Model comparison
Llama 4 Maverick vs Qwen3.6-35B-A3B
Head-to-head evidence from 17 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Llama 4 Maverick unranked; Qwen3.6-35B-A3B #31
BenchAlign evidence: Llama 4 Maverick supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Maverick and Qwen3.6-35B-A3B share 17 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to Llama 4 Maverick; 41 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 17
- Llama 4 Maverick only
- 2
- Qwen3.6-35B-A3B only
- 41
- Comparable categories
- 1 / 8
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Llama 4 Maverick only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 59 to 18. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B's sharpest advantage is in mathematics, where it averages 88.2 against 0.7.
Qwen3.6-35B-A3B is the reasoning model in the pair, while Llama 4 Maverick is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Llama 4 Maverick gives you the larger context window at 1M, compared with 262K for Qwen3.6-35B-A3B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Llama 4 Maverick | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Math | Llama 4 Maverick0.7 | Margin→ 87.5 | Qwen3.6-35B-A3B88.2 |
| Agentic | Llama 4 MaverickNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Coding | Llama 4 MaverickNot measured | MarginNo overlap | Qwen3.6-35B-A3B73.8 |
| Knowledge | Llama 4 MaverickNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.8 |
| Multimodal | Llama 4 MaverickNot measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Maverick | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Maverick$0 input / $0 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Llama 4 Maverick121 tok/s | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Llama 4 Maverick0.95 s | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Llama 4 Maverick1M | Qwen3.6-35B-A3B262K | Llama 4 Maverick lists the larger context window. |
Benchmark Deep Dive
Agentic15 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 1.3% | 21.4% | Qwen3.6-35B-A3B leads |
| τ²-bench resultsSource | 17.8% | 95.3% | Qwen3.6-35B-A3B leads |
| GDPval-AASource | 0.0% | 27.4% | Qwen3.6-35B-A3B leads |
| GDPval-AASource | -16 | 1049 | Qwen3.6-35B-A3B leads |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| Claw-EvalSource | — | 68.7% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 26.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| Gert LabsSource | — | 42.65% | Not comparable |
Coding9 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA Coding IndexSource | 16.3% | 41.9% | Qwen3.6-35B-A3B leads |
| Terminal-Bench HardSource | 6.8% | 34.8% | Qwen3.6-35B-A3B leads |
| AA-SciCodeSource | 33.1% | 35.8% | Qwen3.6-35B-A3B leads |
| SWE-bench VerifiedSource | — | 73.4% | Not comparable |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| SWE-bench ProSource | — | 49.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
| NL2RepoSource | — | 29.4% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.3% | 31.6% | Qwen3.6-35B-A3B leads |
| AA-GPQA DiamondSource | 67.1% | 84.1% | Qwen3.6-35B-A3B leads |
| AA-HLESource | 4.8% | 20.2% | Qwen3.6-35B-A3B leads |
| AA-Omniscience IndexSource | -41.8% | -21.4% | Qwen3.6-35B-A3B leads |
| AA-Omniscience AccuracySource | 24.3% | 18.9% | Llama 4 Maverick leads |
| AA-Omniscience Hallucination RateSource | 87.3% | 49.7% | Qwen3.6-35B-A3B leads |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| GPQASource | — | 86% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
MathQwen3.6-35B-A3B wins6 benchmarks
Multimodal16 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 62.1% | 75.0% | Qwen3.6-35B-A3B leads |
| Design Arena WebsiteSource | 905 | — | Not comparable |
| MMMUSource | — | 81.7% | Not comparable |
| MMMU-ProSource | — | 75.3% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | Not comparable |
| CharXivSource | — | 78% | Not comparable |
| SimpleVQASource | — | 58.9% | Not comparable |
| CC-OCRSource | — | 81.9% | Not comparable |
| AI2D_TESTSource | — | 92.7% | Not comparable |
| RefCOCO (avg)Source | — | 92.0% | Not comparable |
| ODINW13Source | — | 50.8% | Not comparable |
| Video-MME (with subtitle)Source | — | 86.6% | Not comparable |
| Video-MME (w/o subtitle)Source | — | 82.5% | Not comparable |
| VideoMMMUSource | — | 83.7% | Not comparable |
| MLVU (M-Avg)Source | — | 86.2% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.0% | 64.4% | Qwen3.6-35B-A3B leads |
Frequently Asked Questions (2)
Which is better, Llama 4 Maverick or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 59 to 18.
Which is better for math, Llama 4 Maverick or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 0.7. Llama 4 Maverick stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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