens on DeepSeek and 3,072 on Llama 3.3 70B (8 of 15). No batch API found in the docs index or the OpenAPI document (0 of 10). Official SDKs for Python and TypeScript, and the OpenAI and Anthropic clients work with a changed base URL (10). Errors carry `type`, `param`, `code` and `request_id` (14 of 15).\n\n### Payments \u0026 pricing: SambaCloud +20\n\n- Gemini 4 Carbon (20): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Introductory prices published in Google's 28 October announcement without a login, $2 and $10, then $4 and $20; the Gemini API pricing page as read on 10 November showed no Carbon row, so the figures rest on the announcement (20). No free tier: Google's developer post puts Carbon on the paid tier (0). A Google account and AI Studio for a key (0). 0 + 20 + 0 + 0 = 20.\n- SambaCloud (40): No machine payment protocol (0). Per-token prices on the pricing page, read without a login on 1 November, such as gpt-oss-120b at $0.22 in and $0.59 out per 1M tokens (20). Free tier with no payment method, per the 8 October check (20). A person signs up in the console to get a key (0).\n\n### Security \u0026 auth: SambaCloud +6\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- SambaCloud (61): Model reading. Bearer keys from the console, up to 25 per user and shown once. No scopes, project limits or rotation guidance were found, and the key travels in a header, never in the URL (18 of 30). The terms let SambaNova access, store and process Customer Content solely to supply the service and for no other purposes, which rules out training without naming it (18 of 20). The DPA's Annex I, read on 1 November, keeps prompts, inputs and completions no more than 30 days for security, fraud and abuse monitoring. No zero-retention option was found in the pages read, and the product page says SambaCloud never sees or collects prompts, against that retention and terms that grant a right to store content and to use query logs (10 of 15, between deepseek-api's 5 and siliconflow's 6 with no period stated and the 15 groq, mistral-api and xai-api take for 30 days with a zero-retention route). The console has a Usage page. No request logs or audit log were found in the docs (5 of 15). The trust centre states SOC 2 Type 2 and ISO 27001. No security.txt, disclosure policy or bug bounty was found, and the SDK's SECURITY.md sends service reports to a general address (10 of 20).\n\n### Maintenance \u0026 community: Gemini 4 Carbon +6\n\n- Gemini 4 Carbon (83): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released to developers on 10 November 2026, with the platform's changelog (30). Deprecations with earliest dates and no stated minimum notice (4 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 4 + 4 + 15 + 5 + 15 + 10 = 83.\n- SambaCloud (77): Model reading. The OpenAPI document and both SDKs (Python 1.14.0, TypeScript 1.11.0) were updated on 27 October 2026, adding `MiniMax-M3.1-Flash`, which is on the pricing page on 1 November (30). Production models get a notice of at least two to three weeks. The recorded removals to June had 14 days or less, and MiniMax-M2.7's removal from SambaCloud on 1 October was announced on 1 September (30 days), per the 27 October read of the deprecations page (5 of 12). One removal in the window from 3 August (MiniMax-M2.7) after 13 model ids left between 9 March and 9 June 2026 (4 of 8). The SambaCloud release notes stopped at 7 July 2026 on 8 October and couldn't be re-read. The community forum had staff replies, per the 8 October check (10 of 15). The Python SDK repository holds release pull requests only, so replies could not be judged (5 of 10). Python 1.14.0 and TypeScript 1.11.0, both 27 October 2026 (15). CI, release-please, a lock file and gitleaks scanning (8 of 10). 30+5+4+10+5+15+8 = 77.\n\n## Score by category\n\n| Category | Weight | Gemini 4 Carbon | SambaCloud | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 85 | SambaCloud +45 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 81 | Gemini 4 Carbon +4 |\n| Agent ergonomics | 13% (16.2 this run) | 93 | 67 | Gemini 4 Carbon +26 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 61 | SambaCloud +6 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | SambaCloud +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 77 | Gemini 4 Carbon +6 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 73 | SambaCloud +1 |\n| Negative events | ≤15 | 0 | -5 | |\n| **Total** | | **62.6 · B** | **64.9 · B** | |\n\n## Facts side by side\n\n| Fact | Gemini 4 Carbon | SambaCloud |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Google | SambaNova Systems, Inc. |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.sambanova.ai/v1` |\n| Transports | | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Freemium |\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 SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-10 | 2026-10-27 |\n| Terms last updated | 2026-04-28 | no date given |\n| Privacy policy last updated | 2026-10-01 | 2023-05-27 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | none | 2 stars, 76 npm/wk, 6.1k PyPI/wk |\n| Agent reviews | none | 3.5/5 (4) |\n\n## How the scores have moved\n\n### Gemini 4 Carbon\n\nNo score change since it was listed.