{
  "data": {
    "a": {
      "slug": "amazon-bedrock",
      "name": "Amazon Bedrock",
      "vendor": "Amazon Web Services",
      "vendorUrl": "https://aws.amazon.com/bedrock/",
      "kind": "model",
      "category": "inference",
      "summary": "AWS's managed API for foundation models from Anthropic, OpenAI, Amazon, Meta, Mistral, DeepSeek, Qwen, xAI and others, called through the Converse API or OpenAI- and Anthropic-compatible endpoints under one AWS account.",
      "url": "https://www.anchorterminal.com/tools/amazon-bedrock",
      "markdownUrl": "https://www.anchorterminal.com/tools/amazon-bedrock.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/amazon-bedrock.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json",
      "dns": "amazon-bedrock.grade.anchorterminal.com",
      "repo": "https://github.com/aws/api-models-aws",
      "license": "Proprietary service under the AWS Customer Agreement and Service Terms. Third-party models carry their providers' licence terms. The AWS SDKs and the Smithy service models are Apache-2.0",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://bedrock-runtime.us-east-1.amazonaws.com",
      "packages": [
        {
          "registry": "pypi",
          "name": "boto3"
        },
        {
          "registry": "npm",
          "name": "@aws-sdk/client-bedrock-runtime"
        }
      ],
      "auth": "mixed",
      "authNotes": "AWS Signature Version 4 with IAM users, roles or short-lived STS credentials, and IAM policies that can name single model or inference-profile ARNs. Bedrock API keys go in an `Authorization: Bearer` header. Short-term keys last up to 12 hours and inherit the caller's IAM permissions; long-term keys create an IAM user and are marked for exploration only. Endpoints are regional, `bedrock-runtime.\u003cregion\u003e.amazonaws.com` and `bedrock-mantle.\u003cregion\u003e.api.aws`.",
      "pricing": "usage",
      "pricingNotes": "Per-token prices per model and Region, with Standard, Priority, Flex and Reserved tiers. Claude Opus 5.5 costs $4/$20 per million tokens through global cross-Region inference and $4.40/$22 through geographic or in-Region inference, cache reads $0.20. Cache reads on Claude Sonnet 5.5 were cut by half from 7 October 2026. Batch is half price on supported models but was not shown for Opus 5.5 or Sonnet 5.5. New AWS accounts get up to $200 in Free Tier credits (https://aws.amazon.com/bedrock/pricing/, rates per AWS's price feed of 30 September 2026; the page's tables are drawn by script and were not readable on 6 November).",
      "priceSummary": "from $0.30 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 on the pricing page or in the user guide's llms.txt (checked 2026-11-06). Access needs an AWS account.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": 21825916,
        "pypiWeekly": null,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html",
      "rateLimitsUrl": "https://docs.aws.amazon.com/general/latest/gr/bedrock.html",
      "llmsTxt": "https://docs.aws.amazon.com/bedrock/latest/userguide/llms.txt",
      "capabilities": [
        "inference.llm",
        "inference.open-weights"
      ],
      "tags": [
        "official",
        "hosted",
        "model",
        "open-weights",
        "enterprise",
        "usage-priced",
        "llms-txt",
        "python",
        "typescript",
        "status-page"
      ],
      "lastRelease": "2026-10-30",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 81.7,
        "grade": "A",
        "agentReady": true,
        "rank": 8,
        "ranked": true,
        "rankOf": 1518,
        "categoryRank": 3,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 92,
          "maintenance": 81,
          "payments": 30,
          "reliability": 80,
          "schema": 94,
          "security": 98,
          "transparency": 85
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": 0,
        "verdict": "Bedrock reaches Claude, GPT-6, Nova, Llama and other families through one IAM-controlled API, with a 99.9 per cent SLA and a per-Region zero-retention switch. Setup needs an AWS account, IAM permissions and a Region, capabilities vary by model, and some Regions gave five older Claude models about 34 days of notice.",
        "bestFor": "Teams already on AWS who want Claude, GPT-6, Nova, Llama and other models under one IAM, billing and VPC boundary, with regional data controls and an SLA.",
        "strengths": [
          "One API and one bill for Anthropic, OpenAI, Amazon, Meta, Mistral, DeepSeek, Qwen, xAI and other model families",
          "IAM policies can limit a caller to named model ARNs, and short-term API keys expire within 12 hours",
          "A `none` data retention mode per Region blocks any model that would store prompts",
