GPT-5 vs Mistral Medium 3.5
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
OpenAI · Aug 2025
OpenAI's August 2025 unified flagship that merged the GPT and o-series reasoning lines into one model with selectable effort.
Mistral AI · Mar 2026
Europe's strongest model line: frontier-adjacent quality at $0.40/$2 with EU data residency and on-prem options.
The verdict
These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: Mistral Medium 3.5 works out roughly 4.3x cheaper per blended million tokens. GPT-5 also takes 400K of context versus 131K for Mistral Medium 3.5.
Specs & pricing
| GPT-5 | Mistral Medium 3.5 | |
|---|---|---|
| modhub Index | 70.7 | — |
| Input price / 1M | $1.25 | $0.4 |
| Output price / 1M | $10 | $2 |
| Context window | 400K | 131K |
| Max output | 128K | — |
| Open weights | no | no |
| Reasoning model | yes | no |
| Multimodal input | text, image | text, image |
| Knowledge cutoff | Sep 2024 | Dec 2025 |
| Released | Aug 2025 | Mar 2026 |
| Example monthly cost* | $27.50 | $7.00 |
* 10M input + 1.5M output tokens per month at list prices, no caching. Green = better value on that row.
Frequently asked questions
- Which is better, GPT-5 or Mistral Medium 3.5?
- These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: Mistral Medium 3.5 works out roughly 4.3x cheaper per blended million tokens. GPT-5 also takes 400K of context versus 131K for Mistral Medium 3.5.
- Which is cheaper, GPT-5 or Mistral Medium 3.5?
- GPT-5 costs $1.25/$10 per million input/output tokens, while Mistral Medium 3.5 costs $0.4/$2. For a typical workload of 10M input and 1.5M output tokens per month, that's $27.50 versus $7.00.
- Which model is better for coding, GPT-5 or Mistral Medium 3.5?
- We don't yet track SWE-bench Verified results for both models; check their individual pages for coding-related scores.