Model comparison
Llama-3.3-70B-Instruct vs Muse Glimmer
Muse Glimmer is the stronger model overall, scoring 41.7 to 30.6 on the Noometry Index.
Last verified . 14 shared benchmarks.
MetaSummary
- They share 14 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 0 categories and Muse Glimmer in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Glimmer leads 38.8 to 15.3.
- The biggest single-benchmark swing is SciCode: 26% for Llama-3.3-70B-Instruct and 44.9% for Muse Glimmer.
Side by side
| Llama-3.3-70B-Instruct | Muse Glimmer | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 30.6 | 41.7 |
| Released | 2024-12-06 | 2026-08-10 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.32 | — |
| Results tracked | 43 | 15 |
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Category by category
Coding Muse Glimmer leads
Llama-3.3-70B-Instruct: 31.0 (#290), Muse Glimmer: 40.4 (#142)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| SciCode | 26% | 44.9% |
| LMArena Coding | 1268 | 1416 |
| LMArena WebDev | — | 1355 |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| BigCodeBench Complete | 57.5% | — |
Agentic & Tool Use Not comparable
Llama-3.3-70B-Instruct: 25.8 (#105), Muse Glimmer: —
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |
Reasoning Muse Glimmer leads
Llama-3.3-70B-Instruct: 14.1 (#327), Muse Glimmer: 25.7 (#144)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| CritPt | 0% | 2.6% |
| LMArena Hard Prompts | 1257 | 1396 |
| SimpleBench | 19.9% | — |
| LiveBench Reasoning | 50.8% | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| Epoch Capabilities Index | 127.33 | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |
Math Muse Glimmer leads
Llama-3.3-70B-Instruct: 15.3 (#298), Muse Glimmer: 38.8 (#125)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| LMArena Math | 1267 | 1417 |
| OTIS Mock AIME 2024-2025 | 5.1% | — |
| LiveBench Math | 42.2% | — |
| MATH Level 5 | 41.6% | — |
Knowledge Muse Glimmer leads
Llama-3.3-70B-Instruct: 30.6 (#226), Muse Glimmer: 38.5 (#143)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| LMArena Expert | 1225 | 1386 |
| GPQA Diamond | 47.4% | — |
| Confabulations | 22.8% | — |
| Vectara Hallucination Rate | 4.1% | — |
| MMLU | 86.3% | — |
Multilingual Muse Glimmer leads
Llama-3.3-70B-Instruct: 39.9 (#220), Muse Glimmer: 50.5 (#122)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| LMArena Non-English | 1236 | 1384 |
| LMArena Chinese | 1217 | 1412 |
| LMArena Russian | 1252 | 1390 |
| LMArena French | 1281 | — |
| LMArena German | 1251 | — |
| LMArena Japanese | 1150 | — |
| LMArena Korean | 1143 | — |
| LMArena Spanish | 1270 | — |
Instruction Following Muse Glimmer leads
Llama-3.3-70B-Instruct: 71.1 (#157), Muse Glimmer: 72.6 (#135)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| LMArena Instruction Following | 1242 | 1375 |
| LiveBench Instruction Following | 82.7% | — |
Long Context Muse Glimmer leads
Llama-3.3-70B-Instruct: 26.4 (#295), Muse Glimmer: 42.1 (#129)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| LMArena Longer Query | 1256 | 1382 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference Muse Glimmer leads
Llama-3.3-70B-Instruct: 47.6 (#207), Muse Glimmer: 57.5 (#126)
| Benchmark | Llama-3.3-70B-Instruct | Muse Glimmer |
|---|---|---|
| LMArena Text | 1274 | 1389 |
| LMArena Creative Writing | 1250 | 1339 |
| LMArena Multi-Turn | 1280 | 1399 |
| LiveBench Language | 39.2% | — |
Frequently asked questions
Is Llama-3.3-70B-Instruct better than Muse Glimmer?
Muse Glimmer is the stronger model overall, scoring 41.7 to 30.6 on the Noometry Index.
Is Llama-3.3-70B-Instruct or Muse Glimmer better for coding?
Muse Glimmer scores higher on coding benchmarks: 40.4 versus 31.0 in the Noometry coding category.
How many benchmarks do Llama-3.3-70B-Instruct and Muse Glimmer share?
14 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Muse Glimmer has 15.