Model comparison
Codestral vs Llama 2-7B
Codestral is the stronger model overall, scoring 30.6 to 29.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AI
MetaSummary
- The widest gap is in reasoning, where Codestral leads 19.8 to 15.7.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Codestral | Llama 2-7B | |
|---|---|---|
| Provider | Mistral AI | Meta |
| Noometry Index | 30.6 | 29.1 |
| Released | 2024-05-29 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 256K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 7 | 29 |
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Category by category
Coding Llama 2-7B leads
Codestral: 27.3 (#321), Llama 2-7B: 29.2 (#307)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| Aider Polyglot | 11.1% | — |
| BigCodeBench Instruct | 41.8% | — |
| LMArena Coding | — | 1002 |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | 137.78 | — |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |
Reasoning Codestral leads
Codestral: 19.8 (#251), Llama 2-7B: 15.7 (#312)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1009 |
| BIG-Bench Hard | — | 39.2% |
| Epoch Capabilities Index | — | 99.06 |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |
Math Not comparable
Codestral: —, Llama 2-7B: 30.7 (#233)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| LMArena Math | — | 1042 |
| GSM8K | — | 16.7% |
Knowledge Not comparable
Codestral: —, Llama 2-7B: 28.2 (#248)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| LMArena Expert | — | 1036 |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |
Multimodal Not comparable
Codestral: —, Llama 2-7B: —
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| ScienceQA | — | 43.1% |
Multilingual Not comparable
Codestral: —, Llama 2-7B: 23.8 (#293)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| LMArena Non-English | — | 973 |
| LMArena Chinese | — | 973 |
| LMArena French | — | 970 |
| LMArena German | — | 978 |
| LMArena Russian | — | 995 |
| LMArena Spanish | — | 1007 |
Instruction Following Not comparable
Codestral: —, Llama 2-7B: 50.8 (#298)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | — | 1006 |
Long Context Not comparable
Codestral: —, Llama 2-7B: 30.4 (#287)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | — | 999 |
Writing & Preference Not comparable
Codestral: —, Llama 2-7B: 28.0 (#298)
| Benchmark | Codestral | Llama 2-7B |
|---|---|---|
| LMArena Text | — | 1053 |
| LMArena Creative Writing | — | 1033 |
| LMArena Multi-Turn | — | 1029 |
Frequently asked questions
Is Codestral better than Llama 2-7B?
Codestral is the stronger model overall, scoring 30.6 to 29.1 on the Noometry Index.
Is Codestral or Llama 2-7B better for coding?
Llama 2-7B scores higher on coding benchmarks: 29.2 versus 27.3 in the Noometry coding category.
How many benchmarks do Codestral and Llama 2-7B share?
0 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and Llama 2-7B has 29.