          "Published SLA of 99.9 per cent a month per Region with service credits",
          "Per-model token quotas published with default values, for example 30,000,000 tokens a minute for Opus 5.5 global inference"
        ],
        "weaknesses": [
          "An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone",
          "Batch inference isn't shown for Claude Opus 5.5 or Sonnet 5.5, and since 26 October batch completion isn't guaranteed",
          "Claude Fable 5 and 5.1 retain all traffic up to 30 days, and AWS may review flagged prompts",
          "Five older Claude models went Legacy on 10 or 13 October 2026 with end of life on 13 November in some Regions, against the 6-month floor the policy states",
          "The Middle East (UAE) and (Bahrain) Regions have been disrupted since March 2026, and AWS says some data there can't be restored"
        ],
        "agentNotes": [
          "Use the geographic or global inference ID from the model card, such as `global.anthropic.claude-opus-5-5`. Global routing is cheaper but can process data in any commercial Region",
          "Set `data_retention_mode` to `none` in each Region before sending sensitive data. Models that need retention then return ValidationException",
          "Back off with jitter on 429 ThrottlingException, 503 and 529 `overloaded_error`, and honour `Retry-After` when it's sent",
          "Generate short-term API keys from an IAM role for production. Long-term keys create an IAM user and AWS marks them exploration only",
          "Call ListFoundationModels in your Region and read `modelLifecycle` before pinning a model ID. Claude 3.x IDs in several Regions stop working on 13 November 2026 and requests don't redirect"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "A",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 81.7
          }
        ],
        "editorialScores": {
          "ergonomics": 92,
          "maintenance": 81,
          "payments": 30,
          "reliability": 80,
          "schema": 94,
          "security": 98,
          "transparency": 76
        },
        "provenanceScore": 94,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-06",
            "maintenance": "2026-11-06",
            "payments": "2026-11-06",
            "reliability": "2026-11-06",
            "schema": "2026-11-06",
            "security": "2026-11-06",
            "transparency": "2026-11-06"
          },
          "last": "2026-11-06",
          "oldest": "2026-11-06",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install boto3   # or: npm i @aws-sdk/client-bedrock-runtime",
        "http": "curl -X POST \"https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-6/converse\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"Authorization: Bearer $AWS_BEARER_TOKEN_BEDROCK\" \\\n  -d '{\"messages\": [{\"role\": \"user\", \"content\": [{\"text\": \"Hello\"}]}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/amazon-bedrock"
      },
      "sameCompany": [
        "amazon-nova-embeddings",
        "amazon-bedrock-guardrails",
        "amazon-transcribe",
        "amazon-polly",
        "amazon-nova-sonic",
        "agentcore-memory",
        "agentcore-identity",
        "aws-secrets-manager",
        "agentcore-web-search",
        "aws-mcp-servers",
        "amazon-ses",
        "amazon-location",
        "amazon-translate",
        "amazon-ads-api",
        "amazon-creators-api"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "Amazon Web Services, Inc.",
        "domain": "amazon.com",
        "domainRegistered": "1994-11-01",
        "domainNote": "The endpoints are on amazonaws.com and api.aws, both AWS domains. The security.txt on aws.amazon.com had expired on 2026-09-24 and was renewed, with Expires 2027-10-16, when read on 2026-11-06.",
        "endpointOnVendorDomain": true,
        "terms": "https://aws.amazon.com/service-terms/",
        "privacy": "https://aws.amazon.com/privacy/",
        "statusPage": "https://health.aws.amazon.com/health/status",
        "changelog": "https://docs.aws.amazon.com/bedrock/latest/userguide/doc-history.html",
        "securityTxt": "valid",
        "checked": "2026-11-06",
        "notes": [
          "AWS's public history feed (historyevents.json) lists Amazon Bedrock as disrupted in the ME-CENTRAL-1 and ME-SOUTH-1 Regions since March 2026, with a last update on 15 September 2026, and no Bedrock event in other Regions in the 90 days to 6 November 2026. An EU-SOUTH-2 packet-loss event on 4 October 2026 named Bedrock AgentCore, not Bedrock.",
          "The pricing page fills its tables by script. Prices here come from AWS's public price feed of 30 September 2026; the bedrockfoundationmodels feed read on 6 November (published 12 October) carries only rate codes."
