# DeepSeek-R1-Distill-Llama-70B vs Kimi K2.7 Code

> Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 37.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-r1-distill-llama-70b-vs-kimi-k2-7-code
- Last updated: 2026-10-10
- Shared benchmarks: 2

## Summary

- They share 2 benchmarks with published results for both. DeepSeek-R1-Distill-Llama-70B scores higher in 0 categories and Kimi K2.7 Code in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.7 Code leads 53.6 to 30.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 51.4% for DeepSeek-R1-Distill-Llama-70B and 95.6% for Kimi K2.7 Code.

## Snapshot

| | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Noometry Index | 37.4 | 43.0 |
| Rank | 187 | 90 |
| Context | — | 262K |
| Input $/M | — | $0.95 |
| Output $/M | — | $4 |
| Weights | Open | Open |

## Coding

- DeepSeek-R1-Distill-Llama-70B: 36.3 (#197)
- Kimi K2.7 Code: 42.4 (#92)

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| LMArena WebDev | — | 1473 |
| SciCode | — | 47.5% |
| WeirdML | — | 54.1% |
| BigCodeBench Instruct | 35.3% | — |
| LiveBench Coding | 51.6% | — |
| BigCodeBench Complete | 49.9% | — |
| ALE-Bench | — | 886.23 |

## Agentic & Tool Use

- DeepSeek-R1-Distill-Llama-70B: —
- Kimi K2.7 Code: 23.9 (#115)

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 5,083 |

## Reasoning

- DeepSeek-R1-Distill-Llama-70B: 24.1 (#150)
- Kimi K2.7 Code: 38.2 (#56)

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| SimpleBench | — | 57.9% |
| Kagi LLM Benchmark | 52.3% | — |
| CritPt | — | 10% |
| Chess Puzzles | — | 21% |
| LiveBench Reasoning | 67.6% | — |
| LiveBench Data Analysis | 55.9% | — |
| Surface Evolver Bench | — | 48.8% |
| Epoch Capabilities Index | — | 150.01 |
| LiveBench | 54.5% | — |

## Math

- DeepSeek-R1-Distill-Llama-70B: 34.3 (#161)
- Kimi K2.7 Code: 52.6 (#39)

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 51.4% | 95.6% |
| FrontierMath (Tiers 1-3) | — | 54% |
| FrontierMath Tier 4 | — | 12.2% |
| LiveBench Math | 58.1% | — |
| MATH Level 5 | 89.9% | — |

## Knowledge

- DeepSeek-R1-Distill-Llama-70B: 30.7 (#216)
- Kimi K2.7 Code: 53.6 (#51)

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | 55.7% | 87.9% |
| SimpleQA Verified | — | 36.5% |

## Instruction Following

- DeepSeek-R1-Distill-Llama-70B: 68.3 (#185)
- Kimi K2.7 Code: —

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| LiveBench Instruction Following | 69.9% | — |

## Writing & Preference

- DeepSeek-R1-Distill-Llama-70B: 49.0 (#189)
- Kimi K2.7 Code: —

| Benchmark | DeepSeek-R1-Distill-Llama-70B | Kimi K2.7 Code |
|---|---|---|
| LiveBench Language | 23.8% | — |

## FAQ

### Is DeepSeek-R1-Distill-Llama-70B better than Kimi K2.7 Code?

Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 37.4 on the Noometry Index.

### Is DeepSeek-R1-Distill-Llama-70B or Kimi K2.7 Code better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.4 versus 36.3 in the Noometry coding category.

### How many benchmarks do DeepSeek-R1-Distill-Llama-70B and Kimi K2.7 Code share?

2 benchmarks have published results for both models. DeepSeek-R1-Distill-Llama-70B has 13 scored results on Noometry and Kimi K2.7 Code has 19.