Model comparison
Llama 3.1-8B vs Muse Glimmer
Muse Glimmer is the stronger model overall, scoring 41.3 to 22.8 on the Noometry Index.
Last verified . 12 shared benchmarks.
MetaSummary
- They share 12 benchmarks with published results for both. Llama 3.1-8B scores higher in 0 categories and Muse Glimmer in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Muse Glimmer leads 37.9 to 8.0.
Side by side
| Llama 3.1-8B | Muse Glimmer | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 22.8 | 41.3 |
| Released | 2024-07-23 | — |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.05 | — |
| Output $ / M tokens | $0.08 | — |
| Results tracked | 43 | 13 |
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Category by category
Coding Muse Glimmer leads
Llama 3.1-8B: 19.9 (#335), Muse Glimmer: 38.7 (#157)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Coding | 1195 | 1417 |
| LMArena WebDev | — | 1355 |
| SciCode | 13.2% | — |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| BigCodeBench Complete | 40.5% | — |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |
Agentic & Tool Use Not comparable
Llama 3.1-8B: 22.3 (#123), Muse Glimmer: —
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |
Reasoning Muse Glimmer leads
Llama 3.1-8B: 14.5 (#316), Muse Glimmer: 27.2 (#111)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Hard Prompts | 1175 | 1395 |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| DTBench | 50.9% | — |
| LMCA | 5.4% | — |
| Epoch Capabilities Index | 116.48 | — |
| PIQA | 81.2% | — |
Math Muse Glimmer leads
Llama 3.1-8B: 9.5 (#311), Muse Glimmer: 36.1 (#128)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Math | 1179 | 1419 |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| Omni-MATH | 13.7% | — |
| MATH Level 5 | 22.9% | — |
| GSM8K | 82.4% | — |
Knowledge Muse Glimmer leads
Llama 3.1-8B: 8.0 (#302), Muse Glimmer: 37.9 (#140)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Expert | 1144 | 1388 |
| GPQA Diamond | 27% | — |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| BoolQ | 82.8% | — |
| MMLU | 56.1% | — |
Multilingual Muse Glimmer leads
Llama 3.1-8B: 34.2 (#244), Muse Glimmer: 50.6 (#117)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Non-English | 1148 | 1384 |
| LMArena Chinese | 1151 | 1412 |
| LMArena Russian | 1158 | 1393 |
| LMArena French | 1176 | — |
| LMArena German | 1144 | — |
| LMArena Japanese | 1061 | — |
| LMArena Korean | 1053 | — |
| LMArena Spanish | 1169 | — |
Instruction Following Muse Glimmer leads
Llama 3.1-8B: 59.1 (#253), Muse Glimmer: 72.7 (#134)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Instruction Following | 1159 | 1374 |
| IFEval | 74.3% | — |
Long Context Muse Glimmer leads
Llama 3.1-8B: 35.8 (#233), Muse Glimmer: 42.1 (#124)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Longer Query | 1182 | 1381 |
Writing & Preference Muse Glimmer leads
Llama 3.1-8B: 29.9 (#285), Muse Glimmer: 57.7 (#122)
| Benchmark | Llama 3.1-8B | Muse Glimmer |
|---|---|---|
| LMArena Text | 1187 | 1389 |
| LMArena Creative Writing | 1154 | 1338 |
| LMArena Multi-Turn | 1172 | 1398 |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |
Frequently asked questions
Is Llama 3.1-8B better than Muse Glimmer?
Muse Glimmer is the stronger model overall, scoring 41.3 to 22.8 on the Noometry Index.
Is Llama 3.1-8B or Muse Glimmer better for coding?
Muse Glimmer scores higher on coding benchmarks: 38.7 versus 19.9 in the Noometry coding category.
How many benchmarks do Llama 3.1-8B and Muse Glimmer share?
12 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Muse Glimmer has 13.