Model comparison
Devstral Small 2505 vs GPT-5-Codex
GPT-5-Codex is the stronger model overall, scoring 37.3 to 33.9 on the Noometry Index. Devstral Small 2505 costs 23× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Mistral AISummary
- They share 1 benchmark with published results for both. Devstral Small 2505 scores higher in 0 categories and GPT-5-Codex in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 19.1.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 37.7% for Devstral Small 2505 and 70.3% for GPT-5-Codex.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 128K.
- Devstral Small 2505 has downloadable open weights; the other is API-only.
Side by side
| Devstral Small 2505 | GPT-5-Codex | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 33.9 | 37.3 |
| Released | 2025-05-07 | 2025-09-15 |
| Weights | Open | Proprietary |
| Context window | 128K | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $0.10 | $1.25 |
| Output $ / M tokens | $0.30 | $10 |
| Results tracked | 4 | 3 |
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Category by category
Coding GPT-5-Codex leads
Devstral Small 2505: 38.6 (#160), GPT-5-Codex: 41.9 (#100)
| Benchmark | Devstral Small 2505 | GPT-5-Codex |
|---|---|---|
| SWE-bench Verified (bash only) | 56.4% | — |
| SciCode | 28.8% | — |
| WeirdML | — | 54.5% |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, GPT-5-Codex: 30.8 (#66)
| Benchmark | Devstral Small 2505 | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | — | 44.3% |
Reasoning GPT-5-Codex leads
Devstral Small 2505: 19.1 (#243), GPT-5-Codex: 30.0 (#80)
| Benchmark | Devstral Small 2505 | GPT-5-Codex |
|---|---|---|
| Kagi LLM Benchmark | 37.7% | 70.3% |
| CritPt | 0% | — |
Frequently asked questions
Is Devstral Small 2505 better than GPT-5-Codex?
GPT-5-Codex is the stronger model overall, scoring 37.3 to 33.9 on the Noometry Index. Devstral Small 2505 costs 23× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.
Which is cheaper, Devstral Small 2505 or GPT-5-Codex?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; GPT-5-Codex lists at $1.25 and $10.
Is Devstral Small 2505 or GPT-5-Codex better for coding?
GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 38.6 in the Noometry coding category.
Which has the bigger context window?
GPT-5-Codex does, with 400K tokens against 128K.
How many benchmarks do Devstral Small 2505 and GPT-5-Codex share?
1 benchmark has published results for both models. Devstral Small 2505 has 4 scored results on Noometry and GPT-5-Codex has 3.