---
title: Amazon Bedrock
slug: amazon-bedrock
url: "https://toolweight.com/options/amazon-bedrock"
homepage: "https://aws.amazon.com/bedrock/"
categories: llm-apis
last_verified: 2026-06-24
license: CC-BY-4.0
---

# Amazon Bedrock

> Multi-vendor model access inside your existing AWS account

Bedrock is procurement infrastructure as much as inference: Anthropic, Meta, Mistral, Cohere and Amazon's own Nova models behind IAM, VPC endpoints, CloudWatch and an existing AWS contract. Model IDs are versioned and lifecycle-managed with published legacy and end-of-life stages. Feature parity with first-party APIs lags by weeks to months, and per-model pricing is set by AWS rather than the model vendor.

## Identity

|  |  |
| --- | --- |
| Name | Amazon Bedrock |
| Company | AWS |
| One-liner | Multi-vendor model access inside your existing AWS account |
| Site | https://aws.amazon.com/bedrock/ |
| Docs | https://docs.aws.amazon.com/bedrock/ |
| Founded | 2006 |
| Open source | No |
| Brand | https://toolweight.com/vendors/AWS |
| Compared in | 1 |

## Where it is compared

### [LLM APIs](https://toolweight.com/compare/llm-apis)
Ranked **#3 of 18** on default weights.
| Field | Value | Confidence | Verified | Source | Note |
| --- | --- | --- | --- | --- | --- |
| Flagship model | Multi-vendor, Claude Opus 4.8, Llama 4, Mistral, Nova Premier | Inferred | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html | Bedrock is a catalogue, not a model, so there is no vendor claim to make about a flagship. The models listed are a toolweight selection from the supported-models page, an editorial choice about what the catalogue is for, which is why this cell is graded inferred rather than vendor-claimed. Capability figures below describe Claude on Bedrock as the reference deployment except where a cell says otherwise. |
| Context window | 1,000,000 tokens | Inferred | 2026-06-24 | - | Input window for Claude on Bedrock; varies by model. |
| Max output | 128,000 tokens | Inferred | 2026-06-24 | - | For Claude on Bedrock, tracking the first-party output cap; varies by model across the catalogue. |
| Image input | ● | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-supported-models-features.html | - |
| Audio in/out | ◐ | Inferred | 2026-01-15 | - | Amazon's own Nova Sonic does speech-to-speech, but this row's reference deployment is Claude on Bedrock, which has no audio at all. Regraded to partial because the capability exists somewhere in the catalogue rather than on the model every other figure in this row describes, a catalogue capability, not a flagship one. |
| Open weights | ◐ | Inferred | 2026-01-15 | - | Hosts open-weight models (Llama, Mistral) alongside closed ones; publishes none of its own. |
| OpenAI-compat API | ○ | Inferred | 2026-06-24 | - | Uses the AWS SDK and SigV4 auth. Anthropic ships a dedicated Bedrock client rather than a base-URL swap. |
| TTFT p50 | - | Unknown | - | - | - |
| Output tok/s | - | Unknown | - | - | - |
| $/M input | - | Unknown | - | - | Set by AWS per model and not guaranteed to match first-party rates; Claude on Bedrock has historically tracked close to Anthropic list price. |
| $/M output | - | Unknown | - | - | - |
| $/M cache read | - | Unknown | - | - | - |
| Batch discount | 50 % | Inferred | 2026-01-15 | - | Bedrock batch inference is offered at a reduced rate for supported models. |
| Tool use | ● | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/tool-use.html | - |
| Schema output | ● | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/structured-output.html | Available for Claude on Bedrock; support varies by model. |
| Effort control | ● | Inferred | 2026-06-24 | - | - |
| Computer use | ● | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/computer-use.html | Beta for Claude on Bedrock, the same Claude computer-use beta the first-party row carries, driven by the same flagship model. Upgraded from partial so the two rows are graded on one rule: beta status alone does not make a yes into a partial, or Anthropic's own row would have to move too. |
| MCP support | ○ | Inferred | 2026-06-24 | - | The MCP connector is not available on Bedrock; wire MCP up client-side instead. |
| Cache TTL | 5 min default, 1 h option; explicit breakpoints only | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.html | Both TTLs are available, same as first-party, it is only the automatic top-level caching path that Bedrock does not offer, so every cache boundary here has to be placed by hand. |
| Continuity policy | The most contractual answer in the category. Bedrock model IDs are versioned and move through a published Active to Legacy to end-of-life lifecycle with dated notices in the console and documentation, and legacy versions keep serving existing workloads after a successor lands. The cost of that stability is lag: new features reach Bedrock weeks to months after the first-party API, and some never do. | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle.html | - |
| Notice period | - | Unknown | - | - | AWS publishes per-model EOL dates through the lifecycle process; no single fixed minimum window was confirmed. |
| Pinnable versions | ● | Vendor-claimed | 2026-06-24 | https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html | Versioned model IDs and inference-profile ARNs. |
| Zero retention | ● | Vendor-claimed | 2026-01-15 | https://docs.aws.amazon.com/bedrock/latest/userguide/data-protection.html | AWS does not store prompts or completions; model invocation logging is opt-in and lands in your own account. This stays a yes where Google's and Cohere's moved to partial because it is a documented, unconditional vendor statement rather than a property of one tier or one deployment mode. |
| Trains on your data | ○ | Vendor-claimed | 2026-01-15 | https://docs.aws.amazon.com/bedrock/latest/userguide/data-protection.html | - |
| AU region | ● | Inferred | 2026-01-15 | - | ap-southeast-2 (Sydney) serves frontier models; check per-model availability as it is not uniform across regions. |
| API since | 2023 | Inferred | - | - | - |
| Positioning | Frontier models inside your existing AWS security perimeter | Inferred | - | - | - |

**Verdict.** Choose Bedrock for procurement and governance, not capability. IAM, VPC endpoints, an existing contract, a Sydney region and a published model lifecycle are worth real money to regulated teams. Accept that you will be weeks or months behind on features, and that the MCP connector and automatic caching are simply not there.

## Alternatives

- [Qwen](https://toolweight.com/options/alibaba-qwen), Alibaba's model family, huge open-weight range, closed flagship
- [Anthropic](https://toolweight.com/options/anthropic), Claude models, built around long agentic runs and tool use
- [Cerebras](https://toolweight.com/options/cerebras), Wafer-scale inference, the fastest tokens per second available
- [Cohere](https://toolweight.com/options/cohere), Enterprise-focused models built for RAG and private deployment
- [DeepSeek](https://toolweight.com/options/deepseek), Frontier-adjacent models at a small fraction of Western prices
- [Fireworks AI](https://toolweight.com/options/fireworks-ai), Fast open-weight inference with strong structured-output support
- [Google Gemini](https://toolweight.com/options/google-gemini), Gemini via AI Studio for prototyping or Vertex AI for production
- [Groq](https://toolweight.com/options/groq), Custom LPU silicon serving open-weight models at extreme speed
- [Meta Llama](https://toolweight.com/options/meta-llama), Open-weight Llama models, hosted almost everywhere but Meta
- [Mistral AI](https://toolweight.com/options/mistral-ai), European lab with an open-weight lineage and EU-resident hosting
- [Moonshot AI](https://toolweight.com/options/moonshot-ai), Kimi models, open-weight agentic performance at low cost
- [OpenAI](https://toolweight.com/options/openai), GPT models plus audio, images and embeddings on one bill

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