Mistral Small 4 vs GPT-4o mini
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Mistral Small 4 | GPT-4o mini |
|---|---|---|
| Provider | Mistral | OpenAI |
| Input Price (1M) | $0.15 | $0.15 |
| Output Price (1M) | $0.60 | $0.60 |
| Context Window | 131,000 | 128,000 |
Verdict
Mistral Small 4 costs $0.15 per 1M input tokens and $0.60 per 1M output tokens. GPT-4o mini costs $0.15 per 1M input tokens and $0.60 per 1M output tokens. Mistral Small 4 and GPT-4o mini have identical input token pricing. For output tokens, Mistral Small 4 is the more affordable option at $0.60/1M vs $0.60.
On context window, Mistral Small 4 supports 131,000 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 Mistral Small 4
- ✓ You need a larger context window (131,000 tokens)
- ✓ You are already integrated with Mistral
When to choose GPT-4o mini
- ✓ You are already integrated with OpenAI
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 Mistral Small 4 cheaper than GPT-4o mini? ▼
Mistral Small 4 and GPT-4o mini have identical input token pricing at $0.15/1M tokens.
What is the context window of Mistral Small 4 vs GPT-4o mini? ▼
Mistral Small 4 has a 131,000-token context window. GPT-4o mini has a 128,000-token context window. Mistral Small 4 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Mistral Small 4 or GPT-4o mini? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Mistral Small 4 is the cheaper option. For maximum context length, Mistral Small 4 supports 131,000 tokens. Use the comparison table above to find the right fit for your workload.