Model comparison
DeepSeek LLM 67B vs Kimi K2 (Jul 2025)
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 24.9 on the Noometry Index.
Last verified . 11 shared benchmarks.
DeepSeekSummary
- They share 11 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and Kimi K2 (Jul 2025) in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2 (Jul 2025) leads 42.7 to 8.7.
Side by side
| DeepSeek LLM 67B | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Noometry Index | 24.9 | 41.2 |
| Released | 2023-11-29 | 2025-07-12 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 262K |
| Input $ / M tokens | — | $0.57 |
| Output $ / M tokens | — | $2.30 |
| Results tracked | 15 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 31.9 (#278), Kimi K2 (Jul 2025): 42.4 (#102)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Coding | 1096 | 1399 |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| GSO | — | 4.9% |
| WeirdML | — | 42.8% |
| ALE-Bench | — | 597.5 |
Agentic & Tool Use Not comparable
DeepSeek LLM 67B: —, Kimi K2 (Jul 2025): 32.4 (#64)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | — | 35.7% |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| METR Time Horizons | — | 59.2% |
Reasoning Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 16.5 (#304), Kimi K2 (Jul 2025): 23.3 (#179)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1384 |
| Epoch Capabilities Index | 110.5 | 146.01 |
| SimpleBench | — | 26.3% |
| Kagi LLM Benchmark | — | 64.4% |
| Chess Puzzles | 0% | — |
| ForecastBench | — | 60.2 |
Math Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 8.7 (#324), Kimi K2 (Jul 2025): 42.7 (#83)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1108 | 1397 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| Omni-MATH | — | 65.4% |
| MATH Level 5 | 6.4% | — |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 7.0 (#313), Kimi K2 (Jul 2025): 37.3 (#157)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| Vectara Hallucination Rate | — | 17.9% |
| GPQA (HELM) | — | 65.3% |
| LMArena Expert | — | 1365 |
Multilingual Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 29.4 (#267), Kimi K2 (Jul 2025): 49.6 (#130)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1073 | 1372 |
| LMArena Chinese | 1132 | 1415 |
| LMArena French | — | 1379 |
| LMArena German | — | 1387 |
| LMArena Japanese | — | 1349 |
| LMArena Korean | — | 1325 |
| LMArena Russian | — | 1385 |
| LMArena Spanish | — | 1386 |
Instruction Following Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 55.4 (#277), Kimi K2 (Jul 2025): 71.1 (#156)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1079 | 1348 |
| IFEval | — | 85% |
Long Context Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 33.1 (#265), Kimi K2 (Jul 2025): 41.2 (#145)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Longer Query | 1092 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |
Writing & Preference Kimi K2 (Jul 2025) leads
DeepSeek LLM 67B: 31.6 (#282), Kimi K2 (Jul 2025): 62.3 (#78)
| Benchmark | DeepSeek LLM 67B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1105 | 1380 |
| LMArena Creative Writing | 1067 | 1350 |
| LMArena Multi-Turn | 1082 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| EQ-Bench Creative Writing | — | 1666 |
| WildBench | — | 86.2% |
Frequently asked questions
Is DeepSeek LLM 67B better than Kimi K2 (Jul 2025)?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or Kimi K2 (Jul 2025) better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and Kimi K2 (Jul 2025) share?
11 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Kimi K2 (Jul 2025) has 42.