Model comparison
Codestral vs Kimi K2.6
Kimi K2.6 is the stronger model overall, scoring 47.7 to 30.6 on the Noometry Index. Codestral costs 3.8× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Mistral AISummary
- They share 1 benchmark with published results for both. Codestral scores higher in 0 categories and Kimi K2.6 in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Kimi K2.6 leads 50.7 to 27.3.
- Codestral is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.95 / $4 for Kimi K2.6.
- Kimi K2.6 accepts more context: 262K tokens versus 256K.
- Kimi K2.6 has downloadable open weights; the other is API-only.
Side by side
| Codestral | Kimi K2.6 | |
|---|---|---|
| Provider | Mistral AI | Moonshot AI |
| Noometry Index | 30.6 | 47.7 |
| Released | 2024-05-29 | 2026-04-20 |
| Weights | Proprietary | Open |
| Context window | 256K | 262K |
| Max output | 8K | 262K |
| Input $ / M tokens | $0.30 | $0.95 |
| Output $ / M tokens | $0.90 | $4 |
| Results tracked | 7 | 51 |
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Category by category
Coding Kimi K2.6 leads
Codestral: 27.3 (#321), Kimi K2.6: 50.7 (#43)
| Benchmark | Codestral | Kimi K2.6 |
|---|---|---|
| ALE-Bench | 137.78 | 1,093 |
| SWE-bench Verified | — | 76.7% |
| Aider Polyglot | 11.1% | — |
| LMArena WebDev | — | 1509 |
| SciCode | — | 53.5% |
| WeirdML | — | 55.9% |
| BigCodeBench Instruct | 41.8% | — |
| LMArena Coding | — | 1488 |
| BigCodeBench Complete | 52.5% | — |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |
Agentic & Tool Use Not comparable
Codestral: —, Kimi K2.6: 21.9 (#137)
| Benchmark | Codestral | 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
Codestral: 19.8 (#251), Kimi K2.6: 40.5 (#55)
| Benchmark | Codestral | Kimi K2.6 |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | — |
| NYT Connections (extended) | — | 87.2% |
| CritPt | — | 8% |
| 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
Codestral: —, Kimi K2.6: 57.0 (#41)
| Benchmark | Codestral | 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
Codestral: —, Kimi K2.6: 54.0 (#54)
| Benchmark | Codestral | Kimi K2.6 |
|---|---|---|
| GPQA Diamond | — | 90.8% |
| SimpleQA Verified | — | 34.9% |
| Vectara Hallucination Rate | — | 10.8% |
| LMArena Expert | — | 1491 |
Multimodal Not comparable
Codestral: —, Kimi K2.6: 31.6 (#103)
| Benchmark | Codestral | Kimi K2.6 |
|---|---|---|
| LMArena Vision | — | 1283 |
| Blueprint-Bench 2 | — | 3.9% |
| Furniture Assembly | — | 21.7% |
| LMArena Document | — | 1451 |
Multilingual Not comparable
Codestral: —, Kimi K2.6: 54.9 (#37)
| Benchmark | Codestral | 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
Codestral: —, Kimi K2.6: 76.3 (#43)
| Benchmark | Codestral | Kimi K2.6 |
|---|---|---|
| LMArena Instruction Following | — | 1451 |
Long Context Not comparable
Codestral: —, Kimi K2.6: 44.9 (#52)
| Benchmark | Codestral | Kimi K2.6 |
|---|---|---|
| LMArena Longer Query | — | 1468 |
Writing & Preference Not comparable
Codestral: —, Kimi K2.6: 68.5 (#26)
| Benchmark | Codestral | 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 Codestral better than Kimi K2.6?
Kimi K2.6 is the stronger model overall, scoring 47.7 to 30.6 on the Noometry Index. Codestral costs 3.8× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Which is cheaper, Codestral or Kimi K2.6?
Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Kimi K2.6 lists at $0.95 and $4.
Is Codestral or Kimi K2.6 better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.7 versus 27.3 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.6 does, with 262K tokens against 256K.
How many benchmarks do Codestral and Kimi K2.6 share?
1 benchmark has published results for both models. Codestral has 7 scored results on Noometry and Kimi K2.6 has 51.