Model comparison
Llama 4 Maverick vs Qwen2.5 32B Instruct
Llama 4 Maverick and Qwen2.5 32B Instruct score almost the same on the Noometry Index (30.9 vs 30.1), so choose on price, context window or the category you care about most.
Last verified . 6 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 6 benchmarks with published results for both. Llama 4 Maverick scores higher in 2 categories and Qwen2.5 32B Instruct in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where Qwen2.5 32B Instruct leads 38.7 to 26.6.
- The biggest single-benchmark swing is GPQA Diamond: 67% for Llama 4 Maverick and 46.1% for Qwen2.5 32B Instruct.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
- Qwen2.5 32B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Llama 4 Maverick | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.9 | 30.1 |
| Released | 2025-04-05 | 2024-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 8K |
| Input $ / M tokens | $0.19 | $0.70 |
| Output $ / M tokens | $0.65 | $2.80 |
| Results tracked | 54 | 7 |
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Category by category
Coding Qwen2.5 32B Instruct leads
Llama 4 Maverick: 26.6 (#324), Qwen2.5 32B Instruct: 38.7 (#169)
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | 49.7% | 45% |
| BigCodeBench Complete | 61.4% | 52.3% |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| SciCode | 33.1% | — |
| WeirdML | 24.5% | — |
| LMArena Coding | 1302 | — |
| ALE-Bench | 172.97 | — |
Agentic & Tool Use Not comparable
Llama 4 Maverick: 28.2 (#91), Qwen2.5 32B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | — |
Reasoning Qwen2.5 32B Instruct leads
Llama 4 Maverick: 10.1 (#342), Qwen2.5 32B Instruct: 19.2 (#266)
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| Epoch Capabilities Index | 132.2 | 128.52 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| Kagi LLM Benchmark | 55.9% | — |
| NYT Connections (extended) | 8% | — |
| ARC-AGI-1 | 4.4% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 0.6% | — |
| LMArena Hard Prompts | 1281 | — |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| ForecastBench | 57.5 | — |
Math Llama 4 Maverick leads
Llama 4 Maverick: 26.0 (#262), Qwen2.5 32B Instruct: 16.2 (#296)
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 20.6% | 7.4% |
| MATH Level 5 | 73% | 56.1% |
| Omni-MATH | 42.2% | — |
| LMArena Math | 1299 | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge Llama 4 Maverick leads
Llama 4 Maverick: 33.4 (#204), Qwen2.5 32B Instruct: 24.9 (#266)
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 67% | 46.1% |
| 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: 31.6 (#105), Qwen2.5 32B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Vision | 1142 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |
Multilingual Not comparable
Llama 4 Maverick: 42.2 (#195), Qwen2.5 32B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1269 | — |
| LMArena Chinese | 1277 | — |
| LMArena French | 1259 | — |
| LMArena German | 1291 | — |
| LMArena Japanese | 1207 | — |
| LMArena Korean | 1203 | — |
| LMArena Russian | 1286 | — |
| LMArena Spanish | 1293 | — |
Instruction Following Not comparable
Llama 4 Maverick: 71.7 (#146), Qwen2.5 32B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| IFEval | 90.8% | — |
| LMArena Instruction Following | 1267 | — |
Long Context Not comparable
Llama 4 Maverick: 31.4 (#279), Qwen2.5 32B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| Fiction.LiveBench | 46.2% | — |
| LMArena Longer Query | 1280 | — |
Writing & Preference Not comparable
Llama 4 Maverick: 38.8 (#252), Qwen2.5 32B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1287 | — |
| LMArena Creative Writing | 1267 | — |
| 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 Qwen2.5 32B Instruct?
Llama 4 Maverick and Qwen2.5 32B Instruct score almost the same on the Noometry Index (30.9 vs 30.1), so choose on price, context window or the category you care about most.
Which is cheaper, Llama 4 Maverick or Qwen2.5 32B Instruct?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; Qwen2.5 32B Instruct lists at $0.70 and $2.80.
Is Llama 4 Maverick or Qwen2.5 32B Instruct better for coding?
Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.7 versus 26.6 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 32B Instruct does, with 131K tokens against 128K.
How many benchmarks do Llama 4 Maverick and Qwen2.5 32B Instruct share?
6 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and Qwen2.5 32B Instruct has 7.