Amazon Bedrock vs Microsoft Foundry: pricing, features and which to choose

Plans, prices, deployment options, strengths and limits for Amazon Bedrock vs Microsoft Foundry, taken from each company's pricing page, docs and changelog. Updated October 2026.

Amazon BedrockMicrosoft Foundry
Amazon Bedrock logo

Amazon Bedrock

Coding AI Tools

Amazon Bedrock is AWS's managed service for generative AI. It offers foundation models from Anthropic, Amazon, Meta, Mistral, OpenAI, DeepSeek and others through one API, plus Knowledge Bases for RAG, Guardrails, fine-tuning and AgentCore for running agents in production. Pricing is pay as you go per token, with batch discounts and provisioned throughput for steady workloads.

Microsoft Foundry logo

Microsoft Foundry

Coding AI Tools

Microsoft Foundry, formerly Azure AI Foundry, is Microsoft's Azure platform for building AI apps and agents. It offers more than 11,000 models, including OpenAI's GPT family and Anthropic's Claude, plus Foundry Agent Service, Foundry IQ for grounding, tools through MCP, evaluations and governance. You pay for model tokens and Azure resources, and creating prompt-based agents carries no extra charge.

Quick comparison

FeatureAmazon BedrockMicrosoft Foundry
CategoryCoding AI ToolsCoding AI Tools
Main useFoundation model APIAI agent platform
Pricing modelPay per usePay per use
Free plan No Yes
Entry paid plan50% off on-demand (Batch)Per token (Foundry Models)
PlatformsAWS cloudAzure cloud
Open source No No
Self-hosted No No
Public API Yes Yes
Profile updatedOctober 2026October 2026

Pricing plans

Every public plan, as listed on each company's pricing page.

Amazon Bedrock

  • On-demandPer token

    Pay per input and output token; rates vary by model and region.

  • Batch50% off on-demand

    Select models; prompts in one file, results to S3.

  • Provisioned ThroughputPer model unit hour

    No commitment, 1-month or 6-month terms; needed for custom models.

  • AgentCoreUsage

    Runtime $0.0895/vCPU-hour; web search $7 per 1,000 queries.

Microsoft Foundry

  • Foundry ModelsPer token

    Rates vary by model and deployment; GPT-6.1 Sol $2 in, $10 out per 1M.

  • Foundry Agent Service$0 platform fee

    Prompt agents free to create and run; pay for tokens and tools.

  • Hosted agentsPer container hour

    Agents built with open source frameworks on managed compute.

  • Provisioned throughputPTU reservations

    Reserved capacity for steady, high-volume workloads.

Strengths and limits

Amazon Bedrock

  • Claude, Nova, Llama, GPT and more in one API.
  • AWS security, IAM and private networking.
  • Knowledge Bases and Guardrails built in.
  • AgentCore runs agents from any framework.
  • AWS console has a learning curve.
  • Costs spread across many services.
  • Model availability varies by region.

Microsoft Foundry

  • More than 11,000 models listed.
  • OpenAI and Claude models on one platform.
  • No platform fee for prompt agents.
  • Entra, Defender and Microsoft 365 integration.
  • Azure portal and quotas are complex.
  • Frequent product renames confuse docs.
  • Prices vary by region and deployment.

Which should you choose?

Choose Amazon Bedrock if

  • Teams already building on AWS.
  • Enterprises needing data to stay in their account.
  • Comparing many models through one API.
  • Running production agents with AgentCore.

Look elsewhere if

  • Hobbyists wanting a simple chat app.
  • Teams outside the AWS cloud.
  • Buyers wanting one flat monthly price.

Choose Microsoft Foundry if

  • Organizations standardized on Azure.
  • Teams wanting GPT and Claude in one place.
  • Agents published to Teams and Microsoft 365.
  • Enterprises with strict data residency rules.

Look elsewhere if

  • Developers outside the Azure cloud.
  • Hobbyists wanting a simple API key.
  • Teams wanting predictable flat pricing.

Amazon Bedrock logo Amazon Bedrock in brief

Amazon Bedrock is part of Amazon Web Services and became generally available in 2023. It is built for developers and enterprises that want to use large language models inside their AWS accounts, with the same identity, networking, logging and compliance controls they use for other AWS services. Data sent to Bedrock stays in the customer's AWS environment and, according to AWS, is not used to train the underlying models. Customers range from startups to banks, healthcare companies and governments, and Bedrock is a common choice for teams that already run their applications on AWS and want one bill, one security model and private network access to models.

The model catalog is Bedrock's main draw. AWS lists models from AI21 Labs, Amazon, Anthropic, Cohere, DeepSeek, Google's Gemma, Luma AI, Meta, MiniMax, Mistral AI, Moonshot AI, NVIDIA, OpenAI, Qwen, Stability AI, TwelveLabs, Writer, xAI and Z.AI. That includes Anthropic's Claude family, Amazon's own Nova models for text, speech, images and video, Meta's Llama, OpenAI's GPT and open-weight gpt-oss models, and image models from Stability AI. Developers call them through the Converse API with the same code, so swapping models takes a parameter change. The Playground in the console lets teams compare prompts across models before writing code.

