{ "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": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Beam 1.0's 53.4 (D), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability.", "b": { "slug": "reflection-beam", "name": "Beam 1.0", "vendor": "Reflection", "vendorUrl": "https://reflection.ai", "kind": "model", "category": "inference", "summary": "Beam 1.0 is Reflection's open-weight text model for coding, reasoning and agentic work, with 501B total and 23B active parameters and a 1M-token context, served by the Reflection API and released as Apache-2.0 weights.", "url": "https://www.anchorterminal.com/tools/reflection-beam", "markdownUrl": "https://www.anchorterminal.com/tools/reflection-beam.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/reflection-beam.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/reflection-beam.json", "dns": "reflection-beam.grade.anchorterminal.com", "repo": "https://huggingface.co/reflection/Beam-1.0-501B-A23B", "license": "Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service", "transports": [ "http" ], "remoteUrl": "https://api.reflection.ai/openai/v1", "packages": [], "auth": "api-key", "authNotes": "Bearer API key created by a person on platform.reflection.ai under API Keys. Each key belongs to one project and to the user who made it, is shown once, can be revoked from the API Keys page, and is disabled if that user leaves the organisation or project. No scopes, expiry or key-management API found. The docs say some organisations must verify a credit card in Billing before their keys work (`payment_method_required`). Self-hosted weights need no account; the Hugging Face repositories are not gated.", "pricing": "freemium", "pricingNotes": "No per-token or plan price for the Reflection API is published on a page we can read. The rate-limits docs describe a daily token allowance that renews at 00:00 UTC and ask those requesting higher limits whether they want paid usage, and some organisations must verify a credit card before keys work (https://developers.reflection.ai/rate-limits.md, checked 2026-11-04). Reflection's beta pricing page and terms are on reflection.ai, which disallows our crawler. The weights are free to self-host under Apache-2.0.", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Reflection docs, llms.txt or OpenAPI document. Access needs a browser sign-up on platform.reflection.ai and an API key (checked 2026-11-04).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://developers.reflection.ai/introduction", "rateLimitsUrl": "https://developers.reflection.ai/rate-limits", "llmsTxt": "https://developers.reflection.ai/llms.txt", "openapi": "https://developers.reflection.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "self-hosted", "free", "openai-compatible", "openapi", "llms-txt", "status-page", "apache-2.0", "gpu", "new" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 53.4, "grade": "D", "agentReady": false, "rank": 953, "ranked": true, "rankOf": 1518, "categoryRank": 34, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 50, "payments": 10, "reliability": 52, "schema": 84, "security": 45, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-04" }, "negative": 0, "verdict": "The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026.", "bestFor": "An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.", "strengths": [ "OpenAI-compatible Chat Completions with `tool_choice`, parallel tool calls, strict tool schemas and `json_schema` structured outputs", "Error reference lists every status and code with whether to retry, and responses carry `Retry-After`, `x-should-retry` and `x-request-id`", "OpenAPI 3.0.3 document, llms.txt, a Markdown copy of every page and a docs MCP endpoint at developers.reflection.ai/mcp", "1,048,576-token context and up to 131,072 output tokens, with reasoning returned in its own `reasoning_content` field", "Weights in BF16, FP8 and NVFP4 under Apache-2.0, ungated, with Reflection's guides for SGLang, vLLM, TokenSpeed, Transformers, Helm and Dynamo" ], "weaknesses": [ "No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers", "Reasoning is mandatory and defaults to `max`, and a tool-call turn returned without `reasoning_content` makes every later request in that session fail", "No per-token price, retention period or subprocessor list on a page we can read; Reflection's terms and pricing pages are on a host that disallows our crawler", "Two API incidents labelled full outages on 14 and 15 October 2026 and three partial ones to 3 November", "No changelog and no model deprecation notice period found" ], "agentNotes": [ "Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`", "Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`", "Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code", "Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC", "Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.4 } ], "editorialScores": { "ergonomics": 67, "maintenance": 50, "payments": 10, "reliability": 52, "schema": 84, "security": 45, "transparency": 39 }, "provenanceScore": 74, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install openai # or: npm install openai, with base URL https://api.reflection.ai/openai/v1", "http": "curl https://api.reflection.ai/openai/v1/chat/completions \\\n -H \"Authorization: Bearer $REFLECTION_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"Beam-1.0-501B-A23B\",\n \"messages\": [\n {\"role\": \"user\", \"content\": \"Why is the sky blue?