Model comparison
Kimi K2.7 Code vs Mistral Large
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 31.9 on the Noometry Index.
Last verified . 7 shared benchmarks.
Mistral AISummary
- They share 7 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Mistral Large in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.9 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 8.5% for Mistral Large.
- Kimi K2.7 Code is cheaper at $0.95 / $4 per million input/output tokens, against $2 / $6 for Mistral Large.
- Kimi K2.7 Code accepts more context: 262K tokens versus 131K.
Side by side
| Kimi K2.7 Code | Mistral Large | |
|---|---|---|
| Provider | Moonshot AI | Mistral AI |
| Noometry Index | 43.3 | 31.9 |
| Released | 2026-06-12 | 2024-02-26 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 16K |
| Input $ / M tokens | $0.95 | $2 |
| Output $ / M tokens | $4 | $6 |
| Results tracked | 19 | 51 |
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Category by category
Coding Kimi K2.7 Code leads
Kimi K2.7 Code: 42.9 (#95), Mistral Large: 34.3 (#240)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| SciCode | 47.5% | 36.2% |
| ALE-Bench | 886.23 | 264.7 |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| WeirdML | 54.1% | — |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| LMArena Coding | — | 1277 |
| BigCodeBench Complete | — | 38.3% |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |
Agentic & Tool Use Mistral Large leads
Kimi K2.7 Code: 24.0 (#122), Mistral Large: 28.6 (#89)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| APEX-Agents | 37.6% | — |
| Berkeley Function Calling Leaderboard | — | 38.4% |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |
Reasoning Kimi K2.7 Code leads
Kimi K2.7 Code: 39.0 (#61), Mistral Large: 15.8 (#310)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| SimpleBench | 57.9% | 22.5% |
| CritPt | 10% | 0% |
| Epoch Capabilities Index | 149.97 | 128.52 |
| Chess Puzzles | 21% | — |
| LiveBench Reasoning | — | 43.5% |
| LMArena Hard Prompts | — | 1257 |
| DTBench | — | 65.1% |
| LiveBench Data Analysis | — | 50.1% |
| LMCA | — | 16.7% |
| Surface Evolver Bench | 48.8% | — |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |
Math Kimi K2.7 Code leads
Kimi K2.7 Code: 52.9 (#48), Mistral Large: 18.2 (#291)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 8.5% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| LMArena Math | — | 1262 |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge Kimi K2.7 Code leads
Kimi K2.7 Code: 53.5 (#57), Mistral Large: 30.1 (#230)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| GPQA Diamond | 87.9% | 51.3% |
| SimpleQA Verified | 36.5% | — |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| LMArena Expert | — | 1232 |
| MMLU | — | 80% |
Multilingual Not comparable
Kimi K2.7 Code: —, Mistral Large: 40.0 (#219)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| LMArena Non-English | — | 1237 |
| LMArena Chinese | — | 1240 |
| LMArena French | — | 1325 |
| LMArena German | — | 1254 |
| LMArena Japanese | — | 1188 |
| LMArena Korean | — | 1202 |
| LMArena Russian | — | 1257 |
| LMArena Spanish | — | 1268 |
Instruction Following Not comparable
Kimi K2.7 Code: —, Mistral Large: 67.9 (#191)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |
| LMArena Instruction Following | — | 1249 |
Long Context Not comparable
Kimi K2.7 Code: —, Mistral Large: 38.3 (#199)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| LMArena Longer Query | — | 1261 |
Writing & Preference Not comparable
Kimi K2.7 Code: —, Mistral Large: 40.7 (#242)
| Benchmark | Kimi K2.7 Code | Mistral Large |
|---|---|---|
| LMArena Text | — | 1266 |
| LMArena Creative Writing | — | 1243 |
| Short-Story Creative Writing | — | 69% |
| EQ-Bench Creative Writing | — | 985 |
| WildBench | — | 80.1% |
| LMArena Multi-Turn | — | 1260 |
| LiveBench Language | — | 39.4% |
Frequently asked questions
Is Kimi K2.7 Code better than Mistral Large?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 31.9 on the Noometry Index.
Which is cheaper, Kimi K2.7 Code or Mistral Large?
Kimi K2.7 Code is cheaper. It lists at $0.95 per million input tokens and $4 per million output tokens; Mistral Large lists at $2 and $6.
Is Kimi K2.7 Code or Mistral Large better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 34.3 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.7 Code does, with 262K tokens against 131K.
How many benchmarks do Kimi K2.7 Code and Mistral Large share?
7 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Mistral Large has 51.