Model comparison
Kimi K2.6 vs Mistral Large 3
Kimi K2.6 is the stronger model overall, scoring 47.7 to 39.1 on the Noometry Index. Mistral Large 3 costs 4.6× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. Kimi K2.6 scores higher in 8 categories and Mistral Large 3 in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.6 leads 40.5 to 15.2.
- The biggest single-benchmark swing is NYT Connections (extended): 87.2% for Kimi K2.6 and 7.5% for Mistral Large 3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.95 / $4 for Kimi K2.6.
Side by side
| Kimi K2.6 | Mistral Large 3 | |
|---|---|---|
| Provider | Moonshot AI | Mistral AI |
| Noometry Index | 47.7 | 39.1 |
| Released | 2026-04-20 | 2025-12-02 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 262K | 8K |
| Input $ / M tokens | $0.95 | $0.25 |
| Output $ / M tokens | $4 | $0.75 |
| Results tracked | 51 | 24 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Kimi K2.6 leads
Kimi K2.6: 50.7 (#43), Mistral Large 3: 34.4 (#237)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1509 | 1230 |
| LMArena Coding | 1488 | 1448 |
| SWE-bench Verified | 76.7% | — |
| SciCode | 53.5% | — |
| WeirdML | 55.9% | — |
| ALE-Bench | 1,093 | — |
Agentic & Tool Use Not comparable
Kimi K2.6: 21.9 (#137), Mistral Large 3: —
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| OSWorld 2.0 | 4.6% | — |
| ExploitBench | 18.4% | — |
| GBAEval | 0.9% | — |
| GDP.pdf | 12% | — |
| Vending-Bench 2 | 6,205 | — |
Reasoning Kimi K2.6 leads
Kimi K2.6: 40.5 (#55), Mistral Large 3: 15.2 (#319)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| NYT Connections (extended) | 87.2% | 7.5% |
| LMArena Hard Prompts | 1470 | 1429 |
| Kagi LLM Benchmark | — | 50.9% |
| CritPt | 8% | — |
| Chess Puzzles | 26% | — |
| Thematic Generalization | — | 23% |
| EBR-Bench | 2.4% | — |
| Mystery Game Puzzles | 18% | — |
| DTBench | 90.9% | — |
| LMCA | 37.3% | — |
| Epoch Capabilities Index | 151.05 | — |
Math Kimi K2.6 leads
Kimi K2.6: 57.0 (#41), Mistral Large 3: 38.7 (#129)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1475 | 1414 |
| 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% | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge Kimi K2.6 leads
Kimi K2.6: 54.0 (#54), Mistral Large 3: 36.0 (#177)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 10.8% | 14.5% |
| LMArena Expert | 1491 | 1421 |
| GPQA Diamond | 90.8% | — |
| SimpleQA Verified | 34.9% | — |
Multimodal Mistral Large 3 leads
Kimi K2.6: 31.6 (#103), Mistral Large 3: 38.2 (#66)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1283 | 1221 |
| Blueprint-Bench 2 | 3.9% | — |
| Furniture Assembly | 21.7% | — |
| LMArena Document | 1451 | — |
Multilingual Kimi K2.6 leads
Kimi K2.6: 54.9 (#37), Mistral Large 3: 52.5 (#84)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1446 | 1413 |
| LMArena Chinese | 1521 | 1447 |
| LMArena French | 1471 | 1455 |
| LMArena German | 1450 | 1437 |
| LMArena Japanese | 1443 | 1394 |
| LMArena Korean | 1427 | 1384 |
| LMArena Russian | 1446 | 1411 |
| LMArena Spanish | 1464 | 1440 |
Instruction Following Kimi K2.6 leads
Kimi K2.6: 76.3 (#43), Mistral Large 3: 74.0 (#108)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1403 |
Long Context Kimi K2.6 leads
Kimi K2.6: 44.9 (#52), Mistral Large 3: 43.1 (#105)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1468 | 1413 |
Writing & Preference Kimi K2.6 leads
Kimi K2.6: 68.5 (#26), Mistral Large 3: 60.0 (#101)
| Benchmark | Kimi K2.6 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1455 | 1428 |
| LMArena Creative Writing | 1434 | 1386 |
| EQ-Bench Creative Writing | 1725 | 1412 |
| LMArena Multi-Turn | 1453 | 1429 |
| EQ-Bench 4 | 1202 | — |
Frequently asked questions
Is Kimi K2.6 better than Mistral Large 3?
Kimi K2.6 is the stronger model overall, scoring 47.7 to 39.1 on the Noometry Index. Mistral Large 3 costs 4.6× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Which is cheaper, Kimi K2.6 or Mistral Large 3?
Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; Kimi K2.6 lists at $0.95 and $4.
Is Kimi K2.6 or Mistral Large 3 better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.7 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Kimi K2.6 and Mistral Large 3 share?
22 benchmarks have published results for both models. Kimi K2.6 has 51 scored results on Noometry and Mistral Large 3 has 24.