# Codestral vs DeepSeek-R1-Distill-Llama-70B

> DeepSeek-R1-Distill-Llama-70B is the stronger model overall, scoring 37.4 to 30.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/codestral-vs-deepseek-r1-distill-llama-70b
- Last updated: 2026-10-10
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. Codestral scores higher in 0 categories and DeepSeek-R1-Distill-Llama-70B in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-R1-Distill-Llama-70B leads 36.3 to 26.9.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 32.5% for Codestral and 52.3% for DeepSeek-R1-Distill-Llama-70B.

## Snapshot

| | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| Provider | Mistral AI | DeepSeek |
| Noometry Index | 30.1 | 37.4 |
| Rank | 287 | 187 |
| Context | 256K | — |
| Input $/M | $0.30 | — |
| Output $/M | $0.90 | — |
| Weights | Open | Open |

## Coding

- Codestral: 26.9 (#316)
- DeepSeek-R1-Distill-Llama-70B: 36.3 (#197)

| Benchmark | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| BigCodeBench Instruct | 41.8% | 35.3% |
| BigCodeBench Complete | 52.5% | 49.9% |
| Aider Polyglot | 11.1% | — |
| LiveBench Coding | — | 51.6% |
| ALE-Bench | 137.78 | — |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |

## Reasoning

- Codestral: 19.1 (#244)
- DeepSeek-R1-Distill-Llama-70B: 24.1 (#150)

| Benchmark | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | 52.3% |
| LiveBench Reasoning | — | 67.6% |
| LiveBench Data Analysis | — | 55.9% |
| LiveBench | — | 54.5% |

## Math

- Codestral: —
- DeepSeek-R1-Distill-Llama-70B: 34.3 (#161)

| Benchmark | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 51.4% |
| LiveBench Math | — | 58.1% |
| MATH Level 5 | — | 89.9% |

## Knowledge

- Codestral: —
- DeepSeek-R1-Distill-Llama-70B: 30.7 (#216)

| Benchmark | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| GPQA Diamond | — | 55.7% |

## Instruction Following

- Codestral: —
- DeepSeek-R1-Distill-Llama-70B: 68.3 (#185)

| Benchmark | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| LiveBench Instruction Following | — | 69.9% |

## Writing & Preference

- Codestral: —
- DeepSeek-R1-Distill-Llama-70B: 49.0 (#189)

| Benchmark | Codestral | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| LiveBench Language | — | 23.8% |

## FAQ

### Is Codestral better than DeepSeek-R1-Distill-Llama-70B?

DeepSeek-R1-Distill-Llama-70B is the stronger model overall, scoring 37.4 to 30.1 on the Noometry Index.

### Is Codestral or DeepSeek-R1-Distill-Llama-70B better for coding?

DeepSeek-R1-Distill-Llama-70B scores higher on coding benchmarks: 36.3 versus 26.9 in the Noometry coding category.

### How many benchmarks do Codestral and DeepSeek-R1-Distill-Llama-70B share?

3 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and DeepSeek-R1-Distill-Llama-70B has 13.