GPT-5 vs Mistral Large
Pricing, benchmarks, and use case comparison
Quick take
- •GPT-5 is meaningfully stronger at cost efficiency (88 vs 66 on our capability index).
- •GPT-5 is 38% cheaper on input tokens, which compounds fast on high-volume or agentic workloads.
- •Mistral Large has a 128000 context window vs 400,000 tokens (128,000 max output) - better for whole-repo or long-document work.
Specs comparison
| GPT-5 | Mistral Large | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Type | Closed source | Closed source |
| Context window | 400,000 tokens (128,000 max output) | ✓128000 |
| Input / 1M tokens | ✓$1.25 | 2.00 |
| Output / 1M tokens | $10.00 | 6.00 |
| Release date | 2025-08 | 2024-02 |
Benchmarks
| Benchmark | GPT-5 | Mistral Large |
|---|---|---|
| SWE-bench Verified | 74.9% | - |
| AIME 2025 | 94.6% | - |
| GPQA (GPT-5 pro) | 88.4% | - |
| MMLU | - | 84.0% |
| HumanEval | - | 92.0% |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose GPT-5 if...
- →You want strong reasoning at the lowest frontier-model price
- →Existing GPT-5-based systems that are already tuned and validated
- →General coding, math, and reasoning workloads on a budget
Choose Mistral Large if...
- →You need a strong European-built flagship with open weights
- →Your work is multilingual or requires nuanced reasoning
- →You want structured/JSON output and solid coding ability
- →You need the option to self-host for data sovereignty