Model comparison
Devstral Small 2505 vs Kimi K2.6
Kimi K2.6 is the stronger model overall, scoring 47.7 to 34.3 on the Noometry Index. Devstral Small 2505 costs 11× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Mistral AISummary
- They share 2 benchmarks with published results for both. Devstral Small 2505 scores higher in 0 categories and Kimi K2.6 in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.6 leads 40.5 to 19.7.
- The biggest single-benchmark swing is SciCode: 28.8% for Devstral Small 2505 and 53.5% for Kimi K2.6.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.95 / $4 for Kimi K2.6.
- Kimi K2.6 accepts more context: 262K tokens versus 128K.
Side by side
| Devstral Small 2505 | Kimi K2.6 | |
|---|---|---|
| Provider | Mistral AI | Moonshot AI |
| Noometry Index | 34.3 | 47.7 |
| Released | 2025-05-07 | 2026-04-20 |
| 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 | 51 |
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Category by category
Coding Kimi K2.6 leads
Devstral Small 2505: 38.9 (#166), Kimi K2.6: 50.7 (#43)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| SciCode | 28.8% | 53.5% |
| SWE-bench Verified | — | 76.7% |
| SWE-bench Verified (bash only) | 56.4% | — |
| LMArena WebDev | — | 1509 |
| WeirdML | — | 55.9% |
| LMArena Coding | — | 1488 |
| ALE-Bench | — | 1,093 |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, Kimi K2.6: 21.9 (#137)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| OSWorld 2.0 | — | 4.6% |
| ExploitBench | — | 18.4% |
| GBAEval | — | 0.9% |
| GDP.pdf | — | 12% |
| Vending-Bench 2 | — | 6,205 |
Reasoning Kimi K2.6 leads
Devstral Small 2505: 19.7 (#252), Kimi K2.6: 40.5 (#55)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| CritPt | 0% | 8% |
| Kagi LLM Benchmark | 37.7% | — |
| NYT Connections (extended) | — | 87.2% |
| Chess Puzzles | — | 26% |
| EBR-Bench | — | 2.4% |
| LMArena Hard Prompts | — | 1470 |
| Mystery Game Puzzles | — | 18% |
| DTBench | — | 90.9% |
| LMCA | — | 37.3% |
| Epoch Capabilities Index | — | 151.05 |
Math Not comparable
Devstral Small 2505: —, Kimi K2.6: 57.0 (#41)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 25.6% |
| MathArena Final-Answer Competitions | — | 72.9% |
| OTIS Mock AIME 2024-2025 | — | 96.1% |
| ProofBench | — | 16% |
| LMArena Math | — | 1475 |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Not comparable
Devstral Small 2505: —, Kimi K2.6: 54.0 (#54)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| GPQA Diamond | — | 90.8% |
| SimpleQA Verified | — | 34.9% |
| Vectara Hallucination Rate | — | 10.8% |
| LMArena Expert | — | 1491 |
Multimodal Not comparable
Devstral Small 2505: —, Kimi K2.6: 31.6 (#103)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| LMArena Vision | — | 1283 |
| Blueprint-Bench 2 | — | 3.9% |
| Furniture Assembly | — | 21.7% |
| LMArena Document | — | 1451 |
Multilingual Not comparable
Devstral Small 2505: —, Kimi K2.6: 54.9 (#37)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| LMArena Non-English | — | 1446 |
| LMArena Chinese | — | 1521 |
| LMArena French | — | 1471 |
| LMArena German | — | 1450 |
| LMArena Japanese | — | 1443 |
| LMArena Korean | — | 1427 |
| LMArena Russian | — | 1446 |
| LMArena Spanish | — | 1464 |
Instruction Following Not comparable
Devstral Small 2505: —, Kimi K2.6: 76.3 (#43)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| LMArena Instruction Following | — | 1451 |
Long Context Not comparable
Devstral Small 2505: —, Kimi K2.6: 44.9 (#52)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| LMArena Longer Query | — | 1468 |
Writing & Preference Not comparable
Devstral Small 2505: —, Kimi K2.6: 68.5 (#26)
| Benchmark | Devstral Small 2505 | Kimi K2.6 |
|---|---|---|
| LMArena Text | — | 1455 |
| LMArena Creative Writing | — | 1434 |
| EQ-Bench Creative Writing | — | 1725 |
| EQ-Bench 4 | — | 1202 |
| LMArena Multi-Turn | — | 1453 |
Frequently asked questions
Is Devstral Small 2505 better than Kimi K2.6?
Kimi K2.6 is the stronger model overall, scoring 47.7 to 34.3 on the Noometry Index. Devstral Small 2505 costs 11× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Which is cheaper, Devstral Small 2505 or Kimi K2.6?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Kimi K2.6 lists at $0.95 and $4.
Is Devstral Small 2505 or Kimi K2.6 better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.7 versus 38.9 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.6 does, with 262K tokens against 128K.
How many benchmarks do Devstral Small 2505 and Kimi K2.6 share?
2 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and Kimi K2.6 has 51.