Model comparison
Llama 4 Scout vs QwQ-32B
QwQ-32B is the stronger model overall, scoring 39.8 to 27.7 on the Noometry Index.
Last verified . 24 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 24 benchmarks with published results for both. Llama 4 Scout scores higher in 0 categories and QwQ-32B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where QwQ-32B leads 49.0 to 27.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 7.8% for Llama 4 Scout and 59.2% for QwQ-32B.
Side by side
| Llama 4 Scout | QwQ-32B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 27.7 | 39.8 |
| Released | 2025-04-05 | 2024-11-28 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.30 | — |
| Results tracked | 43 | 36 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding QwQ-32B leads
Llama 4 Scout: 20.2 (#339), QwQ-32B: 35.4 (#226)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| LMArena Coding | 1286 | 1333 |
| BigCodeBench Complete | 43.1% | 54.4% |
| SWE-bench Verified (bash only) | 9.1% | — |
| Aider Polyglot | — | 20.9% |
| SciCode | 17% | — |
| BigCodeBench Instruct | — | 44.6% |
| LiveBench Coding | — | 72.2% |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.6 (#119), QwQ-32B: —
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning QwQ-32B leads
Llama 4 Scout: 9.1 (#345), QwQ-32B: 23.7 (#174)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| LMArena Hard Prompts | 1266 | 1325 |
| Epoch Capabilities Index | 129.64 | 137.6 |
| ForecastBench | 57.5 | 58.3 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 36.9% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 5% |
| LiveBench Reasoning | — | 83.5% |
| DTBench | 57.9% | — |
| LiveBench Data Analysis | — | 65% |
| LMCA | 12% | — |
| LiveBench | — | 72% |
Math QwQ-32B leads
Llama 4 Scout: 19.6 (#286), QwQ-32B: 38.0 (#143)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.8% | 59.2% |
| LMArena Math | 1287 | 1359 |
| Omni-MATH | 37.3% | — |
| LiveBench Math | — | 77.8% |
| MATH Level 5 | 62.3% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
Knowledge QwQ-32B leads
Llama 4 Scout: 31.9 (#217), QwQ-32B: 37.2 (#158)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| GPQA Diamond | 51.8% | 65.3% |
| LMArena Expert | 1235 | 1324 |
| MMLU-Pro | 74.2% | — |
| Confabulations | — | 15.6% |
| Vectara Hallucination Rate | 7.7% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Not comparable
Llama 4 Scout: 32.2 (#102), QwQ-32B: —
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual QwQ-32B leads
Llama 4 Scout: 41.0 (#212), QwQ-32B: 44.8 (#176)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| LMArena Non-English | 1252 | 1305 |
| LMArena Chinese | 1255 | 1378 |
| LMArena French | 1282 | 1336 |
| LMArena German | 1272 | 1313 |
| LMArena Japanese | 1206 | 1262 |
| LMArena Korean | 1207 | 1279 |
| LMArena Russian | 1263 | 1297 |
| LMArena Spanish | 1278 | 1354 |
Instruction Following QwQ-32B leads
Llama 4 Scout: 65.8 (#217), QwQ-32B: 72.6 (#137)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| LMArena Instruction Following | 1248 | 1297 |
| LiveBench Instruction Following | — | 81.8% |
| IFEval | 81.8% | — |
Long Context QwQ-32B leads
Llama 4 Scout: 27.5 (#294), QwQ-32B: 49.0 (#11)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| Fiction.LiveBench | 36% | 83.3% |
| LMArena Longer Query | 1265 | 1308 |
Writing & Preference QwQ-32B leads
Llama 4 Scout: 37.0 (#261), QwQ-32B: 50.6 (#180)
| Benchmark | Llama 4 Scout | QwQ-32B |
|---|---|---|
| LMArena Text | 1279 | 1329 |
| LMArena Creative Writing | 1249 | 1288 |
| EQ-Bench Creative Writing | 783 | 1257 |
| LMArena Multi-Turn | 1280 | 1314 |
| Short-Story Creative Writing | — | 80.2% |
| WildBench | 78% | — |
| LiveBench Language | — | 51.4% |
Frequently asked questions
Is Llama 4 Scout better than QwQ-32B?
QwQ-32B is the stronger model overall, scoring 39.8 to 27.7 on the Noometry Index.
Is Llama 4 Scout or QwQ-32B better for coding?
QwQ-32B scores higher on coding benchmarks: 35.4 versus 20.2 in the Noometry coding category.
How many benchmarks do Llama 4 Scout and QwQ-32B share?
24 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and QwQ-32B has 36.