\"}\n ]\n }'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/reflection-beam" }, "sameCompany": [ "reflection-mirror" ], "area": "models", "provenance": { "legalEntity": "Reflection AI", "domain": "reflection.ai", "domainRegistered": "2017-12-16", "domainNote": "RDAP gave a registration date of 16 December 2017 and a transfer on 15 March 2024 on 17 October 2026 (not re-read; RDAP is a JSON service), so the domain predates the current owner.", "endpointOnVendorDomain": true, "terms": "https://reflection.ai/legal/commercial-terms-of-service", "privacy": "https://reflection.ai/legal/privacy-policy", "statusPage": "https://status.reflection.ai", "changelog": "", "securityTxt": "unknown", "checked": "2026-11-04", "notes": [ "reflection.ai's robots.txt disallows ClaudeBot, Claude-Web and anthropic-ai (read 4 November 2026), so the commercial terms, the privacy policy and reflection.ai's security.txt weren't re-read and their 17 October readings are struck. Both URLs are kept as listed facts.", "The legal entity is the copyright holder in the NOTICE files of Reflection's Mirror repository (`Copyright 2026 Reflection AI`), as on the reflection-mirror listing, since the fuller name came from struck pages.", "developers.reflection.ai/.well-known/security.txt returned 404 on 17 October 2026. The model card names reports@reflection.ai for security vulnerabilities.", "No changelog or release notes found in the developers docs or llms.txt (4 November 2026).", "status.reflection.ai answers robots.txt with a plain 404 (no rules) and was read under it." ], "score": 74 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/reflection-beam.json", "live": { "slug": "reflection-beam", "probe": { "target": "https://api.reflection.ai/openai/v1", "method": "get", "lastAt": "2026-11-10T23:47:22.954004943Z", "lastOk": true, "lastStatus": 404, "lastMs": 327, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 372, "p95ms24h": 460, "samples24h": 244, "samples30d": 5929, "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": 242, "ok": 242 } ], "since": "2026-10-17T00:00:00Z" }, "vendorStatus": { "page": "https://status.reflection.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-10T23:37:20.104679569Z" }, "securityTxt": { "url": "https://reflection.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:09:09.067534565Z" }, "llmsTxt": { "url": "https://developers.reflection.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:44:22.761493943Z" }, "domain": { "domain": "reflection.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/reflection.ai", "checkedAt": "2026-11-08T15:05:49.098411889Z" }, "pages": [ { "url": "https://reflection.ai/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-10T16:29:27.227176424Z", "changedAt": "2026-11-07T14:18:16.340207649Z", "fingerprint": "10e2a9daf712" }, { "url": "https://reflection.ai/legal/commercial-terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:29:24.31008174Z", "changedAt": "2026-11-07T14:18:12.998666824Z", "fingerprint": "34980ad61f53" } ], "models": { "reflection/beam-1.0-501b-a23b": { "openrouterId": "reflection/beam-1.0-501b-a23b", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 131072, "checkedAt": "2026-11-03T23:49:21.261568406Z" } }, "updatedAt": "2026-11-10T23:47:22.954004943Z" }, "streak": { "days": 24, "from": "2026-10-17", "sinceWatching": true, "best": 24 } }, "edges": [ { "by": 33, "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 weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50." }, "scores": { "a": 83, "b": 50 } }, { "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 (tool use, structured output, caching, context, batch, SDKs and defaults, errors). `tool_choice` of auto, none, required or a named function, `parallel_tool_calls`, strict tools and up to 128 tools. The tool-calling loop needs `reasoning_content` sent back on every assistant turn, and the docs say the model sometimes returns a tool-call step without it, after which every request in the session fails (12 of 20). `json_object` and strict `json_schema` (15). Cached prompt tokens are reported in `usage`, but caching can't be steered, the `prompt_cache_*` options are ignored and no cached price exists in the beta (5 of 10). 1,048,576-token context and 131,072 output tokens (15). No batch endpoint (0 of 10). No Reflection SDK, the OpenAI Python and TypeScript SDKs are documented, and defaults cost an agent turns, with reasoning always on at `max`, `stop` and `seed` ignored and a default output budget not reduced to fit the prompt (5 of 10). Machine-readable `error.code` values with `param`, `x-should-retry`, `Retry-After` and `x-request-id` (15). 12 + 15 + 5 + 15 + 0 + 5 + 15 = 67, per the 17 October reading of the developers guides, not re-read on 4 November beyond the models and rate-limits pages." }, "scores": { "a": 93, "b": 67 } }, { "by": 15, "category": "transparency", "leads": "gemini-4-carbon", "name": "Transparency \u0026 trust", "reasons": { "a": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.", "b": "Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39." }, "scores": { "a": 72, "b": 57 } }, { "by": 12, "category": "reliability", "leads": "reflection-beam", "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 lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52." }, "scores": { "a": 40, "b": 52 } }, { "by": 10, "category": "security", "leads": "gemini-4-carbon", "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. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models \"under contributor terms your organization accepted\". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45." }, "scores": { "a": 55, "b": 45 } }, { "by": 10, "category": "payments", "leads": "gemini-4-carbon", "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": "Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are \"interested in paid usage\", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10." }, "scores": { "a": 20, "b": 10 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Google", "b": "Reflection", "name": "Vendor" }, { "a": "https://generativelanguage.googleapis.com/v1beta", "b": "https://api.reflection.ai/openai/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": "Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-10", "b": "2026-10-16", "name": "Last release" }, { "a": "2026-04-28", "b": "2026-10-05", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "2026-08-28", "name": "Privacy policy last updated" }, { "a": "yes", "b": "yes", "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": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Beam 1.0's 53.4 (D), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability.", "question": "Which is better for AI agents, Gemini 4 Carbon or Beam 1.0?" }, { "answer": "Both need an API key.", "question": "Do Gemini 4 Carbon and Beam 1.0 need an API key?" }, { "answer": "Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Beam 1.0 at https://api.reflection.ai/openai/v1.", "question": "Can an agent call Gemini 4 Carbon and Beam 1.0 without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Agent ergonomics, 93 against 67", "Security \u0026 auth, 55 against 45", "Payments \u0026 pricing, 20 against 10", "Maintenance \u0026 community, 83 against 50", "Transparency \u0026 trust, 72 against 57" ], "also": null, "goodFor": "Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.", "slug": "gemini-4-carbon", "watchFor": "Paid tier only, with no free tier to try it on" }, { "aheadOn": [ "Reliability, 52 against 40" ], "also": null, "goodFor": "An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.", "slug": "reflection-beam", "watchFor": "No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers" } ], "history": { "gemini-4-carbon": null, "reflection-beam": [ { "causes": [ "evidence", "correction" ], "date": "2026-11-04", "delta": 0.1, "from": 53.3, "fromGrade": "D", "to": 53.4, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.1, "from": 53.4, "fromGrade": "D", "to": 53.3, "toGrade": "D" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.json", "title": "Amazon Bedrock vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.json", "title": "Amazon Bedrock vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.json", "title": "Claude API vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.json", "title": "Claude API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.json", "title": "Antseed vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-reflection-beam.json", "title": "Antseed vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/antseed-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-carbon.json", "title": "Azure OpenAI in Foundry Models vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.json", "title": "Azure OpenAI in Foundry Models vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.json", "title": "BlockRun.AI vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-reflection-beam.json", "title": "BlockRun.AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon.json", "title": "Cerebras Inference vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam.json", "title": "Cerebras Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-carbon.json", "title": "Claude Fable 5.2 vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-reflection-beam.json", "title": "Claude Fable 5.2 vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-carbon.json", "title": "Claude Mythos 5.2 vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-reflection-beam.json", "title": "Claude Mythos 5.2 vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-carbon.json", "title": "Cloudflare AI Gateway vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-reflection-beam.json", "title": "Cloudflare AI Gateway vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-carbon.json", "title": "Cloudflare Workers AI vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-reflection-beam.json", "title": "Cloudflare Workers AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.json", "title": "Cohere Chat API (Command models) vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam.json", "title": "Cohere Chat API (Command models) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.json", "title": "DeepInfra vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-reflection-beam.json", "title": "DeepInfra vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon.json", "title": "DeepSeek API vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-reflection-beam.json", "title": "DeepSeek API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon.json", "title": "Eden AI vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.json", "title": "Eden AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon.json", "title": "Glimpse vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-reflection-beam.json", "title": "Glimpse vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-carbon.json", "title": "Fireworks AI Inference vs Gemini 4 Carbon", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-carbon" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam.json", "title": "Fireworks AI Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-gemini-api.json", "title": "Gemini 4 Carbon vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-groq.json", "title": "Gemini 4 Carbon vs GroqCloud", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-hugging-face-inference-providers.json", "title": "Gemini 4 