Model comparison
Llama 4 Maverick vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.9 on the Noometry Index. Llama 4 Maverick costs 2.0× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Last verified . 11 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 11 benchmarks with published results for both. Llama 4 Maverick scores higher in 0 categories and Qwen3 14B in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 14B leads 38.6 to 26.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 20.6% for Llama 4 Maverick and 66.4% for Qwen3 14B.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Qwen3 14B accepts more context: 131K tokens versus 128K.
Side by side
| Llama 4 Maverick | Qwen3 14B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.9 | 35.5 |
| Released | 2025-04-05 | 2025-04 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 8K |
| Input $ / M tokens | $0.19 | $0.35 |
| Output $ / M tokens | $0.65 | $1.40 |
| Results tracked | 54 | 12 |
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Category by category
Coding Qwen3 14B leads
Llama 4 Maverick: 26.6 (#324), Qwen3 14B: 37.3 (#195)
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| SciCode | 33.1% | 31.6% |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| WeirdML | 24.5% | — |
| BigCodeBench Instruct | 49.7% | — |
| LMArena Coding | 1302 | — |
| BigCodeBench Complete | 61.4% | — |
| ALE-Bench | 172.97 | — |
Agentic & Tool Use Qwen3 14B leads
Llama 4 Maverick: 28.2 (#91), Qwen3 14B: 29.6 (#83)
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | 41% |
Reasoning Qwen3 14B leads
Llama 4 Maverick: 10.1 (#342), Qwen3 14B: 18.5 (#280)
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 55.9% | 49.1% |
| CritPt | 0% | 0% |
| DTBench | 61.9% | 64% |
| LMCA | 15.9% | 18.2% |
| Epoch Capabilities Index | 132.2 | 138.23 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| NYT Connections (extended) | 8% | — |
| ARC-AGI-1 | 4.4% | — |
| Chess Puzzles | — | 4% |
| EnigmaEval | 0.6% | — |
| LMArena Hard Prompts | 1281 | — |
| ForecastBench | 57.5 | — |
Math Qwen3 14B leads
Llama 4 Maverick: 26.0 (#262), Qwen3 14B: 38.6 (#133)
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 20.6% | 66.4% |
| Omni-MATH | 42.2% | — |
| LMArena Math | 1299 | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge Qwen3 14B leads
Llama 4 Maverick: 33.4 (#204), Qwen3 14B: 39.3 (#134)
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 67% | 63.8% |
| Vectara Hallucination Rate | 8.2% | 5.4% |
| Humanity's Last Exam | 5.7% | — |
| MMLU-Pro | 81% | — |
| Confabulations | 22.6% | — |
| GPQA (HELM) | 65% | — |
| LMArena Expert | 1259 | — |
Multimodal Not comparable
Llama 4 Maverick: 31.6 (#105), Qwen3 14B: —
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1142 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |
Multilingual Not comparable
Llama 4 Maverick: 42.2 (#195), Qwen3 14B: —
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| 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), Qwen3 14B: —
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| IFEval | 90.8% | — |
| LMArena Instruction Following | 1267 | — |
Long Context Qwen3 14B leads
Llama 4 Maverick: 31.4 (#279), Qwen3 14B: 38.1 (#204)
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | 46.2% | 62.5% |
| LMArena Longer Query | 1280 | — |
Writing & Preference Not comparable
Llama 4 Maverick: 38.8 (#252), Qwen3 14B: —
| Benchmark | Llama 4 Maverick | Qwen3 14B |
|---|---|---|
| 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 Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.9 on the Noometry Index. Llama 4 Maverick costs 2.0× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Maverick or Qwen3 14B?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is Llama 4 Maverick or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 26.6 in the Noometry coding category.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 128K.
How many benchmarks do Llama 4 Maverick and Qwen3 14B share?
11 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and Qwen3 14B has 12.