{ "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": 1486, "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": "2026-11-07T18:20:09.570975096Z", "lastOk": true, "lastStatus": 404, "lastMs": 339, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 269, "p95ms24h": 352, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "versions": [ { "registry": "npm", "name": "@aws-sdk/client-bedrock-runtime", "version": "3.1164.0", "seenAt": "2026-11-06T23:05:19.602032841Z" }, { "registry": "pypi", "name": "boto3", "version": "1.43.126", "released": "2026-11-06", "seenAt": "2026-11-06T23:05:17.831478687Z" } ], "githubStars": 229, "npmWeekly": 21825916, "pypiWeekly": 637851852, "securityTxt": { "url": "https://amazon.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-11-07T16:00:18.354437696Z" }, "llmsTxt": { "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:17.63045618Z" }, "pages": [ { "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:05:11.906374144Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "dce416908c57" } ], "updatedAt": "2026-11-07T18:20:09.570975096Z" } }, "answer": "Amazon Bedrock scores 81.7 (A) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.", "b": { "slug": "meta-model-api", "name": "Meta Model API", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai", "kind": "model", "category": "inference", "summary": "Meta Model API is Meta's pay-as-you-go API for its hosted Muse models, including Muse Wonder and Muse Spark, through OpenAI-style Responses and Chat Completions endpoints and an Anthropic-style Messages endpoint, plus image, speech and segmentation routes.", "url": "https://www.anchorterminal.com/tools/meta-model-api", "markdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/meta-model-api.json", "dns": "meta-model-api.grade.anchorterminal.com", "license": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "transports": [ "http" ], "remoteUrl": "https://api.meta.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer API key created on the API keys tab of the Model API dashboard after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team, are shown once and are revoked by deletion. No key scopes were found, and every key on a team shares the team's rate limits.", "pricing": "usage", "pricingNotes": "Muse Wonder is $4.00 per million input tokens, $0.20 cached and $20.00 per million output tokens, Standard mode only (checked 2026-10-12). Muse Spark is $1.25, $0.15 and $4.25, or $0.10, $0.002 and $0.20 in Contributor mode, where Meta may train on the content. Billed in arrears to a card. No free allowance was found.", "priceSummary": "from $1.25 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in dev.meta.ai/llms.txt, the pricing page, the API reference or the billing help pages, checked 12 October 2026. Usage is charged to a card at a payment threshold or on the 1st of each month.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-12" }, "docsUrl": "https://dev.meta.ai/docs/overview", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm", "image.generate", "image.edit", "speech.stt", "speech.streaming" ], "tags": [ "official", "hosted", "model", "usage-priced", "closed-source", "llms-txt", "multimodal", "streaming", "openai-compatible", "anthropic-compatible", "card-required" ], "lastRelease": "2026-10-12", "graded": true, "anchor": { "graded": true, "score": 52.3, "grade": "D", "agentReady": false, "rank": 989, "ranked": true, "rankOf": 1486, "categoryRank": 33, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.", "bestFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "strengths": [ "Muse Wonder and Muse Spark take text, image, video, audio and PDF input with a 1,048,576-token context window", "Per-token prices, per-model rate limits and rate-limit headers published without a login", "Content sent in Standard mode is not used to train Meta models, and training use is opt-in through `-contributor` model IDs", "Responses, Chat Completions and Messages endpoints, so the OpenAI and Anthropic SDKs work with a base-URL change", "llms.txt and a Markdown copy of every docs page, with an error guide that gives the Retry-After value for each retryable error" ], "weaknesses": [ "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found", "No free API allowance found, and billing is set up with a card", "No readable status history. The dev.meta.ai/status page showed \"Status information is unavailable\", and `/v1/status` reports only the current state", "`tool_choice` accepts only `auto`, so a call can't be forced or ruled out", "No OpenAPI file, batch endpoint or Model API changelog found, and API keys have no scopes" ], "agentNotes": [ "Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests", "Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content", "Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key", "Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`", "Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 64, "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": "2026-10-30", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl -X POST \"https://api.meta.ai/v1/responses\" \\\n -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"muse-spark-1.3\", \"input\": \"What is the capital of France?