Model comparison
Llama 4 Maverick vs Qwen3 235B 2507
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Llama 4 Maverick #191 (Supported); Qwen3 235B 2507 #78 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Maverick and Qwen3 235B 2507 share 0 comparable benchmark results. 0 of 8 categories are comparable. 18 results are unique to Llama 4 Maverick; 4 to Qwen3 235B 2507.
Updated July 22, 2026- Shared results
- 0
- Llama 4 Maverick only
- 18
- Qwen3 235B 2507 only
- 4
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Maverick and Qwen3 235B 2507 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Llama 4 Maverick has the larger context window at 1M, compared with 128K for Qwen3 235B 2507.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Maverick | Qwen3 235B 2507 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Maverick$0 input / $0 output | Qwen3 235B 2507$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Llama 4 Maverick121 tok/s | Qwen3 235B 2507Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Llama 4 Maverick0.95 s | Qwen3 235B 2507Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Llama 4 Maverick1M | Qwen3 235B 2507128K | Llama 4 Maverick lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3 235B 2507 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.3% | — | Not comparable |
| AA-GPQA DiamondSource | 67.1% | — | Not comparable |
| AA-HLESource | 4.8% | — | Not comparable |
| AA-Omniscience IndexSource | -41.8% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 87.3% | — | Not comparable |
| GPQASource | — | 77.5% | Not comparable |
| SuperGPQASource | — | 62.6% | Not comparable |
| MMLU-ProSource | — | 83% | Not comparable |
Math1 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3 235B 2507 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 0.690% | — | Not comparable |
Multilingual1 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3 235B 2507 | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 79.4% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Llama 4 Maverick | Qwen3 235B 2507 | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.0% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Llama 4 Maverick and Qwen3 235B 2507 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Llama 4 Maverick and Qwen3 235B 2507 today?
Llama 4 Maverick: $0.00 input / $0.00 output per 1M tokens Qwen3 235B 2507: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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