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Mistral Large (Bedrock) vs o3: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Mistral Large (Bedrock) (AWS Bedrock) and o3 (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Mar 11, 2026

Interactive Cost Calculator

AWS BedrockMistral Large (Bedrock)OpenAIo3

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: o3 at $60.00/month.

Cheapest: o3 at $60.00/mo — save 40.0% vs Mistral Large (Bedrock)
Alert
Besto3
OpenAI$60.00$0.006000$20.00$40.0040.0%Alerts coming soon
Mistral Large (Bedrock)
AWS Bedrock$100.00$0.010000$40.00$60.00Alerts coming soon

Monthly Cost Comparison

Price Comparison at a Glance

All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.

Pricing TypeMistral Large (Bedrock)o3Cheaper
Input (standard)$4.00/M$2.00/Mo3
Output$12.00/M$8.00/Mo3
Cached inputN/A$0.50/M

Prices last verified: 2026-03-06 – 2026-03-11

Cost Breakdown by Usage Volume

Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.

VolumeMistral Large (Bedrock)Monthlyo3MonthlyMistral Large (Bedrock)Per requesto3Per request
1K requests/mo$10.00$6.00$0.010000$0.006000
10K requests/mo$100.00$60.00$0.010000$0.006000
100K requests/mo$1,000.00$600.00$0.010000$0.006000
1M requests/mo$10,000.00$6,000.00$0.010000$0.006000

Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.

Price History

Input price per 1M tokens

When to Choose Mistral Large (Bedrock)

by AWS Bedrock

  • Code generation
  • Content Creation
  • Summarization

Input / 1M tokens

$4.00/M

Output / 1M tokens

$12.00/M

Context window

128,000

Tier

premium

When to Choose o3

by OpenAI

  • Code generation
  • Document summarization

Input / 1M tokens

$2.00/M

Output / 1M tokens

$8.00/M

Context window

200,000

Tier

reasoning

Key Differences Beyond Price

Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.

CapabilityMistral Large (Bedrock)o3
Context window128,000 tokens200,000 tokens
Max output tokens8,192 tokens100,000 tokens
Performance tierPremiumReasoning
Vision / image inputNoYes
Function callingYesYes
JSON modeYesYes
Prompt cachingNoYes
Batch API (50% discount)YesNo
Extended reasoningNoYes
Fine-tuningNoNo
Rate limit (req/min)Not published1,000

Mistral Large (Bedrock) notes

Mistral Large via AWS Bedrock. Strong multilingual performance. Useful for enterprises already on AWS that need Mistral's capabilities with native AWS security.

o3 notes

State-of-the-art reasoning performance. Costs reflect internal thinking tokens. Price reduced significantly from launch.

Frequently Asked Questions

Is Mistral Large (Bedrock) cheaper than o3?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), o3 costs $600.00/month versus $1,000.00/month for Mistral Large (Bedrock) — a 40% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.

Which model has a larger context window, Mistral Large (Bedrock) or o3?

o3 has a larger context window at 200,000 tokens, compared to 128,000 tokens for Mistral Large (Bedrock). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.

Do Mistral Large (Bedrock) and o3 support the Batch API?

Mistral Large (Bedrock) supports the Batch API (50% discount for async processing), while o3 does not. If your workload tolerates up to 24-hour latency, routing to Mistral Large (Bedrock) with batch pricing could significantly cut costs versus o3's standard rate.

Which model offers better prompt caching?

o3 supports prompt caching at $0.50/M for cached input, while Mistral Large (Bedrock) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, o3's caching capability can substantially reduce effective costs.

What are the best use cases for Mistral Large (Bedrock) vs o3?

Both models are well-suited for Code generation. Mistral Large (Bedrock) is particularly strong for Content Creation, Summarization. o3 is favored for Document summarization. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.

What is the cost per request for Mistral Large (Bedrock) vs o3?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral Large (Bedrock) costs $0.010000 per request and o3 costs $0.006000 per request. At 100,000 requests/month, that translates to $1,000.00 and $600.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Mistral Large (Bedrock) vs o3: Summary

When comparing Mistral Large (Bedrock) and o3 for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. o3 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $600.00/month, compared to $1,000.00/month for Mistral Large (Bedrock).

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral Large (Bedrock) charges $4.00/M for input tokens and $12.00/M for output tokens. o3 charges $2.00/M input and $8.00/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.

Prompt caching is supported by o3 but not Mistral Large (Bedrock). For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.

Context window capacity differs between the two: o3 supports up to 200,000 tokens in a single request, versus 128,000 tokens for Mistral Large (Bedrock). A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.

Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Mistral Large (Bedrock) or o3 is recommended.