        ],
        "score": 94
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/amazon-bedrock.json",
      "live": {
        "slug": "amazon-bedrock",
        "probe": {
          "target": "https://bedrock-runtime.us-east-1.amazonaws.com",
          "method": "get",
          "lastAt": "2026-11-10T23:46:49.850908339Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 250,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 269,
          "p95ms24h": 373,
          "samples24h": 244,
          "samples30d": 984,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 13,
              "ok": 13
            },
            {
              "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": "2026-11-06T00:00:00Z"
        },
        "versions": [
          {
            "registry": "npm",
            "name": "@aws-sdk/client-bedrock-runtime",
            "version": "3.1165.0",
            "seenAt": "2026-11-10T03:18:51.484950693Z"
          },
          {
            "registry": "pypi",
            "name": "boto3",
            "version": "1.43.127",
            "released": "2026-11-09",
            "seenAt": "2026-11-10T03:18:50.286628577Z"
          }
        ],
        "githubStars": 229,
        "npmWeekly": 21874862,
        "pypiWeekly": 600461796,
        "securityTxt": {
          "url": "https://amazon.com/.well-known/security.txt",
          "state": "valid",
          "checkedAt": "2026-11-10T16:09:12.70977413Z"
        },
        "llmsTxt": {
          "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-10T15:41:52.89896946Z"
        },
        "domain": {
          "domain": "amazon.com",
          "registered": "1994-11-01",
          "source": "https://rdap.verisign.com/com/v1/domain/amazon.com",
          "checkedAt": "2026-11-08T14:52:19.114196922Z"
        },
        "pages": [
          {
            "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html",
            "kind": "deprecations",
            "status": 304,
            "checkedAt": "2026-11-10T16:15:51.46773023Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "dce416908c57"
          }
        ],
        "github": {
          "repo": "aws/api-models-aws",
          "checkedAt": "2026-11-09T09:41:58.304677819Z",
          "stars": 229,
          "archived": false,
          "issuesEnabled": false,
          "pushedAt": "2026-11-06T19:40:10Z",
          "openIssues": 0,
          "openPRs": 3,
          "issuesOpened90d": 0,
          "issuesClosed90d": 0,
          "prsMerged90d": 8,
          "ci": {
            "branch": "main",
            "runs": 50,
            "success": 50,
            "failure": 0,
            "other": 0,
            "latest": "success",
            "latestAt": "2026-11-06T20:18:21Z"
          }
        },
        "updatedAt": "2026-11-10T23:46:49.850908339Z"
      },
      "streak": {
        "days": 4,
        "from": "2026-11-06",
        "sinceWatching": true,
        "last": {
          "kind": "shutdown",
          "date": "2026-10-14",
          "what": "Claude Sonnet 4 (`anthropic.claude-sonnet-4-20250514-v1:0`) end of life",
          "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html"
        },
        "next": {
          "kind": "shutdown",
          "date": "2026-11-26",
          "what": "AI21 Jamba 1.5 Large and Mini end of life",
          "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html"
        },
        "best": 4
      }
    },
    "answer": "Amazon Bedrock scores 81.7 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 5 of 7 scored categories.",
    "b": {
      "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
      }
    },
    "edges": [
      {
        "by": 43,
        "category": "security",
        "leads": "amazon-bedrock",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "Model reading. IAM with SigV4, roles and STS session credentials, policies down to a model or inference-profile ARN, short-term API keys that expire within 12 hours, long-term keys with expiry and reset, and condition keys that can deny bearer tokens altogether (30). The security page says customer data isn't shared with model providers or used to improve the base models (20). The abuse detection page says Bedrock stores no inputs or outputs by default, and a per-Region `none` mode blocks models that require retention, but Claude Fable 5 and 5.1 keep all traffic up to 30 days and GPT-6 and GPT-5.x keep flagged traffic up to 30 days (13 of 15, a judgement call; Anthropic's own API got 12 for the same Fable exception without an account-level block). CloudTrail logs API calls, and model invocation logging can send prompts and responses to S3 or CloudWatch Logs (15). Bedrock is in ISO, SOC and CSA STAR Level 2 scope, HIPAA eligible and FedRAMP High in GovCloud (US-West) per its security page, with a vulnerability disclosure programme on HackerOne, and the aws.amazon.com security.txt, expired on 6 October, was renewed with Expires 2027-10-16 when read on 6 November (20). Up from 96 on 6 October for that reason.",
          "b": "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."
        },
        "scores": {
          "a": 98,
          "b": 55
        }
      },
      {
        "by": 40,
        "category": "reliability",
        "leads": "amazon-bedrock",
        "name": "Reliability",
        "reasons": {
          "a": "AWS Health Dashboard with per-service, per-Region feeds and a public history file (20). The history lists Amazon Bedrock as disrupted in ME-CENTRAL-1 (UAE) and ME-SOUTH-1 (Bahrain) since March 2026, where AWS said on 15 September 2026 (still inside the 90-day window on 6 November) that it can't restore resources held only there. No other Bedrock event appears in the history in the 90 days to 6 November; an EU-SOUTH-2 packet-loss event on 4 October named Bedrock AgentCore, not Bedrock. This counts as one major event (10). StatusGator's third-party mirror shows 'Increased Error Rates' warnings on 24, 26 and 27 August and 10 September that we couldn't find in AWS's own history, so we didn't score them. Per-model token quotas with default values in the AWS General Reference, such as 30,000,000 tokens a minute for Opus 5.5 global inference (15). The error guide gives exponential backoff with jitter for 429, 503 and 529 and says to honour `Retry-After`, and the SDKs retry ModelNotReadyException up to five times (15). SLA of 99.9 per cent a month per Region for the model APIs, last updated 4 October 2023 (10). Converse and the current Claude, GPT-6 and Nova 2 Lite models are GA (10).",
          "b": "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."
