Model comparison
Devstral Small 2505 vs Kimi K2.7 Code
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 34.3 on the Noometry Index. Devstral Small 2505 costs 11× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. Devstral Small 2505 scores higher in 0 categories and Kimi K2.7 Code in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.7 Code leads 39.0 to 19.7.
- The biggest single-benchmark swing is SciCode: 28.8% for Devstral Small 2505 and 47.5% for Kimi K2.7 Code.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 128K.
Side by side
| Devstral Small 2505 | Kimi K2.7 Code | |
|---|---|---|
| Provider | Mistral AI | Moonshot AI |
| Noometry Index | 34.3 | 43.3 |
| Released | 2025-05-07 | 2026-06-12 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $0.10 | $0.95 |
| Output $ / M tokens | $0.30 | $4 |
| Results tracked | 4 | 19 |
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Category by category
Coding Kimi K2.7 Code leads
Devstral Small 2505: 38.9 (#166), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | Devstral Small 2505 | Kimi K2.7 Code |
|---|---|---|
| SciCode | 28.8% | 47.5% |
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| SWE-bench Verified (bash only) | 56.4% | — |
| LMArena WebDev | — | 1473 |
| WeirdML | — | 54.1% |
| ALE-Bench | — | 886.23 |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, Kimi K2.7 Code: 24.0 (#122)
| Benchmark | Devstral Small 2505 | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 5,083 |
Reasoning Kimi K2.7 Code leads
Devstral Small 2505: 19.7 (#252), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | Devstral Small 2505 | Kimi K2.7 Code |
|---|---|---|
| CritPt | 0% | 10% |
| SimpleBench | — | 57.9% |
| Kagi LLM Benchmark | 37.7% | — |
| Chess Puzzles | — | 21% |
| Surface Evolver Bench | — | 48.8% |
| Epoch Capabilities Index | — | 149.97 |
Math Not comparable
Devstral Small 2505: —, Kimi K2.7 Code: 52.9 (#48)
| Benchmark | Devstral Small 2505 | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 54% |
| FrontierMath Tier 4 | — | 12.2% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
Knowledge Not comparable
Devstral Small 2505: —, Kimi K2.7 Code: 53.5 (#57)
| Benchmark | Devstral Small 2505 | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | — | 87.9% |
| SimpleQA Verified | — | 36.5% |
Frequently asked questions
Is Devstral Small 2505 better than Kimi K2.7 Code?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 34.3 on the Noometry Index. Devstral Small 2505 costs 11× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Which is cheaper, Devstral Small 2505 or Kimi K2.7 Code?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is Devstral Small 2505 or Kimi K2.7 Code better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 38.9 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.7 Code does, with 262K tokens against 128K.
How many benchmarks do Devstral Small 2505 and Kimi K2.7 Code share?
2 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and Kimi K2.7 Code has 19.