\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/meta-model-api" }, "sameCompany": [ "muse-spark-open", "muse-code", "muse-glimmer-30b" ], "area": "models", "unitPrices": [ { "item": "Muse Wonder input", "unit": "1m-tokens", "usd": 4, "note": "Standard mode, muse-wonder-1.0. No long-context premium." }, { "item": "Muse Wonder cached input", "unit": "1m-tokens", "usd": 0.2 }, { "item": "Muse Wonder output", "unit": "1m-tokens", "usd": 20 }, { "item": "Muse Spark input", "unit": "1m-tokens", "usd": 1.25, "note": "Standard mode, muse-spark-1.3, 1.2 and 1.1." }, { "item": "Muse Spark cached input", "unit": "1m-tokens", "usd": 0.15 }, { "item": "Muse Spark output", "unit": "1m-tokens", "usd": 4.25 }, { "item": "Muse Spark input, Contributor mode", "unit": "1m-tokens", "usd": 0.1, "note": "Meta may use the content to train its models." }, { "item": "Muse Spark output, Contributor mode", "unit": "1m-tokens", "usd": 0.2, "note": "Cached input is $0.002 per million tokens." }, { "item": "Web search grounding", "unit": "1k-requests", "usd": 2.5, "note": "Per 1,000 search queries, on top of token cost." }, { "item": "Muse Image generated image", "unit": "image", "usd": 0.01 } ], "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "meta.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": true, "terms": "https://dev.meta.ai/legal/terms-of-service", "privacy": "https://www.facebook.com/privacy/policy/", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The terms (last updated 9 October 2026) are an agreement with Meta Platforms, Inc., or Meta Platforms Ireland Limited for users in the European Region. The model card names the same two.", "The privacy field is the Meta Privacy Policy, which the terms link. www.facebook.com's robots.txt asks readers like ours not to fetch it, so it wasn't read. The terms also link a subprocessor list at forwork.meta.com/legal/mfw-subprocessor-list/ and the Meta Global Processor Terms, neither of which was read.", "The API answers at api.meta.ai, whose robots.txt disallows every path, so nothing there was requested.", "dev.meta.ai/status, linked from the site header and the error guide, opens a Model API Status page. On 4 November it showed \"Status information is unavailable\" to our reader, so no component or incident history was read. The documented `GET /v1/status` endpoint reports only the current state.", "No Model API changelog was found. The only changelog on dev.meta.ai is Muse Code's.", "dev.meta.ai/.well-known/security.txt returns 404. www.meta.ai's and www.facebook.com's robots.txt disallow ClaudeBot, so their security.txt files weren't read.", "developer.meta.com/ai/ redirects to dev.meta.ai." ], "score": 64 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/meta-model-api.json", "live": { "slug": "meta-model-api", "probe": { "target": "https://api.meta.ai/v1", "method": "get", "lastAt": "2026-11-07T18:20:39.224681736Z", "lastOk": true, "lastStatus": 404, "lastMs": 168, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 73, "p95ms24h": 200, "samples24h": 239, "samples30d": 6412, "days": [ { "date": "2026-10-12", "probes": 33, "ok": 33 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "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": 187, "ok": 187 } ] }, "securityTxt": { "url": "https://meta.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:02:03.890144289Z" }, "llmsTxt": { "url": "https://dev.meta.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:07.335168045Z" }, "domain": { "domain": "meta.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/meta.ai", "checkedAt": "2026-11-01T14:15:25.518716318Z" }, "pages": [ { "url": "https://dev.meta.ai/legal/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:02:46.050794947Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0ef10c66f1b3" } ], "updatedAt": "2026-11-07T18:20:39.224681736Z" } }, "edges": [ { "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": "No status page with readable component history. The error guide's dev.meta.ai/status link now opens a Model API Status page, which showed \"Status information is unavailable\" to our reader on 4 November, its content drawn by script that we don't request, and the documented `GET /v1/status` reports only the current state (0). No readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-wonder-1.0, 150 RPM and 3,000,000 TPM for the contributor variants, 600 background submissions a minute (15). 429 and 503 carry Retry-After (60 seconds for `service_overloaded` and `backend_unavailable`), with backoff-with-jitter guidance, rate-limit headers on every token response and a documented mid-stream `server_shutting_down` event to retry, a generation call read as stateless as gemini-api's (15). No SLA found, and the terms let Meta throttle or suspend access without notice (0). Muse Wonder is labelled a preview. Muse Spark 1.3 carries no preview label, but the API opened on 8 July 2026 as a public preview and we found no general-availability notice, so half (5 of 10, the 12 October partial, kept). 