        },
        "scores": {
          "a": 80,
          "b": 40
        }
      },
      {
        "by": 13,
        "category": "transparency",
        "leads": "amazon-bedrock",
        "name": "Transparency \u0026 trust",
        "reasons": {
          "a": "Closed service under the AWS Customer Agreement and Service Terms, with the SDKs and Smithy models under Apache-2.0 (18, as for S3). The data retention, abuse detection and security pages agree that Bedrock stores nothing by default, name the models that retain traffic and for how long, and say retained data isn't shared with providers. The retention page's `default` mode says AWS 'may retain the data for safety and abuse-prevention purposes' without a period, and a legacy `provider_data_share` mode is kept though sharing isn't supported (25 of 30). A written lifecycle policy with Legacy and EOL dates per model, but the legacy table's 34-day Legacy periods for five Claude models in some Regions contradict its own 6-month floor (15 of 20, down from 18). AWS's sub-processor list, per the 4 October S3 check, and per-Region, geographic and global inference options, with global routing able to process data in any commercial Region (18 of 20).",
          "b": "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."
        },
        "scores": {
          "a": 85,
          "b": 72
        }
      },
      {
        "by": 10,
        "category": "payments",
        "leads": "amazon-bedrock",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "No x402, MPP or L402 (0). Per-token prices per model, tier and Region on the public pricing page, filled from AWS's public price feed (20). New accounts get up to $200 in Free Tier credits and the Free Tier page lists Bedrock among eligible services, and the Free Tier FAQ says most new customers don't need a payment method, but AWS may still ask for one, so half, as for S3 (10). A person signs up for AWS in a browser and sets up IAM before any key exists (0).",
          "b": "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."
        },
        "scores": {
          "a": 30,
          "b": 20
        }
      },
      {
        "by": 9,
        "category": "schema",
        "leads": "amazon-bedrock",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "Model reading. No OpenAPI, but the bedrock-runtime and bedrock Smithy models are public in aws/api-models-aws with types, required members and enums, counted as for S3 (25). llms.txt for the user guide with about 2,000 lines, each page with a Markdown twin (10). Model cards state context, output limits, endpoints and supported functions per model, and the guide now recommends `bedrock-runtime` for new work, but support for each API, endpoint and feature changes model by model (16 of 20). Structured outputs compile JSON Schema to a grammar, with `minimum`, `maximum` and string lengths supported, though some inference profiles don't support it, such as Haiku 4.5 through the India profile (13 of 15). Every operation lists typed errors with HTTP codes and links to a troubleshooting page with causes and fixes, and examples run through the guide (15). API version 2023-09-30 and a dated document history with an RSS feed, newest entry 30 October 2026, with structured outputs for Claude on both endpoints added on 18 October (15).",
          "b": "Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85."
        },
        "scores": {
          "a": 94,
          "b": 85
        }
      }
    ],
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Amazon Web Services",
        "b": "Google",
        "name": "Vendor"
      },
      {
        "a": "https://bedrock-runtime.us-east-1.amazonaws.com",
        "b": "https://generativelanguage.googleapis.com/v1beta",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Proprietary service under the AWS Customer Agreement and Service Terms. Third-party models carry their providers' licence terms. The AWS SDKs and the Smithy service models are Apache-2.0",
        "b": "Closed model, used through the Gemini API and Google's apps under Google's terms",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-30",
        "b": "2026-11-10",
        "name": "Last release"
      },
      {
        "a": "2026-10-01",
        "b": "2026-04-28",
        "name": "Terms last updated"
      },
      {
        "a": "2026-05-18",
        "b": "2026-10-01",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes, with an opt-out",
        "b": "yes",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "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": "21.8M npm/wk",
        "b": "none",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "Amazon Bedrock scores 81.7 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 5 of 7 scored categories.",
        "question": "Which is better for AI agents, Amazon Bedrock or Gemini 4 Carbon?"
      },
      {
        "answer": "Amazon Bedrock takes an API key or an OAuth sign-in. Gemini 4 Carbon needs an API key.",
        "question": "Do Amazon Bedrock and Gemini 4 Carbon need an API key?"
