Model comparison
Llama 4 Scout vs Qwen3.6 Flash
Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 27.7 on the Noometry Index. Llama 4 Scout costs 2.8× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.
Last verified . 6 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 6 benchmarks with published results for both. Llama 4 Scout scores higher in 0 categories and Qwen3.6 Flash in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.6 Flash leads 29.0 to 9.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 7.8% for Llama 4 Scout and 84.4% for Qwen3.6 Flash.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.19 / $1.13 for Qwen3.6 Flash.
- Qwen3.6 Flash accepts more context: 1M tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Llama 4 Scout | Qwen3.6 Flash | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 27.7 | 38.8 |
| Released | 2025-04-05 | 2026-04-27 |
| Weights | Open | Proprietary |
| Context window | 128K | 1M |
| Max output | 4K | 66K |
| Input $ / M tokens | $0.10 | $0.19 |
| Output $ / M tokens | $0.30 | $1.13 |
| Results tracked | 43 | 13 |
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Category by category
Coding Not comparable
Llama 4 Scout: 20.2 (#339), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| LMArena Coding | 1286 | — |
| BigCodeBench Complete | 43.1% | — |
| ALE-Bench | — | 326.4 |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.6 (#119), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning Qwen3.6 Flash leads
Llama 4 Scout: 9.1 (#345), Qwen3.6 Flash: 29.0 (#96)
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| DTBench | 57.9% | 77.1% |
| LMCA | 12% | 31% |
| Epoch Capabilities Index | 129.64 | 143.26 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | — | 35.2% |
| Kagi LLM Benchmark | 36.9% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 20% |
| LMArena Hard Prompts | 1266 | — |
| Mystery Game Puzzles | — | 18% |
| ForecastBench | 57.5 | — |
Math Qwen3.6 Flash leads
Llama 4 Scout: 19.6 (#286), Qwen3.6 Flash: 39.0 (#117)
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.8% | 84.4% |
| FrontierMath (Feb 2025 set) | 0% | 10.3% |
| FrontierMath (Tiers 1-3) | — | 22.5% |
| Omni-MATH | 37.3% | — |
| LMArena Math | 1287 | — |
| MATH Level 5 | 62.3% | — |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3.6 Flash leads
Llama 4 Scout: 31.9 (#217), Qwen3.6 Flash: 42.1 (#100)
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| GPQA Diamond | 51.8% | 83.3% |
| SimpleQA Verified | — | 15.9% |
| MMLU-Pro | 74.2% | — |
| Vectara Hallucination Rate | 7.7% | — |
| GPQA (HELM) | 50.7% | — |
| LMArena Expert | 1235 | — |
Multimodal Not comparable
Llama 4 Scout: 32.2 (#102), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual Not comparable
Llama 4 Scout: 41.0 (#212), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| LMArena Non-English | 1252 | — |
| LMArena Chinese | 1255 | — |
| LMArena French | 1282 | — |
| LMArena German | 1272 | — |
| LMArena Japanese | 1206 | — |
| LMArena Korean | 1207 | — |
| LMArena Russian | 1263 | — |
| LMArena Spanish | 1278 | — |
Instruction Following Not comparable
Llama 4 Scout: 65.8 (#217), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| IFEval | 81.8% | — |
| LMArena Instruction Following | 1248 | — |
Long Context Not comparable
Llama 4 Scout: 27.5 (#294), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| Fiction.LiveBench | 36% | — |
| LMArena Longer Query | 1265 | — |
Writing & Preference Not comparable
Llama 4 Scout: 37.0 (#261), Qwen3.6 Flash: —
| Benchmark | Llama 4 Scout | Qwen3.6 Flash |
|---|---|---|
| LMArena Text | 1279 | — |
| LMArena Creative Writing | 1249 | — |
| EQ-Bench Creative Writing | 783 | — |
| WildBench | 78% | — |
| LMArena Multi-Turn | 1280 | — |
Frequently asked questions
Is Llama 4 Scout better than Qwen3.6 Flash?
Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 27.7 on the Noometry Index. Llama 4 Scout costs 2.8× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Scout or Qwen3.6 Flash?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Qwen3.6 Flash lists at $0.19 and $1.13.
Which has the bigger context window?
Qwen3.6 Flash does, with 1M tokens against 128K.
How many benchmarks do Llama 4 Scout and Qwen3.6 Flash share?
6 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and Qwen3.6 Flash has 13.