GPT-5 mini vs Codestral
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-5 mini | Codestral |
|---|---|---|
| Provider | OpenAI | Mistral |
| Input Price (1M) | $0.25 | $0.30 |
| Output Price (1M) | $2.00 | $0.90 |
| Context Window | 128,000 | 256,000 |
Verdict
GPT-5 mini costs $0.25 per 1M input tokens and $2.00 per 1M output tokens. Codestral costs $0.30 per 1M input tokens and $0.90 per 1M output tokens. GPT-5 mini is 17% cheaper on input tokens than Codestral. For output tokens, Codestral is the more affordable option at $0.90/1M vs $2.00.
On context window, Codestral supports 256,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-5 mini
- ✓ You need the lowest input token cost ($ 0.25/1M)
- ✓ You are already integrated with OpenAI
When to choose Codestral
- ✓ Your workload is output-heavy — Codestral generates text cheaper
- ✓ You need a larger context window (256,000 tokens)
- ✓ You are already integrated with Mistral
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is GPT-5 mini cheaper than Codestral? ▼
GPT-5 mini is cheaper on input tokens at $0.25/1M vs $0.30/1M for Codestral — a 17% saving.
What is the context window of GPT-5 mini vs Codestral? ▼
GPT-5 mini has a 128,000-token context window. Codestral has a 256,000-token context window. Codestral supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-5 mini or Codestral? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GPT-5 mini is the cheaper option. For maximum context length, Codestral supports 256,000 tokens. Use the comparison table above to find the right fit for your workload.