      },
      {
        "answer": "Yes. Amazon Bedrock has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Gemini 4 Carbon at https://generativelanguage.googleapis.com/v1beta.",
        "question": "Can an agent call Amazon Bedrock and Gemini 4 Carbon without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 80 against 40",
          "Schema \u0026 documentation, 94 against 85",
          "Security \u0026 auth, 98 against 55",
          "Payments \u0026 pricing, 30 against 20",
          "Transparency \u0026 trust, 85 against 72"
        ],
        "also": [
          "Agent-ready, a grade of BB or better"
        ],
        "goodFor": "Teams already on AWS who want Claude, GPT-6, Nova, Llama and other models under one IAM, billing and VPC boundary, with regional data controls and an SLA.",
        "slug": "amazon-bedrock",
        "watchFor": "An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone"
      },
      {
        "aheadOn": null,
        "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"
      }
    ],
    "history": null,
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.json",
        "title": "Amazon Bedrock vs Claude API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed.json",
        "title": "Amazon Bedrock vs Antseed",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.json",
        "title": "Amazon Bedrock vs Azure OpenAI in Foundry Models",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.json",
        "title": "Amazon Bedrock vs BlockRun.AI",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.json",
        "title": "Amazon Bedrock vs Cerebras Inference",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-fable-5-2.json",
        "title": "Amazon Bedrock vs Claude Fable 5.2",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-fable-5-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-mythos-5-2.json",
        "title": "Amazon Bedrock vs Claude Mythos 5.2",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-mythos-5-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-ai-gateway.json",
        "title": "Amazon Bedrock vs Cloudflare AI Gateway",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-ai-gateway"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-workers-ai.json",
        "title": "Amazon Bedrock vs Cloudflare Workers AI",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-workers-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.json",
        "title": "Amazon Bedrock vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepinfra.json",
        "title": "Amazon Bedrock vs DeepInfra",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepinfra"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api.json",
        "title": "Amazon Bedrock vs DeepSeek API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.json",
        "title": "Amazon Bedrock vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse.json",
        "title": "Amazon Bedrock vs Glimpse",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-fireworks-inference.json",
        "title": "Amazon Bedrock vs Fireworks AI Inference",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-fireworks-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api.json",
        "title": "Amazon Bedrock vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq.json",
        "title": "Amazon Bedrock vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.json",
        "title": "Amazon Bedrock vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small.json",
        "title": "Amazon Bedrock vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3.json",
        "title": "Amazon Bedrock vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.json",
        "title": "Amazon Bedrock vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api.json",
        "title": "Amazon Bedrock vs MiniMax API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-mistral-api.json",
        "title": "Amazon Bedrock vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.json",
        "title": "Amazon Bedrock vs Muse Ember",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-spark-open.json",
        "title": "Amazon Bedrock vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-nemotron-3-5-super-vl.json",
        "title": "Amazon Bedrock vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-nemotron-3-5-super-vl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai.json",
        "title": "Amazon Bedrock vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.json",
        "title": "Amazon Bedrock vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openrouter.json",
        "title": "Amazon Bedrock vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-prism-inference.json",
        "title": "Amazon Bedrock vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router.json",
        "title": "Amazon Bedrock vs Router.com (Ramp Router)",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router"
      },
      {
        "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/amazon-bedrock-vs-routerplus.json",
        "title": "Amazon Bedrock vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova.json",
        "title": "Amazon Bedrock vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.json",
        "title": "Amazon Bedrock vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.json",
        "title": "Amazon Bedrock vs Simplismart",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api.json",
        "title": "Amazon Bedrock vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-swe-2-flash.json",
        "title": "Amazon Bedrock vs SWE-2 Flash",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-swe-2-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-tencent-tokenhub.json",
        "title": "Amazon Bedrock vs Tencent Cloud TokenHub",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-tencent-tokenhub"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.json",
        "title": "Amazon Bedrock vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.json",
        "title": "Amazon Bedrock vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.json",
        "title": "Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.json",
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        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-swe-2-flash.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vercel-ai-gateway.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-4-carbon-vs-vertex-ai.json",
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    ],
    "panel": null,
    "scores": [
      {
        "amazon-bedrock": 80,
        "by": 40,
        "edge": "amazon-bedrock",
        "gemini-4-carbon": 40,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "amazon-bedrock": 94,
        "by": 9,
        "edge": "amazon-bedrock",
        "gemini-4-carbon": 85,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "amazon-bedrock": 92,
        "by": 1,
        "edge": "gemini-4-carbon",
        "gemini-4-carbon": 93,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "amazon-bedrock": 98,
        "by": 43,
        "edge": "amazon-bedrock",
        "gemini-4-carbon": 55,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "amazon-bedrock": 30,
        "by": 10,
        "edge": "amazon-bedrock",
        "gemini-4-carbon": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "amazon-bedrock": 81,
        "by": 2,
        "edge": "gemini-4-carbon",
        "gemini-4-carbon": 83,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "amazon-bedrock": 85,
        "by": 13,
        "edge": "amazon-bedrock",
        "gemini-4-carbon": 72,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Amazon Bedrock scores 81.7 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 5 of 7 scored categories. Both do llm inference.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "amazon-bedrock": "Bedrock reaches Claude, GPT-6, Nova, Llama and other families through one IAM-controlled API, with a 99.9 per cent SLA and a per-Region zero-retention switch. Setup needs an AWS account, IAM permissions and a Region, capabilities vary by model, and some Regions gave five older Claude models about 34 days of notice.",
      "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."
