Mistral Large 3 vs o4-mini: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Mistral Large 3 (Mistral AI) and o4-mini (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Mar 8, 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 Large 3 at $12.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestMistral Large 3 | Mistral AI | $12.50 | $0.001250 | $5.00 | $7.50 | 62.1% | Alerts coming soon |
o4-mini | OpenAI | $33.00 | $0.003300 | $11.00 | $22.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Mistral Large 3 | o4-mini | Cheaper |
|---|---|---|---|
| Input (standard) | $0.50/M | $1.10/M | Mistral Large 3 |
| Output | $1.50/M | $4.40/M | Mistral Large 3 |
| Cached input | N/A | $0.28/M | — |
| Batch input | N/A | $0.55/M | — |
| Batch output | N/A | $2.20/M | — |
Prices last verified: 2026-03-08
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 Large 3Monthly | o4-miniMonthly | Mistral Large 3Per request | o4-miniPer request |
|---|---|---|---|---|
| 1K requests/mo | $1.25 | $3.30 | $0.001250 | $0.003300 |
| 10K requests/mo | $12.50 | $33.00 | $0.001250 | $0.003300 |
| 100K requests/mo | $125.00 | $330.00 | $0.001250 | $0.003300 |
| 1M requests/mo | $1,250.00 | $3,300.00 | $0.001250 | $0.003300 |
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 Large 3
by Mistral AI
- Code generation
- Content & copywriting
- RAG / Semantic search
Input / 1M tokens
$0.50/M
Output / 1M tokens
$1.50/M
Context window
262,144
Tier
premium
When to Choose o4-mini
by OpenAI
- Code generation
- Data extraction
Input / 1M tokens
$1.10/M
Output / 1M tokens
$4.40/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 Large 3 | o4-mini |
|---|---|---|
| Context window | 262,144 tokens | 200,000 tokens |
| Max output tokens | 8,192 tokens | 100,000 tokens |
| Performance tier | Premium | Reasoning |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | No | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 1,000 |
Mistral Large 3 notes
Major price reduction from original Mistral Large ($2/$6 -> $0.50/$1.50). Supports 80+ languages.
o4-mini notes
Configurable reasoning effort. Best budget reasoning model from OpenAI.
Frequently Asked Questions
Is Mistral Large 3 cheaper than o4-mini?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Mistral Large 3 costs $125.00/month versus $330.00/month for o4-mini — a 62% 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 3 or o4-mini?
Mistral Large 3 has a larger context window at 262,144 tokens, compared to 200,000 tokens for o4-mini. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Mistral Large 3 and o4-mini support the Batch API?
o4-mini supports the Batch API (50% discount for async processing), while Mistral Large 3 does not. If your workload tolerates up to 24-hour latency, routing to o4-mini with batch pricing could significantly cut costs versus Mistral Large 3's standard rate.
Which model offers better prompt caching?
o4-mini supports prompt caching at $0.28/M for cached input, while Mistral Large 3 does not offer prompt caching. For RAG applications or chatbots with large, repeated context, o4-mini's caching capability can substantially reduce effective costs.
What are the best use cases for Mistral Large 3 vs o4-mini?
Both models are well-suited for Code generation. Mistral Large 3 is particularly strong for Content & copywriting, RAG / Semantic search. o4-mini is favored for Data extraction. 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 3 vs o4-mini?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral Large 3 costs $0.001250 per request and o4-mini costs $0.003300 per request. At 100,000 requests/month, that translates to $125.00 and $330.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Mistral Large 3 vs o4-mini: Summary
When comparing Mistral Large 3 and o4-mini for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Mistral Large 3 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $125.00/month, compared to $330.00/month for o4-mini.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral Large 3 charges $0.50/M for input tokens and $1.50/M for output tokens. o4-mini charges $1.10/M input and $4.40/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 o4-mini but not Mistral Large 3. 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 Large 3 supports up to 262,144 tokens in a single request, versus 200,000 tokens for o4-mini. 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
See cost recommendations for workloads where Mistral Large 3 or o4-mini is recommended.