Model comparison
Laguna M.1 vs Llama 3.1-8B
Laguna M.1 is the stronger model overall, scoring 31.9 to 22.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
Poolside
MetaSummary
- The widest gap is in coding, where Laguna M.1 leads 36.4 to 19.9.
- Laguna M.1 accepts more context: 262K tokens versus 128K.
Side by side
| Laguna M.1 | Llama 3.1-8B | |
|---|---|---|
| Provider | Poolside | Meta |
| Noometry Index | 31.9 | 22.8 |
| Released | 2026-04-28 | 2024-07-23 |
| Weights | Open | Open |
| Context window | 262K | 128K |
| Max output | 33K | 4K |
| Input $ / M tokens | — | $0.05 |
| Output $ / M tokens | — | $0.08 |
| Results tracked | 3 | 43 |
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Category by category
Coding Laguna M.1 leads
Laguna M.1: 36.4 (#195), Llama 3.1-8B: 19.9 (#335)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| LMArena WebDev | 1348 | — |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| LMArena Coding | — | 1195 |
| BigCodeBench Complete | — | 40.5% |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |
Agentic & Tool Use Not comparable
Laguna M.1: —, Llama 3.1-8B: 22.3 (#123)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |
Reasoning Laguna M.1 leads
Laguna M.1: 21.9 (#187), Llama 3.1-8B: 14.5 (#316)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1175 |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Surface Evolver Bench | 15.6% | — |
| Epoch Capabilities Index | — | 116.48 |
| PIQA | — | 81.2% |
Math Laguna M.1 leads
Laguna M.1: 20.3 (#276), Llama 3.1-8B: 9.5 (#311)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| ProofBench | 0% | — |
| Omni-MATH | — | 13.7% |
| LMArena Math | — | 1179 |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |
Knowledge Not comparable
Laguna M.1: —, Llama 3.1-8B: 8.0 (#302)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| LMArena Expert | — | 1144 |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |
Multilingual Not comparable
Laguna M.1: —, Llama 3.1-8B: 34.2 (#244)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | — | 1148 |
| LMArena Chinese | — | 1151 |
| LMArena French | — | 1176 |
| LMArena German | — | 1144 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1053 |
| LMArena Russian | — | 1158 |
| LMArena Spanish | — | 1169 |
Instruction Following Not comparable
Laguna M.1: —, Llama 3.1-8B: 59.1 (#253)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| IFEval | — | 74.3% |
| LMArena Instruction Following | — | 1159 |
Long Context Not comparable
Laguna M.1: —, Llama 3.1-8B: 35.8 (#233)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | — | 1182 |
Writing & Preference Not comparable
Laguna M.1: —, Llama 3.1-8B: 29.9 (#285)
| Benchmark | Laguna M.1 | Llama 3.1-8B |
|---|---|---|
| LMArena Text | — | 1187 |
| LMArena Creative Writing | — | 1154 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |
| LMArena Multi-Turn | — | 1172 |
Frequently asked questions
Is Laguna M.1 better than Llama 3.1-8B?
Laguna M.1 is the stronger model overall, scoring 31.9 to 22.8 on the Noometry Index.
Is Laguna M.1 or Llama 3.1-8B better for coding?
Laguna M.1 scores higher on coding benchmarks: 36.4 versus 19.9 in the Noometry coding category.
Which has the bigger context window?
Laguna M.1 does, with 262K tokens against 128K.
How many benchmarks do Laguna M.1 and Llama 3.1-8B share?
0 benchmarks have published results for both models. Laguna M.1 has 3 scored results on Noometry and Llama 3.1-8B has 43.