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  "markdown": "Amazon Bedrock scores 81.7 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 5 of 7 scored categories. Both do llm inference.\n\n- Amazon Bedrock: grade A, 81.7/100, rank #8 of 1518. Markdown https://www.anchorterminal.com/tools/amazon-bedrock.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json\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- 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### Amazon Bedrock (A)\n\nGood for: Teams already on AWS who want Claude, GPT-6, Nova, Llama and other models under one IAM, billing and VPC boundary, with regional data controls and an SLA.\n\nAhead on:\n- Reliability, 80 against 40\n- Schema \u0026 documentation, 94 against 85\n- Security \u0026 auth, 98 against 55\n- Payments \u0026 pricing, 30 against 20\n- Transparency \u0026 trust, 85 against 72\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone\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\nWatch for: Paid tier only, with no free tier to try it on\n\n\n## Why the edge\n\n### Security \u0026 auth: Amazon Bedrock +43\n\n- Amazon Bedrock (98): Model reading. IAM with SigV4, roles and STS session credentials, policies down to a model or inference-profile ARN, short-term API keys that expire within 12 hours, long-term keys with expiry and reset, and condition keys that can deny bearer tokens altogether (30). The security page says customer data isn't shared with model providers or used to improve the base models (20). The abuse detection page says Bedrock stores no inputs or outputs by default, and a per-Region `none` mode blocks models that require retention, but Claude Fable 5 and 5.1 keep all traffic up to 30 days and GPT-6 and GPT-5.x keep flagged traffic up to 30 days (13 of 15, a judgement call; Anthropic's own API got 12 for the same Fable exception without an account-level block). CloudTrail logs API calls, and model invocation logging can send prompts and responses to S3 or CloudWatch Logs (15). Bedrock is in ISO, SOC and CSA STAR Level 2 scope, HIPAA eligible and FedRAMP High in GovCloud (US-West) per its security page, with a vulnerability disclosure programme on HackerOne, and the aws.amazon.com security.txt, expired on 6 October, was renewed with Expires 2027-10-16 when read on 6 November (20). Up from 96 on 6 October for that reason.\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\n### Reliability: Amazon Bedrock +40\n\n- Amazon Bedrock (80): AWS Health Dashboard with per-service, per-Region feeds and a public history file (20). The history lists Amazon Bedrock as disrupted in ME-CENTRAL-1 (UAE) and ME-SOUTH-1 (Bahrain) since March 2026, where AWS said on 15 September 2026 (still inside the 90-day window on 6 November) that it can't restore resources held only there. No other Bedrock event appears in the history in the 90 days to 6 November; an EU-SOUTH-2 packet-loss event on 4 October named Bedrock AgentCore, not Bedrock. This counts as one major event (10). StatusGator's third-party mirror shows 'Increased Error Rates' warnings on 24, 26 and 27 August and 10 September that we couldn't find in AWS's own history, so we didn't score them. Per-model token quotas with default values in the AWS General Reference, such as 30,000,000 tokens a minute for Opus 5.5 global inference (15). The error guide gives exponential backoff with jitter for 429, 503 and 529 and says to honour `Retry-After`, and the SDKs retry ModelNotReadyException up to five times (15). SLA of 99.9 per cent a month per Region for the model APIs, last updated 4 October 2023 (10). Converse and the current Claude, GPT-6 and Nova 2 Lite models are GA (10).\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\n### Transparency \u0026 trust: Amazon Bedrock +13\n\n- Amazon Bedrock (85): Closed service under the AWS Customer Agreement and Service Terms, with the SDKs and Smithy models under Apache-2.0 (18, as for S3). The data retention, abuse detection and security pages agree that Bedrock stores nothing by default, name the models that retain traffic and for how long, and say retained data isn't shared with providers. The retention page's `default` mode says AWS 'may retain the data for safety and abuse-prevention purposes' without a period, and a legacy `provider_data_share` mode is kept though sharing isn't supported (25 of 30). A written lifecycle policy with Legacy and EOL dates per model, but the legacy table's 34-day Legacy periods for five Claude models in some Regions contradict its own 6-month floor (15 of 20, down from 18). AWS's sub-processor list, per the 4 October S3 check, and per-Region, geographic and global inference options, with global routing able to process data in any commercial Region (18 of 20).\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\n### Payments \u0026 pricing: Amazon Bedrock +10\n\n- Amazon Bedrock (30): No x402, MPP or L402 (0). Per-token prices per model, tier and Region on the public pricing page, filled from AWS's public price feed (20). New accounts get up to $200 in Free Tier credits and the Free Tier page lists Bedrock among eligible services, and the Free Tier FAQ says most new customers don't need a payment method, but AWS may still ask for one, so half, as for S3 (10). A person signs up for AWS in a browser and sets up IAM before any key exists (0).