Bedrock's strengths are a broad model catalog under one API, AWS security, private networking and compliance, data that stays in your account, and mature tooling for RAG, guardrails and agents through AgentCore. Its weaknesses are AWS console complexity, pricing that spreads across many services, regional differences in model availability and slower access to some newest models than each lab's own API. Google Vertex AI is the Google Cloud equivalent. Microsoft Foundry serves Azure customers with OpenAI, Claude and thousands of other models. Hugging Face hosts open models. OpenRouter routes across providers with one key. Choose Bedrock if your stack already runs on AWS.

Read the full Amazon Bedrock review

Microsoft Foundry logo Microsoft Foundry in brief

Microsoft Foundry is the successor to Azure AI Studio and Azure AI Foundry, and Microsoft calls it its AI app and agent factory. It serves developers and enterprises building on Azure, especially companies that already use Microsoft 365, Entra ID, Fabric and Azure security tools. The portal at ai.azure.com, SDKs and a Visual Studio Code extension cover the full cycle: choose a model, ground it in company data, build an agent, evaluate it and monitor it in production. Because it runs inside Azure subscriptions, usage counts toward existing Azure commitments, and Microsoft's regional and data zone deployments help with data residency requirements in the US, Europe and Asia Pacific.

Foundry Models gives access to more than 11,000 models, according to Microsoft's pricing page. That includes OpenAI models, which Microsoft hosts on Azure, such as the GPT-6 family that reached general availability in September 2026, plus Microsoft's own MAI models, Meta's Llama, Mistral, DeepSeek, xAI's Grok and many open models from Hugging Face. Since November 2025 Anthropic's Claude models have also been available in Foundry, which Microsoft says made Azure the only cloud offering both Claude and GPT frontier models. Teams can benchmark models side by side, use a model router that picks a model per request and fine-tune or distill models through Azure Machine Learning.

Microsoft Foundry's strengths are the largest model catalog among the big clouds, first-party hosting of OpenAI models, Claude and GPT on one platform, deep Microsoft 365 and Entra integration, and agent tooling with MCP and governance built in. Its weaknesses are Azure complexity, frequent renaming that confuses documentation, pricing that changes by region and deployment type, and quotas that can limit access to new models. Amazon Bedrock is the AWS counterpart. Google Vertex AI leads with Gemini on Google Cloud. Microsoft Copilot Studio offers low-code agents for business users. Hugging Face hosts open models. Choose Foundry if your organization runs on Azure and Microsoft 365.

Read the full Microsoft Foundry review

Frequently asked questions

How do Amazon Bedrock vs Microsoft Foundry compare on price?

Amazon Bedrock has no free plan, and its first paid plan (Batch) is listed at 50% off on-demand. Microsoft Foundry has a free option, and its first paid plan (Foundry Models) is listed at Per token. Prices are from each company's pricing page and can change, so check before you buy.

Which has a free plan, Amazon Bedrock vs Microsoft Foundry?

Microsoft Foundry offers a free plan or free self-hosted use. Amazon Bedrock requires a paid plan.

Can I self-host or integrate Amazon Bedrock vs Microsoft Foundry?

None of them is open source. All of them run as hosted services only. Amazon Bedrock and Microsoft Foundry offer a public API.

How much does Amazon Bedrock cost?

Bedrock has no subscription. On-demand inference bills per input and output token, at rates that vary by model and region. AWS says batch inference for select models costs 50% less. Provisioned Throughput bills per model unit hour, with optional one-month or six-month terms, and AgentCore services have their own usage rates.

Which models are on Amazon Bedrock?

AWS lists models from Anthropic, Amazon, Meta, Mistral AI, OpenAI, DeepSeek, Cohere, AI21 Labs, Qwen, Stability AI, xAI, Writer, NVIDIA, TwelveLabs, Luma AI, MiniMax, Moonshot AI, Z.AI and Google's Gemma. That includes the Claude family, Amazon Nova, Llama, GPT and gpt-oss models. Availability varies by region.

Is Azure AI Foundry the same as Microsoft Foundry?

Yes. Microsoft renamed Azure AI Studio to Azure AI Foundry and then to Microsoft Foundry. The portal remains at ai.azure.com, and older documentation, SDK names and blog posts still use the earlier names. The platform covers Foundry Models, Foundry Agent Service, Foundry IQ, Foundry Tools and Foundry Control Plane.

How much does Microsoft Foundry cost?

There is no platform subscription. You pay for model tokens, tools and Azure resources. Microsoft says creating and running prompt-based agents in Foundry Agent Service has no extra charge beyond those costs. Hosted agents bill per container hour, and provisioned throughput units reserve capacity for high-volume workloads.

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