Model comparison
Qwen3.5-122B-A10B vs Qwen3.6-35B-A3B
Head-to-head evidence from 24 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Qwen3.5-122B-A10B #25; Qwen3.6-35B-A3B #31
BenchAlign evidence: Qwen3.5-122B-A10B supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Qwen3.5-122B-A10B and Qwen3.6-35B-A3B share 24 comparable benchmark results. 4 of 8 categories are comparable. 8 results are unique to Qwen3.5-122B-A10B; 34 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 24
- Qwen3.5-122B-A10B only
- 8
- Qwen3.6-35B-A3B only
- 34
- Comparable categories
- 4 / 8
Treat this as a split decision. Qwen3.5-122B-A10B makes more sense if knowledge is the priority; Qwen3.6-35B-A3B is the better fit if coding is the priority.
Confidence note. This is a partial-evidence comparison with 24 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.5-122B-A10B and Qwen3.6-35B-A3B finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
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 | Qwen3.5-122B-A10B | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Knowledge | Qwen3.5-122B-A10B83.6 | Margin← 31.8 | Qwen3.6-35B-A3B51.8 |
| Agentic | Qwen3.5-122B-A10B56.4 | Margin← 4.9 | Qwen3.6-35B-A3B51.5 |
| Coding | Qwen3.5-122B-A10B72.0 | Margin→ 1.8 | Qwen3.6-35B-A3B73.8 |
| Multimodal | Qwen3.5-122B-A10B77.2 | Margin← 0.9 | Qwen3.6-35B-A3B76.3 |
| Reasoning | Qwen3.5-122B-A10B60.2 | MarginNo overlap | Qwen3.6-35B-A3BNot measured |
| Math | Qwen3.5-122B-A10BNot measured | MarginNo overlap | Qwen3.6-35B-A3B88.2 |
| Multilingual | Qwen3.5-122B-A10B82.2 | MarginNo overlap | Qwen3.6-35B-A3BNot measured |
| Inst. Following | Qwen3.5-122B-A10B93.4 | MarginNo overlap | Qwen3.6-35B-A3BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SuperGPQA
KnowledgeA 67.1%B 64.7%Winner: Qwen3.5-122B-A10BΔ 2.4SuperGPQA: Qwen3.5-122B-A10B scored 67.1%; Qwen3.6-35B-A3B scored 64.7%. Qwen3.5-122B-A10B wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 49.4%B 51.5%Winner: Qwen3.6-35B-A3BΔ 2.1Terminal-Bench 2.0: Qwen3.5-122B-A10B scored 49.4%; Qwen3.6-35B-A3B scored 51.5%. Qwen3.6-35B-A3B wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 86.7%B 85.2%Winner: Qwen3.5-122B-A10BΔ 1.5MMLU-Pro: Qwen3.5-122B-A10B scored 86.7%; Qwen3.6-35B-A3B scored 85.2%. Qwen3.5-122B-A10B wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 72%B 73.4%Winner: Qwen3.6-35B-A3BΔ 1.4SWE-bench Verified: Qwen3.5-122B-A10B scored 72%; Qwen3.6-35B-A3B scored 73.4%. Qwen3.6-35B-A3B wins this benchmark. - Source ↗
CharXiv
MultimodalA 77.2%B 78%Winner: Qwen3.6-35B-A3BΔ 0.8CharXiv: Qwen3.5-122B-A10B scored 77.2%; Qwen3.6-35B-A3B scored 78%. Qwen3.6-35B-A3B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Qwen3.5-122B-A10B | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Qwen3.5-122B-A10B$0 input / $0 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Qwen3.5-122B-A10BNot available | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Qwen3.5-122B-A10BNot available | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Qwen3.5-122B-A10B262K | Qwen3.6-35B-A3B262K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticQwen3.5-122B-A10B wins17 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.4% | 51.5% | Qwen3.6-35B-A3B leads |
| BrowseCompSource | 63.8% | — | Not comparable |
| OSWorld-VerifiedSource | 58% | — | Not comparable |
| τ²-bench resultsSource | 93.6% | 95.3% | Qwen3.6-35B-A3B leads |
| AA Agentic IndexSource | 20.7% | 21.4% | Qwen3.6-35B-A3B leads |
| GDPval-AASource | 23.9% | 27.4% | Qwen3.6-35B-A3B leads |
| GDPval-AASource | 978 | 1049 | Qwen3.6-35B-A3B leads |
| 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 |
CodingQwen3.6-35B-A3B wins9 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 72% | 73.4% | Qwen3.6-35B-A3B leads |
| AA Coding IndexSource | 45.7% | 41.9% | Qwen3.5-122B-A10B leads |
| Terminal-Bench HardSource | 31.1% | 34.8% | Qwen3.6-35B-A3B leads |
| AA-SciCodeSource | 42.0% | 35.8% | Qwen3.5-122B-A10B leads |
| 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 |
Reasoning3 benchmarks
KnowledgeQwen3.5-122B-A10B wins11 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMLU-ProSource | 86.7% | 85.2% | Qwen3.5-122B-A10B leads |
| SuperGPQASource | 67.1% | 64.7% | Qwen3.5-122B-A10B leads |
| GPQASource | 86.6% | 86% | Qwen3.5-122B-A10B leads |
| Artificial Analysis Intelligence IndexSource | 32.3% | 31.6% | Qwen3.5-122B-A10B leads |
| AA-GPQA DiamondSource | 85.7% | 84.1% | Qwen3.5-122B-A10B leads |
| AA-HLESource | 23.4% | 20.2% | Qwen3.5-122B-A10B leads |
| AA-Omniscience IndexSource | -39.6% | -21.4% | Qwen3.6-35B-A3B leads |
| AA-Omniscience AccuracySource | 24.7% | 18.9% | Qwen3.5-122B-A10B leads |
| AA-Omniscience Hallucination RateSource | 85.5% | 49.7% | Qwen3.6-35B-A3B leads |
| C-EvalSource | — | 90% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
Math5 benchmarks
Multilingual1 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMLU-ProXSource | 82.2% | — | Not comparable |
MultimodalQwen3.5-122B-A10B wins18 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMMUSource | 83.9% | 81.7% | Qwen3.5-122B-A10B leads |
| MMVUSource | 74.7% | — | Not comparable |
| MathVisionSource | 86.2% | — | Not comparable |
| CharXivSource | 77.2% | 78% | Qwen3.6-35B-A3B leads |
| V*Source | 93.2% | — | Not comparable |
| AA-MMMU-ProSource | 75.0% | 75.0% | Tie |
| MMMU-ProSource | — | 75.3% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | 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 |
Frequently Asked Questions (5)
Which is better, Qwen3.5-122B-A10B or Qwen3.6-35B-A3B?
Qwen3.5-122B-A10B and Qwen3.6-35B-A3B are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Qwen3.5-122B-A10B or Qwen3.6-35B-A3B?
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 83.6 versus 51.8. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Qwen3.5-122B-A10B or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 73.8 versus 72. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Qwen3.5-122B-A10B or Qwen3.6-35B-A3B?
Qwen3.5-122B-A10B has the edge for agentic tasks in this comparison, averaging 56.4 versus 51.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Qwen3.5-122B-A10B or Qwen3.6-35B-A3B?
Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 77.2 versus 76.3. Inside this category, MMMU is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.