Model comparison
DeepSeek-R1-Distill-Llama-70B vs Kimi K2 (Jul 2025)
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 37.8 on the Noometry Index.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-R1-Distill-Llama-70B scores higher in 1 category and Kimi K2 (Jul 2025) in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Kimi K2 (Jul 2025) leads 62.3 to 49.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 52.3% for DeepSeek-R1-Distill-Llama-70B and 64.4% for Kimi K2 (Jul 2025).
Side by side
| DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Noometry Index | 37.8 | 41.2 |
| Released | 2025-01-20 | 2025-07-12 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 262K |
| Input $ / M tokens | — | $0.57 |
| Output $ / M tokens | — | $2.30 |
| Results tracked | 13 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Kimi K2 (Jul 2025) leads
DeepSeek-R1-Distill-Llama-70B: 36.8 (#202), Kimi K2 (Jul 2025): 42.4 (#102)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| GSO | — | 4.9% |
| WeirdML | — | 42.8% |
| BigCodeBench Instruct | 35.3% | — |
| LiveBench Coding | 51.6% | — |
| LMArena Coding | — | 1399 |
| BigCodeBench Complete | 49.9% | — |
| ALE-Bench | — | 597.5 |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Kimi K2 (Jul 2025): 32.4 (#64)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | — | 35.7% |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| METR Time Horizons | — | 59.2% |
Reasoning DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 24.9 (#156), Kimi K2 (Jul 2025): 23.3 (#179)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| Kagi LLM Benchmark | 52.3% | 64.4% |
| SimpleBench | — | 26.3% |
| LiveBench Reasoning | 67.6% | — |
| LMArena Hard Prompts | — | 1384 |
| LiveBench Data Analysis | 55.9% | — |
| Epoch Capabilities Index | — | 146.01 |
| ForecastBench | — | 60.2 |
| LiveBench | 54.5% | — |
Math Kimi K2 (Jul 2025) leads
DeepSeek-R1-Distill-Llama-70B: 36.0 (#176), Kimi K2 (Jul 2025): 42.7 (#83)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 51.4% | — |
| Omni-MATH | — | 65.4% |
| LiveBench Math | 58.1% | — |
| LMArena Math | — | 1397 |
| MATH Level 5 | 89.9% | — |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Kimi K2 (Jul 2025) leads
DeepSeek-R1-Distill-Llama-70B: 30.7 (#225), Kimi K2 (Jul 2025): 37.3 (#157)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| GPQA Diamond | 55.7% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| Vectara Hallucination Rate | — | 17.9% |
| GPQA (HELM) | — | 65.3% |
| LMArena Expert | — | 1365 |
Multilingual Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Kimi K2 (Jul 2025): 49.6 (#130)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | — | 1372 |
| LMArena Chinese | — | 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-R1-Distill-Llama-70B: 68.2 (#190), Kimi K2 (Jul 2025): 71.1 (#156)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| LiveBench Instruction Following | 69.9% | — |
| IFEval | — | 85% |
| LMArena Instruction Following | — | 1348 |
Long Context Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Kimi K2 (Jul 2025): 41.2 (#145)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |
| LMArena Longer Query | — | 1353 |
Writing & Preference Kimi K2 (Jul 2025) leads
DeepSeek-R1-Distill-Llama-70B: 49.0 (#194), Kimi K2 (Jul 2025): 62.3 (#78)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | — | 1380 |
| LMArena Creative Writing | — | 1350 |
| Short-Story Creative Writing | — | 85.6% |
| EQ-Bench Creative Writing | — | 1666 |
| WildBench | — | 86.2% |
| LMArena Multi-Turn | — | 1371 |
| LiveBench Language | 23.8% | — |
Frequently asked questions
Is DeepSeek-R1-Distill-Llama-70B better than Kimi K2 (Jul 2025)?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 37.8 on the Noometry Index.
Is DeepSeek-R1-Distill-Llama-70B or Kimi K2 (Jul 2025) better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 36.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Llama-70B and Kimi K2 (Jul 2025) share?
1 benchmark has published results for both models. DeepSeek-R1-Distill-Llama-70B has 13 scored results on Noometry and Kimi K2 (Jul 2025) has 42.