Model comparison
Llama 4 Maverick vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 30.9 on the Noometry Index. Llama 4 Maverick costs 2.9× less per token, which makes it the better buy when Qwen3-Next 80B-A3B Instruct's lead doesn't matter for your workload.
Last verified . 25 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 25 benchmarks with published results for both. Llama 4 Maverick scores higher in 1 category and Qwen3-Next 80B-A3B Instruct in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3-Next 80B-A3B Instruct leads 31.1 to 10.1.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 55.9% for Llama 4 Maverick and 66.7% for Qwen3-Next 80B-A3B Instruct.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $0.50 / $2 for Qwen3-Next 80B-A3B Instruct.
- Qwen3-Next 80B-A3B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.9 | 43.0 |
| Released | 2025-04-05 | 2025-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 33K |
| Input $ / M tokens | $0.19 | $0.50 |
| Output $ / M tokens | $0.65 | $2 |
| Results tracked | 54 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 26.6 (#324), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1302 | 1440 |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| SciCode | 33.1% | — |
| WeirdML | 24.5% | — |
| BigCodeBench Instruct | 49.7% | — |
| BigCodeBench Complete | 61.4% | — |
| ALE-Bench | 172.97 | — |
Agentic & Tool Use Not comparable
Llama 4 Maverick: 28.2 (#91), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 10.1 (#342), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 55.9% | 66.7% |
| LMArena Hard Prompts | 1281 | 1428 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| NYT Connections (extended) | 8% | — |
| ARC-AGI-1 | 4.4% | — |
| CritPt | 0% | — |
| EnigmaEval | 0.6% | — |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| Epoch Capabilities Index | 132.2 | — |
| ForecastBench | 57.5 | — |
Math Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 26.0 (#262), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Omni-MATH | 42.2% | 46.7% |
| LMArena Math | 1299 | 1440 |
| OTIS Mock AIME 2024-2025 | 20.6% | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 33.4 (#204), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| MMLU-Pro | 81% | 78.6% |
| Vectara Hallucination Rate | 8.2% | 9.3% |
| GPQA (HELM) | 65% | 63% |
| LMArena Expert | 1259 | 1417 |
| GPQA Diamond | 67% | — |
| Humanity's Last Exam | 5.7% | — |
| Confabulations | 22.6% | — |
Multimodal Not comparable
Llama 4 Maverick: 31.6 (#105), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Vision | 1142 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |
Multilingual Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 42.2 (#195), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1269 | 1407 |
| LMArena Chinese | 1277 | 1460 |
| LMArena French | 1259 | 1413 |
| LMArena German | 1291 | 1417 |
| LMArena Japanese | 1207 | 1395 |
| LMArena Korean | 1203 | 1364 |
| LMArena Russian | 1286 | 1404 |
| LMArena Spanish | 1293 | 1435 |
Instruction Following Too close to call
Llama 4 Maverick: 71.7 (#146), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| IFEval | 90.8% | 81% |
| LMArena Instruction Following | 1267 | 1389 |
Long Context Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 31.4 (#279), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Fiction.LiveBench | 46.2% | 55.6% |
| LMArena Longer Query | 1280 | 1403 |
Writing & Preference Qwen3-Next 80B-A3B Instruct leads
Llama 4 Maverick: 38.8 (#252), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Llama 4 Maverick | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1287 | 1417 |
| LMArena Creative Writing | 1267 | 1334 |
| WildBench | 80% | 80.7% |
| LMArena Multi-Turn | 1289 | 1416 |
| Short-Story Creative Writing | 62% | — |
| EQ-Bench Creative Writing | 860 | — |
Frequently asked questions
Is Llama 4 Maverick better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 30.9 on the Noometry Index. Llama 4 Maverick costs 2.9× less per token, which makes it the better buy when Qwen3-Next 80B-A3B Instruct's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Maverick or Qwen3-Next 80B-A3B Instruct?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; Qwen3-Next 80B-A3B Instruct lists at $0.50 and $2.
Is Llama 4 Maverick or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 26.6 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct does, with 131K tokens against 128K.
How many benchmarks do Llama 4 Maverick and Qwen3-Next 80B-A3B Instruct share?
25 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.