Model comparison
DeepSeek-V2.5 (Sep 2024) vs Kimi K2.7 Code
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 37.6 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in knowledge, where Kimi K2.7 Code leads 53.5 to 34.8.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code | |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Noometry Index | 37.6 | 43.3 |
| Released | 2024-09-06 | 2026-06-12 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 262K |
| Input $ / M tokens | — | $0.95 |
| Output $ / M tokens | — | $4 |
| Results tracked | 22 | 19 |
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Category by category
Coding Kimi K2.7 Code leads
DeepSeek-V2.5 (Sep 2024): 31.7 (#281), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| Aider Polyglot | 17.8% | — |
| LMArena WebDev | — | 1473 |
| SciCode | — | 47.5% |
| WeirdML | — | 54.1% |
| BigCodeBench Instruct | 48.6% | — |
| LMArena Coding | 1309 | — |
| BigCodeBench Complete | 53.2% | — |
| ALE-Bench | — | 886.23 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2.5 (Sep 2024): —, Kimi K2.7 Code: 24.0 (#122)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 5,083 |
Reasoning Kimi K2.7 Code leads
DeepSeek-V2.5 (Sep 2024): 25.6 (#145), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| SimpleBench | — | 57.9% |
| CritPt | — | 10% |
| Chess Puzzles | — | 21% |
| LMArena Hard Prompts | 1289 | — |
| Surface Evolver Bench | — | 48.8% |
| Epoch Capabilities Index | — | 149.97 |
Math Kimi K2.7 Code leads
DeepSeek-V2.5 (Sep 2024): 35.9 (#177), Kimi K2.7 Code: 52.9 (#48)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 54% |
| FrontierMath Tier 4 | — | 12.2% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| LMArena Math | 1288 | — |
Knowledge Kimi K2.7 Code leads
DeepSeek-V2.5 (Sep 2024): 34.8 (#193), Kimi K2.7 Code: 53.5 (#57)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | — | 87.9% |
| SimpleQA Verified | — | 36.5% |
| LMArena Expert | 1266 | — |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.5 (#193), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1273 | — |
| LMArena Chinese | 1318 | — |
| LMArena French | 1289 | — |
| LMArena German | 1258 | — |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |
| LMArena Russian | 1289 | — |
| LMArena Spanish | 1248 | — |
Instruction Following Not comparable
DeepSeek-V2.5 (Sep 2024): 67.5 (#194), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#174), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference Not comparable
DeepSeek-V2.5 (Sep 2024): 49.8 (#187), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Kimi K2.7 Code?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 37.6 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or Kimi K2.7 Code better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 31.7 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Kimi K2.7 Code share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Kimi K2.7 Code has 19.