Carbon vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-inkling-2-small.json", "title": "Gemini 4 Carbon vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-jais-3.json", "title": "Gemini 4 Carbon vs Jais 3", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-meta-model-api.json", "title": "Gemini 4 Carbon vs Meta Model API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api.json", "title": "Gemini 4 Carbon vs MiniMax API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api.json", "title": "Gemini 4 Carbon vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember.json", "title": "Gemini 4 Carbon vs Muse Ember", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.json", "title": "Gemini 4 Carbon vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl.json", "title": "Gemini 4 Carbon vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-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-routerplus.json", "title": "Gemini 4 Carbon vs RouterPlus", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova.json", "title": "Gemini 4 Carbon vs SambaCloud", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow.json", "title": "Gemini 4 Carbon vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart.json", "title": "Gemini 4 Carbon vs Simplismart", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api.json", "title": "Gemini 4 Carbon vs StepFun API", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.json", "title": "Gemini 4 Carbon vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub.json", "title": "Gemini 4 Carbon vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference.json", "title": "Gemini 4 Carbon vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.json", "title": "Gemini 4 Carbon vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.json", "title": "Gemini 4 Carbon vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api.json", "title": "Gemini 4 Carbon vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam.json", "title": "Gemini Developer API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-reflection-beam.json", "title": "GroqCloud vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/groq-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.json", "title": "Hugging Face Inference Providers vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam.json", "title": "Inkling 2 Small vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.json", "title": "Jais 3 vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.json", "title": "Meta Model API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.json", "title": "MiniMax API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam.json", "title": "Mistral AI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam.json", "title": "Muse Ember vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam.json", "title": "Muse Spark Open vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.json", "title": "Novita AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.json", "title": "OpenAI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam.json", "title": "OpenRouter vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam.json", "title": "Prism Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam.json", "title": "Router.com (Ramp Router) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus.json", "title": "Beam 1.0 vs RouterPlus", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus" }, { "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/reflection-beam-vs-siliconflow.json", "title": "Beam 1.0 vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.json", "title": "Beam 1.0 vs Simplismart", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.json", "title": "Beam 1.0 vs StepFun API", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash.json", "title": "Beam 1.0 vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.json", "title": "Beam 1.0 vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.json", "title": "Beam 1.0 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference" }, { "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/reflection-beam-vs-vertex-ai.json", "title": "Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.json", "title": "Beam 1.0 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam.json", "title": "Nemotron 3.5 Super VL vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam" } ], "panel": null, "scores": [ { "by": 12, "edge": "reflection-beam", "gemini-4-carbon": 40, "key": "reliability", "name": "Reliability", "reflection-beam": 52, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 1, "edge": "gemini-4-carbon", "gemini-4-carbon": 85, "key": "schema", "name": "Schema \u0026 documentation", "reflection-beam": 84, "weight": 13 }, { "by": 26, "edge": "gemini-4-carbon", "gemini-4-carbon": 93, "key": "ergonomics", "name": "Agent ergonomics", "reflection-beam": 67, "weight": 13 }, { "by": 10, "edge": "gemini-4-carbon", "gemini-4-carbon": 55, "key": "security", "name": "Security \u0026 auth", "reflection-beam": 45, "weight": 14 }, { "by": 10, "edge": "gemini-4-carbon", "gemini-4-carbon": 20, "key": "payments", "name": "Payments \u0026 pricing", "reflection-beam": 10, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 33, "edge": "gemini-4-carbon", "gemini-4-carbon": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "reflection-beam": 50, "weight": 7 }, { "by": 15, "edge": "gemini-4-carbon", "gemini-4-carbon": 72, "key": "transparency", "name": "Transparency \u0026 trust", "reflection-beam": 57, "weight": 7 } ], "summary": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Beam 1.0's 53.4 (D), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability. 