Head to head · LLM inference · October 2026 research run
Amazon Bedrock vs Meta Model API
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.
Best model APIs and inference for AI agents · All 830 models comparisons
Which one, for what
Best 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.
Ahead on
- Reliability, 80 against 40
- Schema & documentation, 94 against 60
- Agent ergonomics, 92 against 75
- Security & auth, 98 against 64
- Payments & pricing, 30 against 20
- Maintenance & community, 81 against 46
- Transparency & trust, 85 against 53
Also in its favour
- Agent-ready, a grade of BB or better
Watch for
An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone
Best 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.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
Muse Wonder is labelled a preview, and no deprecation policy or notice period was found
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Reliability Amazon Bedrock +40
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).
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.
Maintenance & community Amazon Bedrock +35
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.
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.
Schema & documentation Amazon Bedrock +34
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).
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.
Security & auth Amazon Bedrock +34
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.
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.
Transparency & trust Amazon Bedrock +32
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).
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.
Agent ergonomics Amazon Bedrock +17
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).
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.
Score by category
| Category | Weight this run | Amazon Bedrock | Meta Model API | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 80 | 40 | Amazon Bedrock +40 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 94 | 60 | Amazon Bedrock +34 |
| Agent ergonomics | 13%16.2 | 92 | 75 | Amazon Bedrock +17 |
| Security & auth | 14%17.5 | 98 | 64 | Amazon Bedrock +34 |
| Payments & pricing | 10%12.5 | 30 | 20 | Amazon Bedrock +10 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 81 | 46 | Amazon Bedrock +35 |
| Transparency & trust | 7%8.8 | 85 | 53 | Amazon Bedrock +32 |
| Negative events | ≤15 | 0 | 0 | |
| Total | A 81.7/100 | D 52.3/100 |
Facts side by side
| Fact | Amazon Bedrock | Meta Model API |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | Amazon Web Services | Meta |
| Hosted endpoint | https://bedrock-runtime.us-east-1.amazonaws.com | https://api.meta.ai/v1 |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| 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. |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-30 | 2026-10-12 |
| Terms last updated | 2026-10-01 | 2026-10-02 |
| Privacy policy last updated | 2026-05-18 | couldn't be read |
| Customer content may train models | yes, with an opt-out | yes |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | yes |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 21.8M npm/wk | none |
What the same task costs
| Task | Amazon Bedrock | Meta Model API |
|---|---|---|
| Research a product and write a sourced reportanthropic.claude-opus-5-5 on Amazon Bedrock, muse-wonder-1.0 on Meta Model API | $43.88 | $3.85 |
| Build a small four-page websiteanthropic.claude-opus-5-5 on Amazon Bedrock, muse-wonder-1.0 on Meta Model API | $10.03 | $1.67 |
| Find and fix a bug in a large codebaseanthropic.claude-opus-5-5 on Amazon Bedrock, muse-wonder-1.0 on Meta Model API | $2.16 | $0.37 |
Estimated from each listing's published prices, the same tasks as on the price index. Plans, minimums and free allowances aren't counted.
How the scores have moved
Amazon Bedrock
No score change since it was listed.
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.
Before you call either
Amazon Bedrock
- 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_modetononein 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 honourRetry-Afterwhen 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
modelLifecyclebefore pinning a model ID. Claude 3.x IDs in several Regions stop working on 13 November 2026 and requests don't redirect
Meta Model API
- Use
muse-wonder-1.0for long multi-step work andmuse-spark-1.3for cheaper, high-volume calls. Both take the same requests - Keep personal or confidential data away from
-contributormodel IDs. Meta may train on that content - Honour Retry-After on 429 and 503, which is 60 seconds for
service_overloaded, and checkGET 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 readMODEL_API_KEY - Leave
tool_choiceatauto. The docs saynoneandrequiredare not supported
Questions
Which is better for AI agents, Amazon Bedrock or Meta Model API?
Amazon Bedrock scores 81.7 (A) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.
Do Amazon Bedrock and Meta Model API need an API key?
Amazon Bedrock takes an API key or an OAuth sign-in. Meta Model API needs an API key.
Can an agent call Amazon Bedrock and Meta Model API without installing anything?
