Model comparison
Llama 4 Maverick vs Qwen3.7 Flash
Qwen3.7 Flash is the stronger model overall, scoring 39.5 to 30.6 on the Noometry Index.
Last verified . 4 shared benchmarks.
Summary
- They share 4 benchmarks with published results for both. Llama 4 Maverick scores higher in 0 categories and Qwen3.7 Flash in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.7 Flash leads 27.3 to 10.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 20.6% for Llama 4 Maverick and 86.7% for Qwen3.7 Flash.
- Qwen3.7 Flash is cheaper at $0.03 / $0.13 per million input/output tokens, against $0.19 / $0.65 for Llama 4 Maverick.
- Qwen3.7 Flash accepts more context: 1M tokens versus 128K.
- Llama 4 Maverick has downloadable open weights; the other is API-only.
Side by side
| Llama 4 Maverick | Qwen3.7 Flash | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.6 | 39.5 |
| Released | 2025-04-05 | 2026-07-15 |
| Weights | Open | Proprietary |
| Context window | 128K | 1M |
| Max output | 4K | 131K |
| Input $ / M tokens | $0.19 | $0.03 |
| Output $ / M tokens | $0.65 | $0.13 |
| Results tracked | 54 | 7 |
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Category by category
Coding Not comparable
Llama 4 Maverick: 26.3 (#318), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| SciCode | 33.1% | — |
| WeirdML | 24.5% | — |
| BigCodeBench Instruct | 49.7% | — |
| LMArena Coding | 1302 | — |
| BigCodeBench Complete | 61.4% | — |
| ALE-Bench | 172.97 | — |
Agentic & Tool Use Not comparable
Llama 4 Maverick: 27.9 (#86), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | — |
Reasoning Qwen3.7 Flash leads
Llama 4 Maverick: 10.1 (#337), Qwen3.7 Flash: 27.3 (#108)
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| NYT Connections (extended) | 8% | 43.8% |
| Epoch Capabilities Index | 132.2 | 144.62 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| Kagi LLM Benchmark | 55.9% | — |
| ARC-AGI-1 | 4.4% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 23% |
| EnigmaEval | 0.6% | — |
| LMArena Hard Prompts | 1281 | — |
| Mystery Game Puzzles | — | 15% |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| ForecastBench | 57.5 | — |
Math Qwen3.7 Flash leads
Llama 4 Maverick: 24.6 (#256), Qwen3.7 Flash: 37.3 (#100)
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 20.6% | 86.7% |
| FrontierMath (Tiers 1-3) | — | 19.3% |
| Omni-MATH | 42.2% | — |
| LMArena Math | 1299 | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge Qwen3.7 Flash leads
Llama 4 Maverick: 33.3 (#196), Qwen3.7 Flash: 48.9 (#69)
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| GPQA Diamond | 67% | 82.3% |
| Humanity's Last Exam | 5.7% | — |
| MMLU-Pro | 81% | — |
| Confabulations | 22.6% | — |
| Vectara Hallucination Rate | 8.2% | — |
| GPQA (HELM) | 65% | — |
| LMArena Expert | 1259 | — |
Multimodal Not comparable
Llama 4 Maverick: 30.9 (#100), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| LMArena Vision | 1141 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |
Multilingual Not comparable
Llama 4 Maverick: 42.4 (#190), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| LMArena Non-English | 1269 | — |
| LMArena Chinese | 1277 | — |
| LMArena French | 1258 | — |
| LMArena German | 1291 | — |
| LMArena Japanese | 1207 | — |
| LMArena Korean | 1203 | — |
| LMArena Russian | 1286 | — |
| LMArena Spanish | 1293 | — |
Instruction Following Not comparable
Llama 4 Maverick: 71.9 (#140), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| IFEval | 90.8% | — |
| LMArena Instruction Following | 1267 | — |
Long Context Not comparable
Llama 4 Maverick: 31.4 (#274), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| Fiction.LiveBench | 46.2% | — |
| LMArena Longer Query | 1280 | — |
Writing & Preference Not comparable
Llama 4 Maverick: 39.0 (#247), Qwen3.7 Flash: —
| Benchmark | Llama 4 Maverick | Qwen3.7 Flash |
|---|---|---|
| LMArena Text | 1287 | — |
| LMArena Creative Writing | 1266 | — |
| Short-Story Creative Writing | 62% | — |
| EQ-Bench Creative Writing | 860 | — |
| WildBench | 80% | — |
| LMArena Multi-Turn | 1289 | — |
Frequently asked questions
Is Llama 4 Maverick better than Qwen3.7 Flash?
Qwen3.7 Flash is the stronger model overall, scoring 39.5 to 30.6 on the Noometry Index.
Which is cheaper, Llama 4 Maverick or Qwen3.7 Flash?
Qwen3.7 Flash is cheaper. It lists at $0.03 per million input tokens and $0.13 per million output tokens; Llama 4 Maverick lists at $0.19 and $0.65.
Which has the bigger context window?
Qwen3.7 Flash does, with 1M tokens against 128K.
How many benchmarks do Llama 4 Maverick and Qwen3.7 Flash share?
4 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and Qwen3.7 Flash has 7.