Model comparison
Laguna M.1 vs Mixtral 8x7B
Laguna M.1 is the stronger model overall, scoring 31.9 to 26.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
Poolside
Mistral AISummary
- The widest gap is in reasoning, where Laguna M.1 leads 21.9 to 17.4.
- Laguna M.1 accepts more context: 262K tokens versus 32K.
Side by side
| Laguna M.1 | Mixtral 8x7B | |
|---|---|---|
| Provider | Poolside | Mistral AI |
| Noometry Index | 31.9 | 26.8 |
| Released | 2026-04-28 | 2023-12-11 |
| Weights | Open | Open |
| Context window | 262K | 32K |
| Max output | 33K | 32K |
| Input $ / M tokens | — | $0.70 |
| Output $ / M tokens | — | $0.70 |
| Results tracked | 3 | 38 |
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Category by category
Coding Laguna M.1 leads
Laguna M.1: 36.4 (#195), Mixtral 8x7B: 32.2 (#265)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| LMArena WebDev | 1348 | — |
| LMArena Coding | — | 1127 |
| HumanEval+ | — | 39.6% |
| MBPP+ | — | 49.7% |
Reasoning Laguna M.1 leads
Laguna M.1: 21.9 (#187), Mixtral 8x7B: 17.4 (#283)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| LMArena Hard Prompts | — | 1115 |
| DTBench | — | 49.6% |
| Surface Evolver Bench | 15.6% | — |
| Adversarial NLI | — | 55.2% |
| Epoch Capabilities Index | — | 118.38 |
| ForecastBench | — | 56.3 |
| HellaSwag | — | 86.7% |
| PIQA | — | 83.6% |
| WinoGrande | — | 77.2% |
Math Laguna M.1 leads
Laguna M.1: 20.3 (#276), Mixtral 8x7B: 17.2 (#284)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| ProofBench | 0% | — |
| Omni-MATH | — | 10.5% |
| LMArena Math | — | 1147 |
| MATH Level 5 | — | 10% |
| GSM8K | — | 74.4% |
Knowledge Not comparable
Laguna M.1: —, Mixtral 8x7B: 11.0 (#296)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| GPQA Diamond | — | 30.6% |
| MMLU-Pro | — | 33.5% |
| GPQA (HELM) | — | 29.6% |
| LMArena Expert | — | 1088 |
| ARC (AI2) Challenge | — | 87.3% |
| MMLU | — | 70.6% |
| OpenBookQA | — | 85.8% |
| TriviaQA | — | 82.2% |
Multilingual Not comparable
Laguna M.1: —, Mixtral 8x7B: 29.8 (#261)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| LMArena Non-English | — | 1077 |
| LMArena Chinese | — | 1055 |
| LMArena French | — | 1165 |
| LMArena German | — | 1114 |
| LMArena Japanese | — | 931 |
| LMArena Korean | — | 968 |
| LMArena Russian | — | 1090 |
| LMArena Spanish | — | 1110 |
Instruction Following Not comparable
Laguna M.1: —, Mixtral 8x7B: 51.2 (#292)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| IFEval | — | 57.5% |
| LMArena Instruction Following | — | 1110 |
Long Context Not comparable
Laguna M.1: —, Mixtral 8x7B: 33.4 (#255)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| LMArena Longer Query | — | 1103 |
Writing & Preference Not comparable
Laguna M.1: —, Mixtral 8x7B: 34.4 (#265)
| Benchmark | Laguna M.1 | Mixtral 8x7B |
|---|---|---|
| LMArena Text | — | 1132 |
| LMArena Creative Writing | — | 1109 |
| WildBench | — | 67.3% |
| LMArena Multi-Turn | — | 1115 |
Frequently asked questions
Is Laguna M.1 better than Mixtral 8x7B?
Laguna M.1 is the stronger model overall, scoring 31.9 to 26.8 on the Noometry Index.
Is Laguna M.1 or Mixtral 8x7B better for coding?
Laguna M.1 scores higher on coding benchmarks: 36.4 versus 32.2 in the Noometry coding category.
Which has the bigger context window?
Laguna M.1 does, with 262K tokens against 32K.
How many benchmarks do Laguna M.1 and Mixtral 8x7B share?
0 benchmarks have published results for both models. Laguna M.1 has 3 scored results on Noometry and Mixtral 8x7B has 38.