Model comparison
Kimi K2 (Jul 2025) vs Mistral 7B
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 23.0 on the Noometry Index. Mistral 7B costs 4.0× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Mistral AISummary
- They share 17 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 8 categories and Mistral 7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2 (Jul 2025) leads 42.7 to 8.1.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 8K.
Side by side
| Kimi K2 (Jul 2025) | Mistral 7B | |
|---|---|---|
| Provider | Moonshot AI | Mistral AI |
| Noometry Index | 41.2 | 23.0 |
| Released | 2025-07-12 | 2023-09-27 |
| Weights | Open | Open |
| Context window | 262K | 8K |
| Max output | 262K | 8K |
| Input $ / M tokens | $0.57 | $0.25 |
| Output $ / M tokens | $2.30 | $0.25 |
| Results tracked | 42 | 37 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.4 (#102), Mistral 7B: 26.4 (#326)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Coding | 1399 | 1082 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| BigCodeBench Instruct | — | 19.5% |
| BigCodeBench Complete | — | 27.3% |
| ALE-Bench | 597.5 | — |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.4 (#64), Mistral 7B: —
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
Reasoning Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 23.3 (#179), Mistral 7B: 13.1 (#336)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1067 |
| Epoch Capabilities Index | 146.01 | 112.21 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| Chess Puzzles | — | 0% |
| DTBench | — | 42.5% |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| ForecastBench | 60.2 | — |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.7 (#83), Mistral 7B: 8.1 (#325)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Math | 1397 | 1085 |
| OTIS Mock AIME 2024-2025 | — | 0.3% |
| Omni-MATH | 65.4% | — |
| MATH Level 5 | — | 3.7% |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
| GSM8K | — | 54.4% |
Knowledge Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 37.3 (#157), Mistral 7B: 7.4 (#311)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Expert | 1365 | 1036 |
| GPQA Diamond | — | 15.2% |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multilingual Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 49.6 (#130), Mistral 7B: 25.8 (#283)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1372 | 1012 |
| LMArena Chinese | 1415 | 1009 |
| LMArena French | 1379 | 1037 |
| LMArena German | 1387 | 987 |
| LMArena Japanese | 1349 | 878 |
| LMArena Russian | 1385 | 1018 |
| LMArena Spanish | 1386 | 1026 |
| LMArena Korean | 1325 | — |
Instruction Following Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 71.1 (#156), Mistral 7B: 54.2 (#280)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1348 | 1060 |
| IFEval | 85% | — |
Long Context Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 41.2 (#145), Mistral 7B: 32.2 (#271)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1353 | 1060 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
Writing & Preference Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 62.3 (#78), Mistral 7B: 30.7 (#286)
| Benchmark | Kimi K2 (Jul 2025) | Mistral 7B |
|---|---|---|
| LMArena Text | 1380 | 1090 |
| LMArena Creative Writing | 1350 | 1068 |
| LMArena Multi-Turn | 1371 | 1062 |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
Frequently asked questions
Is Kimi K2 (Jul 2025) better than Mistral 7B?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 23.0 on the Noometry Index. Mistral 7B costs 4.0× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Which is cheaper, Kimi K2 (Jul 2025) or Mistral 7B?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or Mistral 7B better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 8K.
How many benchmarks do Kimi K2 (Jul 2025) and Mistral 7B share?
17 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Mistral 7B has 37.