0 + 5 + 15 + 15 + 0 + 5 = 40." }, "scores": { "a": 80, "b": 40 } }, { "by": 35, "category": "maintenance", "leads": "amazon-bedrock", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. The last model or API change is 30 October 2026 (OpenAI model API support and cross-Region inference in GovCloud), after structured outputs for Claude on both endpoints on 18 October (30). Models launched since 7 September 2026 get a 6-month or 45-day Legacy period, but the legacy page, which promises at least 6 months in Legacy, lists Claude 3 Haiku, 3 Sonnet, 3.5 Sonnet, 3.5 Sonnet v2 and 3.7 Sonnet as Legacy from 10 or 13 October with end of life on 13 November in several Regions, about 34 days (6 of 12, down from 10). Six models reached end of life in the 90 days to 6 November on five dates, Command R and R+ on 19 August, Claude 3 Haiku on 10 September, Nova Sonic on 14 September, Nova Canvas and Nova Reel on 30 September and Claude Sonnet 4 on 14 October (3 of 8, down from 4). Dated document history several times a month, What's New and re:Post, with direct support on a paid plan (12 of 15). SDK issue replies not sampled (5 of 10). Current official SDKs, boto3 1.43.125 on 5 November and `@aws-sdk/client-bedrock-runtime` 3.1163.0 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later (10). Down from 86 on 6 October.", "b": "Model reading. Muse Wonder launched on 12 October 2026 (30). No deprecation policy or notice period found. All three Muse Spark versions are still served, so no retirement has tested one (0 of 12). Dated launches on the API since 6 August that we read, Muse Image on 25 August, Muse Voice Transcribe on 3 September and Muse Wonder on 12 October (8 of 8). Muse Code leaving beta on 31 August is a separate product and isn't counted. No Model API changelog. A help centre with support tickets, answered 'typically within two business days' by Meta's own account, which we didn't test (8 of 15). No SDK of Meta's own for the API (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46." }, "scores": { "a": 81, "b": 46 } }, { "by": 34, "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": "No OpenAPI or similar machine-readable contract found. The reference is Markdown pages with schema sections, and /openapi.json paths on dev.meta.ai return 404 (0). llms.txt at dev.meta.ai/llms.txt, and every docs page has a Markdown copy (10). The models page says when to choose Muse Wonder and when Muse Spark, and the tool-calling and structured-output guides state their limits, such as `tool_choice` only accepting `auto` and which schema keywords `strict` allows (16 of 20). JSON Schema tools and output, `reasoning_effort` an enum from minimal to max, a strict subset that returns 400 when violated, though `tool_choice` has one value (12 of 15). Curl, Python and TypeScript examples on each page and an error guide covering 400 to 504 with the error envelope, codes and a fix for each (15). Versioned model IDs (muse-spark-1.1 to 1.3, muse-wonder-1.0) and dated launch posts on the developer blog, but no API changelog (7 of 15). 0 + 10 + 16 + 12 + 15 + 7 = 60." }, "scores": { "a": 94, "b": 60 } }, { "by": 34, "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. Bearer keys per team, named, shown once and revoked by deletion, with rotation advice. No scopes, read-only keys or per-key limits found (20 of 30). The terms say Meta will not use Content submitted to the Standard Services to train Meta Models, and training applies only to the `-contributor` model IDs a caller picks. Content may still be used to develop and improve safety and security systems (17 of 20). Retention is 'as needed' for the service, the law, flagged violations and safety review, with no period stated. Zero data retention for qualified accounts through sales, with flagged content kept up to 2 years (10 of 15). The usage dashboard shows tokens and requests per day by model, with no per-key or per-call log found (5 of 15). No security.txt on dev.meta.ai. Meta's bug bounty at bugbounty.meta.com is named in the Muse Code SDK's security policy, and a security commitments page describes TLS 1.2 or later, PCI-DSS card handling and an ISMS, with no named certification for the API (12 of 20). 20 + 17 + 10 + 5 + 12 = 64." }, "scores": { "a": 98, "b": 64 } }, { "by": 32, "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": "Closed service with clear terms, under California law with AAA arbitration for Meta Platforms, Inc. and Irish law and courts for Meta Platforms Ireland Limited, with liability capped at the greater of 12 months of fees or $1,000. Muse Glimmer's open weights don't change the hosted service (15). The terms, the models page, the pricing page and the zero-retention help page agree that Standard content isn't used for training and Contributor content may be, but retention periods are not stated outside zero retention, and the privacy policy is Meta's general one (18 of 30). No deprecation policy or dated notices found, and the terms let Meta remove functionality without notice (0). A subprocessor list is linked from the terms but wasn't read, and no data locations were found (8 of 20). 