Mistral: Mistral Medium 3.5 vs o3: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Mistral: Mistral Medium 3.5 (Mistral AI) and o3 (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified May 6, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
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Total API calls per month
Showing costs for 2 models. Cheapest: Mistral: Mistral Medium 3.5 at $52.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestMistral: Mistral Medium 3.5 | Mistral AI | $52.50 | $0.005250 | $15.00 | $37.50 | 12.5% | Alerts coming soon |
o3 | OpenAI | $60.00 | $0.006000 | $20.00 | $40.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Mistral: Mistral Medium 3.5 | o3 | Cheaper |
|---|---|---|---|
| Input (standard) | $1.50/M | $2.00/M | Mistral: Mistral Medium 3.5 |
| Output | $7.50/M | $8.00/M | Mistral: Mistral Medium 3.5 |
| Cached input | N/A | $0.50/M | — |
Prices last verified: 2026-03-06 – 2026-05-06
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.
| Volume | Mistral: Mistral Medium 3.5Monthly | o3Monthly | Mistral: Mistral Medium 3.5Per request | o3Per request |
|---|---|---|---|---|
| 1K requests/mo | $5.25 | $6.00 | $0.005250 | $0.006000 |
| 10K requests/mo | $52.50 | $60.00 | $0.005250 | $0.006000 |
| 100K requests/mo | $525.00 | $600.00 | $0.005250 | $0.006000 |
| 1M requests/mo | $5,250.00 | $6,000.00 | $0.005250 | $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 tokensWhen to Choose Mistral: Mistral Medium 3.5
by Mistral AI
- General chatbot
Input / 1M tokens
$1.50/M
Output / 1M tokens
$7.50/M
Context window
262,144
Tier
mid
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.
| Capability | Mistral: Mistral Medium 3.5 | o3 |
|---|---|---|
| Context window | 262,144 tokens | 200,000 tokens |
| Max output tokens | 4,096 tokens | 100,000 tokens |
| Performance tier | Mid | Reasoning |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API (50% discount) | No | No |
| Extended reasoning | Yes | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 1,000 |
o3 notes
State-of-the-art reasoning performance. Costs reflect internal thinking tokens. Price reduced significantly from launch.
Frequently Asked Questions
Is Mistral: Mistral Medium 3.5 cheaper than o3?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Mistral: Mistral Medium 3.5 costs $525.00/month versus $600.00/month for o3 — a 13% 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: Mistral Medium 3.5 or o3?
Mistral: Mistral Medium 3.5 has a larger context window at 262,144 tokens, compared to 200,000 tokens for o3. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Mistral: Mistral Medium 3.5 and o3 support the Batch API?
Neither Mistral: Mistral Medium 3.5 nor o3 currently supports a batch API with discounted pricing. For batch-eligible alternatives, consider models from OpenAI, Anthropic, or Google that include batch API support.
Which model offers better prompt caching?
o3 supports prompt caching at $0.50/M for cached input, while Mistral: Mistral Medium 3.5 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: Mistral Medium 3.5 vs o3?
Mistral: Mistral Medium 3.5 is best suited for General chatbot, while o3 is optimized for Code generation, Document summarization. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.
What is the cost per request for Mistral: Mistral Medium 3.5 vs o3?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral: Mistral Medium 3.5 costs $0.005250 per request and o3 costs $0.006000 per request. At 100,000 requests/month, that translates to $525.00 and $600.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Mistral: Mistral Medium 3.5 vs o3: Summary
When comparing Mistral: Mistral Medium 3.5 and o3 for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Mistral: Mistral Medium 3.5 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $525.00/month, compared to $600.00/month for o3.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral: Mistral Medium 3.5 charges $1.50/M for input tokens and $7.50/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: Mistral Medium 3.5. 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: Mistral: Mistral Medium 3.5 supports up to 262,144 tokens in a single request, versus 200,000 tokens for o3. 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.
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Relevant Use Cases
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