\n\n### SambaCloud\n\n- -1.5 on 1 November 2026: new evidence, negative event\n- -0.1 on 28 October 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**SambaCloud.** Per-token prices are readable without a login, a free tier needs no card, and no incident has been posted since 25 June 2026. A Data Processing Addendum now names 24 sub-processors. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the product page's privacy claim contradicts the terms.\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### SambaCloud\n\n1. Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs and status page have named models the API no longer serves\n2. Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model\n3. Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model\n4. Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing\n5. Drop `do_sample` before moving to Python SDK 1.14.0 or TypeScript 1.11.0. Those releases removed it\n\n## Questions\n\n### Which is better for AI agents, Gemini 4 Carbon or SambaCloud?\n\nSambaCloud scores 64.9 (B) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 4 of 7 scored categories. Gemini 4 Carbon leads on agent ergonomics and maintenance \u0026 community.\n\n### Do Gemini 4 Carbon and SambaCloud need an API key?\n\nBoth need an API key.\n\n### Can an agent call Gemini 4 Carbon and SambaCloud without installing anything?\n\nYes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and SambaCloud at https://api.sambanova.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-4-carbon\", \"b\": \"sambanova\"}`. From a terminal: `anchor compare gemini-4-carbon sambanova`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json and https://www.anchorterminal.com/api/v1/tools/sambanova.json\n\n## Other comparisons with Gemini 4 Carbon or SambaCloud\n\n- [Amazon Bedrock vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.md)\n- [Amazon Bedrock vs SambaCloud](https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Claude API vs SambaCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- [Antseed vs SambaCloud](https://www.anchorterminal.com/compare/antseed-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/azure-openai-vs-sambanova.md)\n- [BlockRun.AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.md)\n- [BlockRun.AI vs SambaCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.md)\n- [Cerebras Inference vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon.md)\n- [Cerebras Inference vs SambaCloud](https://www.anchorterminal.com/compare/cerebras-inference-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-sambanova.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 SambaCloud](https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova.md)\n- [DeepInfra vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.md)\n- [DeepInfra vs SambaCloud](https://www.anchorterminal.com/compare/deepinfra-vs-sambanova.md)\n- [DeepSeek API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon.md)\n- [DeepSeek API vs SambaCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.md)\n- [Eden AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon.md)\n- [Eden AI vs SambaCloud](https://www.anchorterminal.com/compare/eden-ai-vs-sambanova.md)\n- [Glimpse vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon.md)\n- [Glimpse vs SambaCloud](https://www.anchorterminal.com/compare/elorian-glimpse-vs-sambanova.md)\n- [Fireworks AI Inference vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-carbon.md)\n- [Fireworks AI Inference vs SambaCloud](https://www.anchorterminal.com/compare/fireworks-inference-vs-sambanova.md)\n- [Gemini 4 Carbon vs Gemini Developer API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-gemini-api.md)\n- [Gemini 4 Carbon vs GroqCloud](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-groq.md)\n- [Gemini 4 Carbon vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-hugging-face-inference-providers.md)\n- [Gemini 4 Carbon vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-inkling-2-small.md)\n- [Gemini 4 Carbon vs Jais 3](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-jais-3.md)\n- [Gemini 4 Carbon vs Meta Model API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-meta-model-api.md)\n- [Gemini 4 Carbon vs MiniMax API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api.md)\n- [Gemini 4 Carbon vs Mistral AI API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api.md)\n- [Gemini 4 Carbon vs Muse