15 + 18 + 0 + 8 = 41." }, "scores": { "a": 85, "b": 53 } }, { "by": 17, "category": "ergonomics", "leads": "amazon-bedrock", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Converse takes tools with `toolChoice` auto, any or a named tool and `strict: true`, but forced choice depends on the model behind it (17 of 20). Structured outputs on supported models only (13 of 15). Explicit and implicit prompt caching, cache reads at $0.20 per million on Opus 5.5, 0.05x input, with 5-minute and 1-hour TTLs (15). 1M-token context on Opus 5.5, Sonnet 5.5 and Nova 2 Lite, a judgement call since Bedrock has no default model (15). Batch at half price on supported models, but the pricing page shows none for Opus 5.5 or Sonnet 5.5, while Flex is half price on Nova (7 of 10). AWS SDKs in every major language plus token generators for Python, JavaScript and Java (10). Typed errors with recovery advice per code (15).", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls on all three endpoints, parallel calls, tool search with deferred loading, built-in web search and a computer-use tool, but `tool_choice` accepts only `auto`, so a call can't be forced or forbidden (15 of 20). Output constrained to the JSON Schema on every surface (15). Automatic prompt caching with no setup, and cached input at 5 per cent of the input price on Muse Wonder (15). 1,048,576-token context on Muse Wonder and every Muse Spark version, with no long-context premium (15). No batch endpoint or discount found. Background responses run asynchronously at the normal price (0). No SDK of Meta's own. The docs use the OpenAI and Anthropic SDKs against compatible endpoints, the same reading as StepFun (0). OpenAI-style error envelope with `type` and `code`, per-status fixes and named retryable codes (15). 15 + 15 + 15 + 15 + 0 + 0 + 15 = 75." }, "scores": { "a": 92, "b": 75 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Amazon Web Services", "b": "Meta", "name": "Vendor" }, { "a": "https://bedrock-runtime.us-east-1.amazonaws.com", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "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 service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-30", "b": "2026-10-12", "name": "Last release" }, { "a": "2026-10-01", "b": "2026-10-02", "name": "Terms last updated" }, { "a": "2026-05-18", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "yes", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "yes", "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": "21.8M npm/wk", "b": "none", "name": "Popularity" } ], "faq": [ { "answer": "Amazon Bedrock scores 81.7 (A) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.", "question": "Which is better for AI agents, Amazon Bedrock or Meta Model API?" }, { "answer": "Amazon Bedrock takes an API key or an OAuth sign-in. Meta Model API needs an API key.", "question": "Do Amazon Bedrock and Meta Model API need an API key?" }, { "answer": "Yes. Amazon Bedrock has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Meta Model API at https://api.meta.ai/v1.", "question": "Can an agent call Amazon Bedrock and Meta Model API without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 40", "Schema \u0026 documentation, 94 against 60", "Agent ergonomics, 92 against 75", "Security \u0026 auth, 98 against 64", "Payments \u0026 pricing, 30 against 20", "Maintenance \u0026 community, 81 against 46", "Transparency \u0026 trust, 85 against 53" ], "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": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "slug": "meta-model-api", "watchFor": "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found" } ], "history": { "amazon-bedrock": null, "meta-model-api": [ { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 52.5, "fromGrade": "D", "to": 52.3, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.3, "from": 52.2, "fromGrade": "D", "to": 52.5, "toGrade": "D" } ] }, "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-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": 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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-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", "title": "Amazon Bedrock vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.json", "title": "Claude API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.json", "title": "Antseed vs Meta Model API", "url": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.json", "title": "Azure OpenAI in Foundry Models vs Meta Model API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api" }, { "json": 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"https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api.json", "title": "Fireworks AI Inference vs Meta Model API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.json", "title": "Gemini Developer