\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\n### Schema \u0026 documentation: Amazon Bedrock +9\n\n- Amazon Bedrock (94): Model reading. No OpenAPI, but the bedrock-runtime and bedrock Smithy models are public in aws/api-models-aws with types, required members and enums, counted as for S3 (25). llms.txt for the user guide with about 2,000 lines, each page with a Markdown twin (10). Model cards state context, output limits, endpoints and supported functions per model, and the guide now recommends `bedrock-runtime` for new work, but support for each API, endpoint and feature changes model by model (16 of 20). Structured outputs compile JSON Schema to a grammar, with `minimum`, `maximum` and string lengths supported, though some inference profiles don't support it, such as Haiku 4.5 through the India profile (13 of 15). Every operation lists typed errors with HTTP codes and links to a troubleshooting page with causes and fixes, and examples run through the guide (15). API version 2023-09-30 and a dated document history with an RSS feed, newest entry 30 October 2026, with structured outputs for Claude on both endpoints added on 18 October (15).\n- Gemini 4 Carbon (85): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock | Gemini 4 Carbon | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 40 | Amazon Bedrock +40 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 94 | 85 | Amazon Bedrock +9 |\n| Agent ergonomics | 13% (16.2 this run) | 92 | 93 | Gemini 4 Carbon +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 98 | 55 | Amazon Bedrock +43 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 20 | Amazon Bedrock +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 81 | 83 | Gemini 4 Carbon +2 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 72 | Amazon Bedrock +13 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **81.7 · A** | **62.6 · B** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock | Gemini 4 Carbon |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Amazon Web Services | Google |\n| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://generativelanguage.googleapis.com/v1beta` |\n| Transports | HTTP |  |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under the AWS Customer Agreement and Service Terms. Third-party models carry their providers' licence terms. The AWS SDKs and the Smithy service models are Apache-2.0 | Closed model, used through the Gemini API and Google's apps under Google's terms |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-11-10 |\n| Terms last updated | 2026-10-01 | 2026-04-28 |\n| Privacy policy last updated | 2026-05-18 | 2026-10-01 |\n| Customer content may train models | yes, with an opt-out | yes |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 21.8M npm/wk | none |\n\n## Verdicts\n\n**Amazon Bedrock.** Bedrock reaches Claude, GPT-6, Nova, Llama and other families through one IAM-controlled API, with a 99.9 per cent SLA and a per-Region zero-retention switch. Setup needs an AWS account, IAM permissions and a Region, capabilities vary by model, and some Regions gave five older Claude models about 34 days of notice.\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## Before you call either\n\n### Amazon Bedrock\n\n1. Use the geographic or global inference ID from the model card, such as `global.anthropic.claude-opus-5-5`. Global routing is cheaper but can process data in any commercial Region\n2. Set `data_retention_mode` to `none` in each Region before sending sensitive data. Models that need retention then return ValidationException\n3. Back off with jitter on 429 ThrottlingException, 503 and 529 `overloaded_error`, and honour `Retry-After` when it's sent\n4. Generate short-term API keys from an IAM role for production. Long-term keys create an IAM user and AWS marks them exploration only\n5. Call ListFoundationModels in your Region and read `modelLifecycle` before pinning a model ID. Claude 3.x IDs in several Regions stop working on 13 November 2026 and requests don't redirect\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## Questions\n\n### Which is better for AI agents, Amazon Bedrock or Gemini 4 Carbon?\n\nAmazon Bedrock scores 81.7 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in 5 of 7 scored categories.\n\n### Do Amazon Bedrock and Gemini 4 Carbon need an API key?\n\nAmazon Bedrock takes an API key or an OAuth sign-in. Gemini 4 Carbon needs an API key.\n\n### Can an agent call Amazon Bedrock and Gemini 4 Carbon without installing anything?\n\nYes. Amazon Bedrock has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Gemini 4 Carbon at https://generativelanguage.googleapis.com/v1beta.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.json, and with the fewest tokens: https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-carbon.