Model comparison
GLM-5.1 vs Qwen3.6-35B-A3B
Head-to-head evidence from 28 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GLM-5.1 #12; Qwen3.6-35B-A3B #31
BenchAlign evidence: GLM-5.1 supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.1 and Qwen3.6-35B-A3B share 28 comparable benchmark results. 4 of 8 categories are comparable. 9 results are unique to GLM-5.1; 30 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 28
- GLM-5.1 only
- 9
- Qwen3.6-35B-A3B only
- 30
- Comparable categories
- 4 / 8
Pick GLM-5.1 if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if mathematics is the priority or you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 28 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
GLM-5.1 is clearly ahead on the provisional aggregate, 67 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.1's sharpest advantage is in agentic, where it averages 65.4 against 51.5. The single biggest benchmark swing on the page is HLE, 52.3% to 21.4%. Qwen3.6-35B-A3B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 203K for GLM-5.1.
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 | GLM-5.1 | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Math | GLM-5.162.0 | Margin→ 26.2 | Qwen3.6-35B-A3B88.2 |
| Agentic | GLM-5.165.4 | Margin← 13.9 | Qwen3.6-35B-A3B51.5 |
| Coding | GLM-5.161.3 | Margin→ 12.5 | Qwen3.6-35B-A3B73.8 |
| Knowledge | GLM-5.152.3 | Margin← 0.5 | Qwen3.6-35B-A3B51.8 |
| Multimodal | GLM-5.1Not measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 52.3%B 21.4%Winner: GLM-5.1Δ 30.9HLE: GLM-5.1 scored 52.3%; Qwen3.6-35B-A3B scored 21.4%. GLM-5.1 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 63.5%B 51.5%Winner: GLM-5.1Δ 12Terminal-Bench 2.0: GLM-5.1 scored 63.5%; Qwen3.6-35B-A3B scored 51.5%. GLM-5.1 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 58.4%B 49.5%Winner: GLM-5.1Δ 8.9SWE-bench Pro: GLM-5.1 scored 58.4%; Qwen3.6-35B-A3B scored 49.5%. GLM-5.1 wins this benchmark. - Source ↗
AIME26
MathA 95.3%B 92.7%Winner: GLM-5.1Δ 2.6AIME26: GLM-5.1 scored 95.3%; Qwen3.6-35B-A3B scored 92.7%. GLM-5.1 wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 82.6%B 83.6%Winner: Qwen3.6-35B-A3BΔ 1HMMT Feb 2026: GLM-5.1 scored 82.6%; Qwen3.6-35B-A3B scored 83.6%. 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 | GLM-5.1 | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.1$1.4 input / $4.4 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-5.1Not available | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.1Not available | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.1203K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
AgenticGLM-5.1 wins18 benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.5% | 51.5% | GLM-5.1 leads |
| BrowseCompSource | 68% | — | Not comparable |
| τ³-bench resultsSource | 70.6% | 67.2% | GLM-5.1 leads |
| MCP AtlasSource | 71.8% | 62.8% | GLM-5.1 leads |
| CyberGymSource | 68.7% | — | Not comparable |
| Claw-EvalSource | 62.3% | 68.7% | Qwen3.6-35B-A3B leads |
| AA Agentic IndexSource | 29.9% | 21.4% | GLM-5.1 leads |
| τ²-bench resultsSource | 97.7% | 95.3% | GLM-5.1 leads |
| GDPval-AASource | 37.8% | 27.4% | GLM-5.1 leads |
| Gert LabsSource | 60.11% | 42.65% | GLM-5.1 leads |
| GDPval-AASource | 1257 | 1049 | GLM-5.1 leads |
| ResearchClawBenchSource | 18.2% | — | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 26.9% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
CodingQwen3.6-35B-A3B wins11 benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.4% | 49.5% | GLM-5.1 leads |
| NL2RepoSource | 42.7% | 29.4% | GLM-5.1 leads |
| SWE-RebenchSource | 62.7% | — | Not comparable |
| Vibe Code BenchSource | 31.46% | — | Not comparable |
| AA Coding IndexSource | 55.8% | 41.9% | GLM-5.1 leads |
| Terminal-Bench HardSource | 43.2% | 34.8% | GLM-5.1 leads |
| AA-SciCodeSource | 43.8% | 35.8% | GLM-5.1 leads |
| SWE-bench VerifiedSource | — | 73.4% | Not comparable |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
Reasoning2 benchmarks
KnowledgeGLM-5.1 wins12 benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| GPQA-DSource | 86.2% | — | Not comparable |
| HLESource | 52.3% | 21.4% | GLM-5.1 leads |
| Artificial Analysis Intelligence IndexSource | 40.2% | 31.6% | GLM-5.1 leads |
| AA-GPQA DiamondSource | 86.8% | 84.1% | GLM-5.1 leads |
| AA-HLESource | 28.0% | 20.2% | GLM-5.1 leads |
| AA-Omniscience IndexSource | 1.9% | -21.4% | GLM-5.1 leads |
| AA-Omniscience AccuracySource | 24.2% | 18.9% | GLM-5.1 leads |
| AA-Omniscience Hallucination RateSource | 29.4% | 49.7% | GLM-5.1 leads |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| GPQASource | — | 86% | Not comparable |
MathQwen3.6-35B-A3B wins7 benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AIME26Source | 95.3% | 92.7% | GLM-5.1 leads |
| HMMT Nov 2025Source | 94.0% | 89.1% | GLM-5.1 leads |
| HMMT Feb 2026Source | 82.6% | 83.6% | Qwen3.6-35B-A3B leads |
| MMAnswerBenchSource | 83.8% | 78.9% | GLM-5.1 leads |
| FrontierMath v2 (Tiers 1-3)Source | 33.448% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 12.500% | — | Not comparable |
| HMMT Feb 2025Source | — | 90.7% | Not comparable |
Multimodal16 benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1312 | — | 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 |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.3% | 64.4% | GLM-5.1 leads |
Frequently Asked Questions (5)
Which is better, GLM-5.1 or Qwen3.6-35B-A3B?
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 67 to 59. The biggest single separator in this matchup is HLE, where the scores are 52.3% and 21.4%.
Which is better for knowledge tasks, GLM-5.1 or Qwen3.6-35B-A3B?
GLM-5.1 has the edge for knowledge tasks in this comparison, averaging 52.3 versus 51.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 73.8 versus 61.3. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for math, GLM-5.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 62. Inside this category, HMMT Nov 2025 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5.1 or Qwen3.6-35B-A3B?
GLM-5.1 has the edge for agentic tasks in this comparison, averaging 65.4 versus 51.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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