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.", "reflection-beam": "The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam", "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.min.md" }, "markdown": "Gemini 4 Carbon scores 62.6 (B) on agent readiness against Beam 1.0's 53.4 (D), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability. 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- Beam 1.0: grade D, 53.4/100, rank #953 of 1518. Markdown https://www.anchorterminal.com/tools/reflection-beam.md · JSON https://www.anchorterminal.com/api/v1/tools/reflection-beam.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- Security \u0026 auth, 55 against 45\n- Payments \u0026 pricing, 20 against 10\n- Maintenance \u0026 community, 83 against 50\n- Transparency \u0026 trust, 72 against 57\n\nWatch for: Paid tier only, with no free tier to try it on\n\n### Beam 1.0 (D)\n\nGood for: An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.\n\nAhead on:\n- Reliability, 52 against 40\n\nWatch for: No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers\n\n\n## Why the edge\n\n### Maintenance \u0026 community: Gemini 4 Carbon +33\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- Beam 1.0 (50): Model reading. The weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50.\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- Beam 1.0 (67): Model reading (tool use, structured output, caching, context, batch, SDKs and defaults, errors). `tool_choice` of auto, none, required or a named function, `parallel_tool_calls`, strict tools and up to 128 tools. The tool-calling loop needs `reasoning_content` sent back on every assistant turn, and the docs say the model sometimes returns a tool-call step without it, after which every request in the session fails (12 of 20). `json_object` and strict `json_schema` (15). Cached prompt tokens are reported in `usage`, but caching can't be steered, the `prompt_cache_*` options are ignored and no cached price exists in the beta (5 of 10). 1,048,576-token context and 131,072 output tokens (15). No batch endpoint (0 of 10). No Reflection SDK, the OpenAI Python and TypeScript SDKs are documented, and defaults cost an agent turns, with reasoning always on at `max`, `stop` and `seed` ignored and a default output budget not reduced to fit the prompt (5 of 10). Machine-readable `error.code` values with `param`, `x-should-retry`, `Retry-After` and `x-request-id` (15). 12 + 15 + 5 + 15 + 0 + 5 + 15 = 67, per the 17 October reading of the developers guides, not re-read on 4 November beyond the models and rate-limits pages.\n\n### Transparency \u0026 trust: Gemini 4 Carbon +15\n\n- Gemini 4 Carbon (72): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.\n- Beam 1.0 (57): Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39.\n\n### Reliability: Beam 1.0 +12\n\n- Gemini 4 Carbon (40): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Carbon's launch stage isn't stated in Google's developer post, the Antigravity post or the Cloud developer guide read on 10 November, and the model ID carries no preview label, so half (5 of 10, a judgement call; Argon's GA earned the platform 10). 10 + 5 + 5 + 15 + 0 + 5 = 40.\n- Beam 1.0 (52): Hosted lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52.\n\n### Security \u0026 auth: Gemini 4 Carbon +10\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- Beam 1.0 (45): Model reading. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models \"under contributor terms your organization accepted\". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45.\n\n### Payments \u0026 pricing: Gemini 4 Carbon +10\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- Beam 1.0 (10): Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are \"interested in paid usage\", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10.\n\n## Score by category\n\n| Category | Weight | Gemini 4 Carbon | Beam 1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 52 | Beam 1.0 +12 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 84 | Gemini 4 Carbon +1 |\n| Agent ergonomics | 13% (16.2 this run) | 93 | 67 | Gemini 4 Carbon +26 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 45 | Gemini 4 Carbon +10 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 10 | Gemini 4 Carbon +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 50 | Gemini 4 Carbon +33 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 57 | Gemini 4 Carbon +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **62.6 · B** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | Gemini 4 Carbon | Beam 1.0 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Google | Reflection |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.reflection.ai/openai/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 | Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-10 | 2026-10-16 |\n| Terms last updated | 2026-04-28 | 2026-10-05 |\n| Privacy policy last updated | 2026-10-01 | 2026-08-28 |\n| Customer content may train models | yes | yes |\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| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### Gemini 4 Carbon\n\nNo score change since it was listed.\n\n### Beam 1.0\n\n- +0.1 on 4 November 2026: new evidence, correction\n- -0.1 on 30 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**Beam 1.0.** The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026.\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### Beam 1.0\n\n1. Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`\n2. Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`\n3. Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code\n4. Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC\n5. Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens\n\n## Questions\n\n### Which is better for AI agents, Gemini 4 Carbon or Beam 1.0?\n\nGemini 4 Carbon scores 62.6 (B) on agent readiness against Beam 1.0's 53.4 (D), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability.\n\n### Do Gemini 4 Carbon and Beam 1.0 need an API key?\n\nBoth need an API key.\n\n### Can an agent call Gemini 4 Carbon and Beam 1.0 without installing anything?\n\nYes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Beam 1.0 at https://api.reflection.ai/openai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-4-carbon\", \"b\": \"reflection-beam\"}`. From a terminal: `anchor compare gemini-4-carbon reflection-beam`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json and https://www.anchorterminal.com/api/v1/tools/reflection-beam.json\n\n## Other comparisons with Gemini 4 Carbon or Beam 1.0\n\n- [Amazon Bedrock vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.md)\n- [Amazon Bedrock vs Beam 1.0](https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Claude API vs Beam 1.0](https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- [Antseed vs Beam 1.0](https://www.anchorterminal.com/compare/antseed-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.md)\n- [BlockRun.AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.md)\n- [BlockRun.AI vs Beam 1.0](https://www.anchorterminal.com/compare/blockrun-ai-vs-reflection-beam.md)\n- [Cerebras Inference vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon.md)\n- [Cerebras Inference vs Beam 1.0](https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam.md)\n- [DeepInfra vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.md)\n- [DeepInfra vs Beam 1.0](https://www.anchorterminal.com/compare/deepinfra-vs-reflection-beam.md)\n- [DeepSeek API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon.md)\n- [DeepSeek API vs Beam 1.0](https://www.anchorterminal.com/compare/deepseek-api-vs-reflection-beam.md)\n- [Eden AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon.md)\n- [Eden AI vs Beam 1.0](https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.md)\n- [Glimpse vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon.md)\n- [Glimpse vs Beam 1.0](https://www.anchorterminal.com/compare/elorian-glimpse-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam.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 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 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 Beam 1.0](https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam.md)\n- [GroqCloud vs Beam 1.0](https://www.anchorterminal.com/compare/groq-vs-reflection-beam.md)\n- [Hugging Face Inference Providers vs Beam 1.0](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.md)\n- [Inkling 2 Small vs Beam 1.0](https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam.md)\n- [Jais 3 vs Beam 1.0](https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.md)\n- [Meta Model API vs Beam 1.0](https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.md)\n- [MiniMax API vs Beam 1.0](https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.md)\n- [Mistral AI API vs Beam 1.0](https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam.md)\n- [Muse Ember vs Beam 1.0](https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam.md)\n- [Muse Spark Open vs Beam 1.0](https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam.md)\n- [Novita AI vs Beam 1.0](https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.md)\n- [OpenAI API vs Beam 1.0](https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.md)\n- [OpenRouter vs Beam 1.0](https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam.md)\n- [Prism Inference vs Beam 1.0](https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam.md)\n- [Router.com (Ramp Router) vs Beam 1.0](https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam.md)\n- [Beam 1.0 vs RouterPlus](https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus.md)\n- [Beam 1.0 vs SambaCloud](https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.md)\n- [Beam 1.0 vs SiliconFlow](https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.md)\n- [Beam 1.0 vs Simplismart](https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.md)\n- [Beam 1.0 vs StepFun API](https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.md)\n- [Beam 1.0 vs SWE-2 Flash](https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash.md)\n- [Beam 1.0 vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.md)\n- [Beam 1.0 vs Together AI Inference](https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.md)\n- [Beam 1.0 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway.md)\n- [Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.md)\n- [Beam 1.0 vs xAI API (Grok)](https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs Beam 1.0](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam.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 Beam 1.0", "url": "" } ], "description": "Gemini 4 Carbon scores 62.6 (B) to Beam 1.0's 53.4 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Gemini 4 Carbon B 62.6", "Beam 1.0 D 53.4", "scores" ], "h1": "Gemini 4 Carbon vs Beam 1.0", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/gemini-4-carbon-vs-reflection-beam", "published": "2026-10-01", "section": "tools", "title": "Gemini 4 Carbon vs Beam 1.0 for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-reflection-beam" }, "tokens": { "markdown": 7050, "slim": 980 }, "version": 1 }