API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api.json", "title": "GroqCloud vs Meta Model API", "url": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api.json", "title": "Hugging Face Inference Providers vs Meta Model API", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-meta-model-api.json", "title": "Inkling 2 Small vs Meta Model API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.json", "title": "Jais 3 vs Meta Model API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-api.json", "title": "Meta Model API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.json", "title": "Meta Model API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.json", "title": "Meta Model API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl.json", "title": "Meta Model API vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.json", "title": "Meta Model API vs Novita AI", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json", "title": "Meta Model API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.json", "title": "Meta Model API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter" }, { "json": 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"https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json", "title": "Meta Model API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart.json", "title": "Meta Model API vs Simplismart", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.json", "title": "Meta Model API vs StepFun API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash.json", "title": "Meta Model API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub.json", "title": "Meta Model API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.json", "title": "Meta Model API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.json", "title": "Meta Model API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.json", "title": "Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.json", "title": "Meta Model API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api" } ], "panel": null, "scores": [ { "amazon-bedrock": 80, "by": 40, "edge": "amazon-bedrock", "key": "reliability", "meta-model-api": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "amazon-bedrock": 94, "by": 34, "edge": "amazon-bedrock", "key": "schema", "meta-model-api": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "amazon-bedrock": 92, "by": 17, "edge": "amazon-bedrock", "key": "ergonomics", "meta-model-api": 75, "name": "Agent ergonomics", "weight": 13 }, { "amazon-bedrock": 98, "by": 34, "edge": "amazon-bedrock", "key": "security", "meta-model-api": 64, "name": "Security \u0026 auth", "weight": 14 }, { "amazon-bedrock": 30, "by": 10, "edge": "amazon-bedrock", "key": "payments", "meta-model-api": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "amazon-bedrock": 81, "by": 35, "edge": "amazon-bedrock", "key": "maintenance", "meta-model-api": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "amazon-bedrock": 85, "by": 32, "edge": "amazon-bedrock", "key": "transparency", "meta-model-api": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Amazon Bedrock scores 81.7 (A) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category. Both do llm inference.", "tasks": [ { "a": "$43.88", "b": "$3.85", "cheaper": "meta-model-api", "task": "Research a product and write a sourced report", "what": "anthropic.claude-opus-5-5 on Amazon Bedrock, muse-wonder-1.0 on Meta Model API" }, { "a": "$10.03", "b": "$1.67", "cheaper": "meta-model-api", "task": "Build a small four-page website", "what": "anthropic.claude-opus-5-5 on Amazon Bedrock, muse-wonder-1.0 on Meta Model API" }, { "a": "$2.16", "b": "$0.37", "cheaper": "meta-model-api", "task": "Find and fix a bug in a large codebase", "what": "anthropic.claude-opus-5-5 on Amazon Bedrock, muse-wonder-1.0 on Meta Model API" } ], "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.", "meta-model-api": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api", "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.min.md" }, "markdown": "Amazon Bedrock scores 81.7 (A) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category. Both do llm inference.\n\n- Amazon Bedrock: grade A, 81.7/100, rank #8 of 1486. Markdown https://www.anchorterminal.com/tools/amazon-bedrock.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json\n- Meta Model API: grade D, 52.3/100, rank #989 of 1486. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 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 60\n- Agent ergonomics, 92 against 75\n- Security \u0026 auth, 98 against 64\n- Payments \u0026 pricing, 30 against 20\n- Maintenance \u0026 community, 81 against 46\n- Transparency \u0026 trust, 85 against 53\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### Meta Model API (D)\n\nGood for: Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.