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"amazon-bedrock\", \"b\": \"gemini-4-carbon\"}`. From a terminal: `anchor compare amazon-bedrock gemini-4-carbon`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json and https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json\n\n## Other comparisons with Amazon Bedrock or Gemini 4 Carbon\n\n- [Amazon Bedrock vs Claude API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.md)\n- [Amazon Bedrock vs Antseed](https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed.md)\n- [Amazon Bedrock vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.md)\n- [Amazon Bedrock vs BlockRun.AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.md)\n- [Amazon Bedrock vs Cerebras Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.md)\n- [Amazon Bedrock vs Claude Fable 5.2](https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-fable-5-2.md)\n- [Amazon Bedrock vs Claude Mythos 5.2](https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-mythos-5-2.md)\n- [Amazon Bedrock vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-ai-gateway.md)\n- [Amazon Bedrock vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-workers-ai.md)\n- [Amazon Bedrock vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.md)\n- [Amazon Bedrock vs DeepInfra](https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepinfra.md)\n- [Amazon Bedrock vs DeepSeek API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api.md)\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Amazon Bedrock vs Glimpse](https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse.md)\n- [Amazon Bedrock vs Fireworks AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-fireworks-inference.md)\n- [Amazon Bedrock vs Gemini Developer API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api.md)\n- [Amazon Bedrock vs GroqCloud](https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq.md)\n- [Amazon Bedrock vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.md)\n- [Amazon Bedrock vs Inkling 2 Small](https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small.md)\n- [Amazon Bedrock vs Jais 3](https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3.md)\n- [Amazon Bedrock vs Meta Model API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.md)\n- [Amazon Bedrock vs MiniMax API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api.md)\n- [Amazon Bedrock vs Mistral AI API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-mistral-api.md)\n- [Amazon Bedrock vs Muse Ember](https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.md)\n- [Amazon Bedrock vs Muse Spark Open](https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-spark-open.md)\n- [Amazon Bedrock vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/amazon-bedrock-vs-nemotron-3-5-super-vl.md)\n- [Amazon Bedrock vs Novita AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai.md)\n- [Amazon Bedrock vs OpenAI API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.md)\n- [Amazon Bedrock vs OpenRouter](https://www.anchorterminal.com/compare/amazon-bedrock-vs-openrouter.md)\n- [Amazon Bedrock vs Prism Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-prism-inference.md)\n- [Amazon Bedrock vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router.md)\n- [Amazon Bedrock vs Beam 1.0](https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.md)\n- [Amazon Bedrock vs RouterPlus](https://www.anchorterminal.com/compare/amazon-bedrock-vs-routerplus.md)\n- [Amazon Bedrock vs SambaCloud](https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova.md)\n- [Amazon Bedrock vs SiliconFlow](https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.md)\n- [Amazon Bedrock vs Simplismart](https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.md)\n- [Amazon Bedrock vs StepFun API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api.md)\n- [Amazon Bedrock vs SWE-2 Flash](https://www.anchorterminal.com/compare/amazon-bedrock-vs-swe-2-flash.md)\n- [Amazon Bedrock vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/amazon-bedrock-vs-tencent-tokenhub.md)\n- [Amazon Bedrock vs Together AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.md)\n- [Amazon Bedrock vs Vercel AI Gateway](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.md)\n- [Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.md)\n- [Amazon Bedrock vs xAI API (Grok)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.md)\n- [Claude API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-carbon.md)\n- [Antseed vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-carbon.md)\n- [Azure OpenAI in Foundry Models vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-carbon.md)\n- [BlockRun.AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-carbon.md)\n- [Cerebras Inference vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-carbon.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 Mythos 5.2 vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-carbon.md)\n- [Cloudflare AI Gateway vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-carbon.md)\n- [Cloudflare Workers AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-carbon.md)\n- [Cohere Chat API (Command models) vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-carbon.md)\n- [DeepInfra vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-carbon.md)\n- [DeepSeek API vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-carbon.md)\n- [Eden AI vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-carbon.md)\n- [Glimpse vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-carbon.md)\n- [Fireworks AI Inference vs Gemini 4 Carbon](https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-carbon.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 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",
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    "description": "Amazon Bedrock scores 81.7 (A) to Gemini 4 Carbon's 62.6 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.",
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    "title": "Amazon Bedrock vs Gemini 4 Carbon for AI agents (2026)",
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