Model comparison
Kimi K2.7 Code vs Mistral Nemo
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 26.4 on the Noometry Index. Mistral Nemo costs 11× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Mistral AISummary
- They share 2 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Mistral Nemo in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.7 Code leads 53.5 to 12.3.
- The biggest single-benchmark swing is GPQA Diamond: 87.9% for Kimi K2.7 Code and 29.9% for Mistral Nemo.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 128K.
Side by side
| Kimi K2.7 Code | Mistral Nemo | |
|---|---|---|
| Provider | Moonshot AI | Mistral AI |
| Noometry Index | 43.3 | 26.4 |
| Released | 2026-06-12 | 2024-07-01 |
| Weights | Open | Open |
| Context window | 262K | 128K |
| Max output | 262K | 128K |
| Input $ / M tokens | $0.95 | $0.15 |
| Output $ / M tokens | $4 | $0.15 |
| Results tracked | 19 | 10 |
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Category by category
Coding Not comparable
Kimi K2.7 Code: 42.9 (#95), Mistral Nemo: —
| Benchmark | Kimi K2.7 Code | Mistral Nemo |
|---|---|---|
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| SciCode | 47.5% | — |
| WeirdML | 54.1% | — |
| ALE-Bench | 886.23 | — |
Agentic & Tool Use Too close to call
Kimi K2.7 Code: 24.0 (#122), Mistral Nemo: 23.5 (#125)
| Benchmark | Kimi K2.7 Code | Mistral Nemo |
|---|---|---|
| APEX-Agents | 37.6% | — |
| Berkeley Function Calling Leaderboard | — | 27.6% |
| BALROG | — | 17.6% |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |
Reasoning Kimi K2.7 Code leads
Kimi K2.7 Code: 39.0 (#61), Mistral Nemo: 20.7 (#232)
| Benchmark | Kimi K2.7 Code | Mistral Nemo |
|---|---|---|
| Epoch Capabilities Index | 149.97 | 118.68 |
| SimpleBench | 57.9% | — |
| CritPt | 10% | — |
| Chess Puzzles | 21% | — |
| DTBench | — | 48.6% |
| Surface Evolver Bench | 48.8% | — |
| PIQA | — | 83.5% |
Math Kimi K2.7 Code leads
Kimi K2.7 Code: 52.9 (#48), Mistral Nemo: 25.5 (#268)
| Benchmark | Kimi K2.7 Code | Mistral Nemo |
|---|---|---|
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| OTIS Mock AIME 2024-2025 | 95.6% | — |
| MATH Level 5 | — | 10.8% |
| GSM8K | — | 84.2% |
Knowledge Kimi K2.7 Code leads
Kimi K2.7 Code: 53.5 (#57), Mistral Nemo: 12.3 (#298)
| Benchmark | Kimi K2.7 Code | Mistral Nemo |
|---|---|---|
| GPQA Diamond | 87.9% | 29.9% |
| SimpleQA Verified | 36.5% | — |
| BoolQ | — | 82.5% |
Writing & Preference Not comparable
Kimi K2.7 Code: —, Mistral Nemo: 28.5 (#296)
| Benchmark | Kimi K2.7 Code | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | — | 881 |
Frequently asked questions
Is Kimi K2.7 Code better than Mistral Nemo?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 26.4 on the Noometry Index. Mistral Nemo costs 11× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Which is cheaper, Kimi K2.7 Code or Mistral Nemo?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Which has the bigger context window?
Kimi K2.7 Code does, with 262K tokens against 128K.
How many benchmarks do Kimi K2.7 Code and Mistral Nemo share?
2 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Mistral Nemo has 10.