\n\nWatch for: Muse Wonder is labelled a preview, and no deprecation policy or notice period was found\n\n\n## Why the edge\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- Meta Model API (40): No status page with readable component history. The error guide's dev.meta.ai/status link now opens a Model API Status page, which showed \"Status information is unavailable\" to our reader on 4 November, its content drawn by script that we don't request, and the documented `GET /v1/status` reports only the current state (0). No readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-wonder-1.0, 150 RPM and 3,000,000 TPM for the contributor variants, 600 background submissions a minute (15). 429 and 503 carry Retry-After (60 seconds for `service_overloaded` and `backend_unavailable`), with backoff-with-jitter guidance, rate-limit headers on every token response and a documented mid-stream `server_shutting_down` event to retry, a generation call read as stateless as gemini-api's (15). No SLA found, and the terms let Meta throttle or suspend access without notice (0). Muse Wonder is labelled a preview. Muse Spark 1.3 carries no preview label, but the API opened on 8 July 2026 as a public preview and we found no general-availability notice, so half (5 of 10, the 12 October partial, kept). 0 + 5 + 15 + 15 + 0 + 5 = 40.\n\n### Maintenance \u0026 community: Amazon Bedrock +35\n\n- Amazon Bedrock (81): Model reading. The last model or API change is 30 October 2026 (OpenAI model API support and cross-Region inference in GovCloud), after structured outputs for Claude on both endpoints on 18 October (30). Models launched since 7 September 2026 get a 6-month or 45-day Legacy period, but the legacy page, which promises at least 6 months in Legacy, lists Claude 3 Haiku, 3 Sonnet, 3.5 Sonnet, 3.5 Sonnet v2 and 3.7 Sonnet as Legacy from 10 or 13 October with end of life on 13 November in several Regions, about 34 days (6 of 12, down from 10). Six models reached end of life in the 90 days to 6 November on five dates, Command R and R+ on 19 August, Claude 3 Haiku on 10 September, Nova Sonic on 14 September, Nova Canvas and Nova Reel on 30 September and Claude Sonnet 4 on 14 October (3 of 8, down from 4). Dated document history several times a month, What's New and re:Post, with direct support on a paid plan (12 of 15). SDK issue replies not sampled (5 of 10). Current official SDKs, boto3 1.43.125 on 5 November and `@aws-sdk/client-bedrock-runtime` 3.1163.0 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later (10). Down from 86 on 6 October.\n- Meta Model API (46): Model reading. Muse Wonder launched on 12 October 2026 (30). No deprecation policy or notice period found. All three Muse Spark versions are still served, so no retirement has tested one (0 of 12). Dated launches on the API since 6 August that we read, Muse Image on 25 August, Muse Voice Transcribe on 3 September and Muse Wonder on 12 October (8 of 8). Muse Code leaving beta on 31 August is a separate product and isn't counted. No Model API changelog. A help centre with support tickets, answered 'typically within two business days' by Meta's own account, which we didn't test (8 of 15). No SDK of Meta's own for the API (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46.\n\n### Schema \u0026 documentation: Amazon Bedrock +34\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- Meta Model API (60): No OpenAPI or similar machine-readable contract found. The reference is Markdown pages with schema sections, and /openapi.json paths on dev.meta.ai return 404 (0). llms.txt at dev.meta.ai/llms.txt, and every docs page has a Markdown copy (10). The models page says when to choose Muse Wonder and when Muse Spark, and the tool-calling and structured-output guides state their limits, such as `tool_choice` only accepting `auto` and which schema keywords `strict` allows (16 of 20). JSON Schema tools and output, `reasoning_effort` an enum from minimal to max, a strict subset that returns 400 when violated, though `tool_choice` has one value (12 of 15). Curl, Python and TypeScript examples on each page and an error guide covering 400 to 504 with the error envelope, codes and a fix for each (15). Versioned model IDs (muse-spark-1.1 to 1.3, muse-wonder-1.0) and dated launch posts on the developer blog, but no API changelog (7 of 15). 0 + 10 + 16 + 12 + 15 + 7 = 60.\n\n### Security \u0026 auth: Amazon Bedrock +34\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- Meta Model API (64): Model reading. Bearer keys per team, named, shown once and revoked by deletion, with rotation advice. No scopes, read-only keys or per-key limits found (20 of 30). The terms say Meta will not use Content submitted to the Standard Services to train Meta Models, and training applies only to the `-contributor` model IDs a caller picks. Content may still be used to develop and improve safety and security systems (17 of 20). Retention is 'as needed' for the service, the law, flagged violations and safety review, with no period stated. Zero data retention for qualified accounts through sales, with flagged content kept up to 2 years (10 of 15). The usage dashboard shows tokens and requests per day by model, with no per-key or per-call log found (5 of 15). No security.txt on dev.meta.ai. Meta's bug bounty at bugbounty.meta.com is named in the Muse Code SDK's security policy, and a security commitments page describes TLS 1.2 or later, PCI-DSS card handling and an ISMS, with no named certification for the API (12 of 20). 