Ember](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember.md)\n- [Gemini 4 Carbon vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.md)\n- [Gemini 4 Carbon vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl.md)\n- [Gemini 4 Carbon vs Novita AI](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-novita-ai.md)\n- [Gemini 4 Carbon vs OpenAI API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openai-api.md)\n- [Gemini 4 Carbon vs OpenRouter](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-openrouter.md)\n- [Gemini 4 Carbon vs Prism Inference](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-prism-inference.md)\n- [Gemini 4 Carbon vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-ramp-router.md)\n- [Gemini 4 Carbon vs Beam 1.0](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.md)\n- [Gemini 4 Carbon vs RouterPlus](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus.md)\n- [Gemini 4 Carbon vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow.md)\n- [Gemini 4 Carbon vs Simplismart](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.md)\n- [Gemini 4 Carbon vs StepFun API](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.md)\n- [Gemini 4 Carbon vs SWE-2 Flash](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.md)\n- [Gemini 4 Carbon vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.md)\n- [Gemini 4 Carbon vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.md)\n- [Gemini 4 Carbon vs Vercel AI Gateway](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.md)\n- [Gemini 4 Carbon vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.md)\n- [Gemini 4 Carbon vs xAI API (Grok)](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api.md)\n- [Gemini Developer API vs SambaCloud](https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.md)\n- [GroqCloud vs SambaCloud](https://www.anchorterminal.com/compare/groq-vs-sambanova.md)\n- [Hugging Face Inference Providers vs SambaCloud](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova.md)\n- [Inkling 2 Small vs SambaCloud](https://www.anchorterminal.com/compare/inkling-2-small-vs-sambanova.md)\n- [Jais 3 vs SambaCloud](https://www.anchorterminal.com/compare/jais-3-vs-sambanova.md)\n- [Meta Model API vs SambaCloud](https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.md)\n- [MiniMax API vs SambaCloud](https://www.anchorterminal.com/compare/minimax-api-vs-sambanova.md)\n- [Mistral AI API vs SambaCloud](https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.md)\n- [Muse Ember vs SambaCloud](https://www.anchorterminal.com/compare/muse-ember-vs-sambanova.md)\n- [Muse Spark Open vs SambaCloud](https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.md)\n- [Novita AI vs SambaCloud](https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.md)\n- [OpenAI API vs SambaCloud](https://www.anchorterminal.com/compare/openai-api-vs-sambanova.md)\n- [OpenRouter vs SambaCloud](https://www.anchorterminal.com/compare/openrouter-vs-sambanova.md)\n- [Router.com (Ramp Router) vs SambaCloud](https://www.anchorterminal.com/compare/ramp-router-vs-sambanova.md)\n- [Beam 1.0 vs SambaCloud](https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.md)\n- [RouterPlus vs SambaCloud](https://www.anchorterminal.com/compare/routerplus-vs-sambanova.md)\n- [SambaCloud vs SiliconFlow](https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.md)\n- [SambaCloud vs Simplismart](https://www.anchorterminal.com/compare/sambanova-vs-simplismart.md)\n- [SambaCloud vs StepFun API](https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api.md)\n- [SambaCloud vs SWE-2 Flash](https://www.anchorterminal.com/compare/sambanova-vs-swe-2-flash.md)\n- [SambaCloud vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/sambanova-vs-tencent-tokenhub.md)\n- [SambaCloud vs Together AI Inference](https://www.anchorterminal.com/compare/sambanova-vs-together-inference.md)\n- [SambaCloud vs Vercel AI Gateway](https://www.anchorterminal.com/compare/sambanova-vs-vercel-ai-gateway.md)\n- [SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.md)\n- [SambaCloud vs xAI API (Grok)](https://www.anchorterminal.com/compare/sambanova-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs SambaCloud](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-sambanova.md)\n- [Prism Inference vs SambaCloud](https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Gemini 4 Carbon vs SambaCloud", "url": "" } ], "description": "SambaCloud scores 64.9 (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", "SambaCloud B 64.9", "scores" ], "h1": "Gemini 4 Carbon vs SambaCloud", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/gemini-4-carbon-vs-sambanova", "published": "2026-10-01", "section": "tools", "title": "Gemini 4 Carbon vs SambaCloud for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova" }, "tokens": { "markdown": 6500, "slim": 930 }, "version": 1 }