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.
Other comparisons with Amazon Bedrock or Meta Model API
- Amazon Bedrock vs Claude API
- Amazon Bedrock vs Antseed
- Amazon Bedrock vs Azure OpenAI in Foundry Models
- Amazon Bedrock vs BlockRun.AI
- Amazon Bedrock vs Cerebras Inference
- Amazon Bedrock vs Cloudflare AI Gateway
- Amazon Bedrock vs Cloudflare Workers AI
- Amazon Bedrock vs Cohere Chat API (Command models)
- Amazon Bedrock vs DeepInfra
- Amazon Bedrock vs DeepSeek API
- Amazon Bedrock vs Eden AI
- Amazon Bedrock vs Glimpse
- Amazon Bedrock vs Fireworks AI Inference
- Amazon Bedrock vs Gemini Developer API
- Amazon Bedrock vs GroqCloud
- Amazon Bedrock vs Hugging Face Inference Providers
- Amazon Bedrock vs Inkling 2 Small
- Amazon Bedrock vs Jais 3
- Amazon Bedrock vs MiniMax API
- Amazon Bedrock vs Mistral AI API
- Amazon Bedrock vs Muse Spark Open
- Amazon Bedrock vs Nemotron 3.5 Super VL
- Amazon Bedrock vs Novita AI
- Amazon Bedrock vs OpenAI API
- Amazon Bedrock vs OpenRouter
- Amazon Bedrock vs Prism Inference
- Amazon Bedrock vs Router.com (Ramp Router)
- Amazon Bedrock vs Beam 1.0
- Amazon Bedrock vs RouterPlus
- Amazon Bedrock vs SambaCloud
- Amazon Bedrock vs SiliconFlow
- Amazon Bedrock vs Simplismart
- Amazon Bedrock vs StepFun API
- Amazon Bedrock vs SWE-2 Flash
- Amazon Bedrock vs Tencent Cloud TokenHub
- Amazon Bedrock vs Together AI Inference
- Amazon Bedrock vs Vercel AI Gateway
- Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)
- Amazon Bedrock vs xAI API (Grok)
- Claude API vs Meta Model API
- Antseed vs Meta Model API
- Azure OpenAI in Foundry Models vs Meta Model API
- BlockRun.AI vs Meta Model API
- Cerebras Inference vs Meta Model API
- Cloudflare AI Gateway vs Meta Model API
- Cloudflare Workers AI vs Meta Model API
- Cohere Chat API (Command models) vs Meta Model API
- DeepInfra vs Meta Model API
- DeepSeek API vs Meta Model API
- Eden AI vs Meta Model API
- Glimpse vs Meta Model API
- Fireworks AI Inference vs Meta Model API
- Gemini Developer API vs Meta Model API
- GroqCloud vs Meta Model API
- Hugging Face Inference Providers vs Meta Model API
- Inkling 2 Small vs Meta Model API
- Jais 3 vs Meta Model API
- Meta Model API vs MiniMax API
- Meta Model API vs Mistral AI API
- Meta Model API vs Muse Spark Open
- Meta Model API vs Nemotron 3.5 Super VL
- Meta Model API vs Novita AI
- Meta Model API vs OpenAI API
- Meta Model API vs OpenRouter
- Meta Model API vs Prism Inference
- Meta Model API vs Router.com (Ramp Router)
- Meta Model API vs Beam 1.0
- Meta Model API vs RouterPlus
- Meta Model API vs SambaCloud
- Meta Model API vs SiliconFlow
- Meta Model API vs Simplismart
- Meta Model API vs StepFun API
- Meta Model API vs SWE-2 Flash
- Meta Model API vs Tencent Cloud TokenHub
- Meta Model API vs Together AI Inference
- Meta Model API vs Vercel AI Gateway
- Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)
- Meta Model API vs xAI API (Grok)
Machine-readable
- This page as Markdown
/compare/amazon-bedrock-vs-meta-model-api.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/amazon-bedrock.json·/api/v1/tools/meta-model-api.json - From a terminal
anchor compare amazon-bedrock meta-model-api(the CLI) - Over MCP
compare_tools {"a": "amazon-bedrock", "b": "meta-model-api"}at/mcp, no key