20 + 17 + 10 + 5 + 12 = 64.\n\n### Transparency \u0026 trust: Amazon Bedrock +32\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- Meta Model API (53): Closed service with clear terms, under California law with AAA arbitration for Meta Platforms, Inc. and Irish law and courts for Meta Platforms Ireland Limited, with liability capped at the greater of 12 months of fees or $1,000. Muse Glimmer's open weights don't change the hosted service (15). The terms, the models page, the pricing page and the zero-retention help page agree that Standard content isn't used for training and Contributor content may be, but retention periods are not stated outside zero retention, and the privacy policy is Meta's general one (18 of 30). No deprecation policy or dated notices found, and the terms let Meta remove functionality without notice (0). A subprocessor list is linked from the terms but wasn't read, and no data locations were found (8 of 20). 15 + 18 + 0 + 8 = 41.\n\n### Agent ergonomics: Amazon Bedrock +17\n\n- Amazon Bedrock (92): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Converse takes tools with `toolChoice` auto, any or a named tool and `strict: true`, but forced choice depends on the model behind it (17 of 20). Structured outputs on supported models only (13 of 15). Explicit and implicit prompt caching, cache reads at $0.20 per million on Opus 5.5, 0.05x input, with 5-minute and 1-hour TTLs (15). 1M-token context on Opus 5.5, Sonnet 5.5 and Nova 2 Lite, a judgement call since Bedrock has no default model (15). Batch at half price on supported models, but the pricing page shows none for Opus 5.5 or Sonnet 5.5, while Flex is half price on Nova (7 of 10). AWS SDKs in every major language plus token generators for Python, JavaScript and Java (10). Typed errors with recovery advice per code (15).\n- Meta Model API (75): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls on all three endpoints, parallel calls, tool search with deferred loading, built-in web search and a computer-use tool, but `tool_choice` accepts only `auto`, so a call can't be forced or forbidden (15 of 20). Output constrained to the JSON Schema on every surface (15). Automatic prompt caching with no setup, and cached input at 5 per cent of the input price on Muse Wonder (15). 1,048,576-token context on Muse Wonder and every Muse Spark version, with no long-context premium (15). No batch endpoint or discount found. Background responses run asynchronously at the normal price (0). No SDK of Meta's own. The docs use the OpenAI and Anthropic SDKs against compatible endpoints, the same reading as StepFun (0). OpenAI-style error envelope with `type` and `code`, per-status fixes and named retryable codes (15). 15 + 15 + 15 + 15 + 0 + 0 + 15 = 75.\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock | Meta Model API | 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 | 60 | Amazon Bedrock +34 |\n| Agent ergonomics | 13% (16.2 this run) | 92 | 75 | Amazon Bedrock +17 |\n| Security \u0026 auth | 14% (17.5 this run) | 98 | 64 | Amazon Bedrock +34 |\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 | 46 | Amazon Bedrock +35 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 53 | Amazon Bedrock +32 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **81.7 · A** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock | Meta Model API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Amazon Web Services | Meta |\n| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://api.meta.ai/v1` |\n| Transports | HTTP | 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 service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-10-12 |\n| Terms last updated | 2026-10-01 | 2026-10-02 |\n| Privacy policy last updated | 2026-05-18 | couldn't be read |\n| Customer content may train models | yes, with an opt-out | yes |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 21.8M npm/wk | none |\n\n## What the same task costs\n\n| Task | Amazon Bedrock | Meta Model API |\n| --- | --- | --- |\n| Research a product and write a sourced report | $43.88 | $3.85 |\n| Build a small four-page website | $10.03 | $1.67 |\n| Find and fix a bug in a large codebase | $2.16 | $0.37 |\n\n## How the scores have moved\n\n### Amazon Bedrock\n\nNo score change since it was listed.\n\n### Meta Model API\n\n- -0.2 on 30 October 2026: checklist\n- +0.3 on 27 October 2026: checklist\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**Meta Model API.** Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.\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### Meta Model API\n\n1. Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests\n2. Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content\n3. Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key\n4. Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`\n5. Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported\n\n## Questions\n\n### Which is better for AI agents, Amazon Bedrock or Meta Model API?\n\nAmazon Bedrock scores 81.7 (A) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.\n\n### Do Amazon Bedrock and Meta Model API need an API key?\n\nAmazon Bedrock takes an API key or an OAuth sign-in. Meta Model API needs an API key.\n\n### Can an agent call Amazon Bedrock and Meta Model API without installing anything?\n\nYes. Amazon Bedrock has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Meta Model API at https://api.meta.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"amazon-bedrock\", \"b\": \"meta-model-api\"}`. From a terminal: `anchor compare amazon-bedrock meta-model-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json and https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n\n## Other comparisons with Amazon Bedrock or Meta Model API\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 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 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 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 Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [Azure OpenAI in Foundry Models vs Meta Model API](https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [Cerebras Inference vs Meta Model API](https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.md)\n- [Cloudflare AI Gateway vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.md)\n- [Cloudflare Workers AI vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.md)\n- [Cohere Chat API (Command models) vs Meta Model API](https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.md)\n- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepSeek API vs Meta Model API](https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md)\n- [Eden AI vs Meta Model API](https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.md)\n- [Glimpse vs Meta Model API](https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api.md)\n- [Fireworks AI Inference vs Meta Model API](https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [Hugging Face Inference Providers vs Meta Model API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api.md)\n- [Inkling 2 Small vs Meta Model API](https://www.anchorterminal.com/compare/inkling-2-small-vs-meta-model-api.md)\n- [Jais 3 vs Meta Model API](https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.md)\n- [Meta Model API vs MiniMax API](https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-api.md)\n- [Meta Model API vs Mistral AI API](https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.md)\n- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Meta Model API vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl.md)\n- [Meta Model API vs Novita AI](https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.md)\n- [Meta Model API vs OpenAI API](https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.md)\n- [Meta Model API vs OpenRouter](https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.md)\n- [Meta Model API vs Prism Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.md)\n- [Meta Model API vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/meta-model-api-vs-ramp-router.md)\n- [Meta Model API vs Beam 1.0](https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.md)\n- [Meta Model API vs RouterPlus](https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus.md)\n- [Meta Model API vs SambaCloud](https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.md)\n- [Meta Model API vs SiliconFlow](https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.md)\n- [Meta Model API vs Simplismart](https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart.md)\n- [Meta Model API vs StepFun API](https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.md)\n- [Meta Model API vs SWE-2 Flash](https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash.md)\n- [Meta Model API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub.md)\n- [Meta Model API vs Together AI Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.md)\n- [Meta Model API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.md)\n- [Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.md)\n- [Meta Model API vs xAI API (Grok)](https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.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": "2026-11-07", "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": "Amazon Bedrock vs Meta Model API", "url": "" } ], "description": "Amazon Bedrock scores 81.7 (A) to Meta Model's 52.3 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Amazon Bedrock A 81.7", "Meta Model API D 52.3", "scores" ], "h1": "Amazon Bedrock vs Meta Model API", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/amazon-bedrock-vs-meta-model-api", "published": "2026-10-01", "section": "tools", "title": "Amazon Bedrock vs Meta Model for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api" }, "tokens": { "markdown": 7500, "slim": 3930 }, "version": 1 }