Codestral vs o4-mini Deep Research
Codestral vs o4-mini Deep Research: Codestral is cheaper for input-heavy usage ($0.30/M vs $2.00/M input tokens), while o4-mini Deep Research is better for long-context tasks (200,000 tokens).
Direct answer: choose Codestral for lower token spend and choose o4-mini Deep Research when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Codestral
o4-mini Deep Research
Cost Differences
o4-mini Deep Research costs more than Codestral
Quick Recommendation
Winner for direct API pricing: Codestral. At the default workload, Codestral saves about $15.75/month ($191.625/year) versus o4-mini Deep Research.
Feature Comparison
| Feature | Codestral | o4-mini Deep Research |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Input Price | $0.30/1M tokens | $2.00/1M tokens |
| Output Price | $0.90/1M tokens | $8.00/1M tokens |
| Context Window | 128,000 tokens | 200,000 tokens |
| Max Output | 32,768 tokens | 32,768 tokens |
| Category | balanced | reasoning |
| Capabilities | textcode | textreasoningcode |
| Release Date | 7/30/2025 | 6/26/2025 |
Codestral vs o4-mini Deep Research: Which Should You Choose?
Choosing between Codestral and o4-mini Deep Research depends on your priorities: cost efficiency, context length, or raw capability. Codestral is the more affordable option at $0.30/1M input tokens — 85% cheaper than o4-mini Deep Research. Meanwhile, o4-mini Deep Research offers a significantly larger context window at 200,000 tokens vs 128,000 for Codestral.
These models come from different providers — Mistral AI and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Mistral AI, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Codestral is a balanced model while o4-mini Deep Research is reasoning. This means they're optimized for different workloads. o4-mini Deep Research targets more demanding workloads, while Codestral provides a cost-effective option for everyday tasks.
Output costs matter too. Codestral charges $0.90/1M output tokens vs $8.00 for o4-mini Deep Research. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Codestral has the edge here at $0.90/1M output tokens.
Best Use Cases
Choose Codestral when:
- • Budget is a primary concern
- • You're already using Mistral AI's API ecosystem
Choose o4-mini Deep Research when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (reasoning)
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
Codestral
- • Input pricing: $0.30/M tokens
- • Output pricing: $0.90/M tokens
- • Context window: 128,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Smaller context window than o4-mini Deep Research
o4-mini Deep Research
- • Input pricing: $2.00/M tokens
- • Output pricing: $8.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Higher input cost than Codestral
- • Higher output cost than Codestral
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Codestral (Mistral AI)
o4-mini Deep Research (OpenAI)
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Which is cheaper, Codestral or o4-mini Deep Research?▼
What is the context window difference between Codestral and o4-mini Deep Research?▼
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Which model has better overall pricing for heavy usage?▼
Where can I compare Mistral AI and OpenAI API pricing beyond this model matchup?▼
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