Model comparison
GLM-5 vs Qwen3.6 Plus
Head-to-head evidence from 41 shared benchmark results across 8 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5 #28 (Supported); Qwen3.6 Plus #30 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5 and Qwen3.6 Plus share 41 comparable benchmark results. 7 of 8 categories are comparable. 8 results are unique to GLM-5; 19 to Qwen3.6 Plus.
Updated July 23, 2026- Shared results
- 41
- GLM-5 only
- 8
- Qwen3.6 Plus only
- 19
- Comparable categories
- 7 / 8
Pick GLM-5 if you want the stronger benchmark profile. Qwen3.6 Plus only becomes the better choice if agentic is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 41 shared benchmark results across 8 evidence categories; 7 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 has the cleaner BenchAlign overall profile here, landing at 66.06 versus 65.2. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GLM-5's sharpest advantage is in instruction following, where it averages 92.6 against 82.3. The single biggest benchmark swing on the page is HLE, 50.4% to 28.8%. Qwen3.6 Plus does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Qwen3.6 Plus is the reasoning model in the pair, while GLM-5 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. Qwen3.6 Plus gives you the larger context window at 1M, compared with 200K for GLM-5.
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 | Δ | Qwen3.6 Plus |
|---|---|---|---|
| Inst. Following | GLM-592.6 | Margin← 10.3 | Qwen3.6 Plus82.3 |
| Knowledge | GLM-566.4 | Margin← 9.3 | Qwen3.6 Plus57.1 |
| Agentic | GLM-556.2 | Margin→ 5.4 | Qwen3.6 Plus61.6 |
| Math | GLM-556.3 | Margin→ 4.2 | Qwen3.6 Plus60.5 |
| Coding | GLM-566.3 | Margin→ 4.0 | Qwen3.6 Plus70.3 |
| Multilingual | GLM-583.1 | Margin→ 1.6 | Qwen3.6 Plus84.7 |
| Reasoning | GLM-560.8 | Margin→ 1.2 | Qwen3.6 Plus62.0 |
| Multimodal | GLM-5Not measured | MarginNo overlap | Qwen3.6 Plus79.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 50.4%B 28.8%Winner: GLM-5Δ 21.6HLE: GLM-5 scored 50.4%; Qwen3.6 Plus scored 28.8%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 16.434%B 26.207%Winner: Qwen3.6 PlusΔ 9.8FrontierMath v2 (Tiers 1-3): GLM-5 scored 16.434%; Qwen3.6 Plus scored 26.207%. Qwen3.6 Plus wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 2.100%B 8.333%Winner: Qwen3.6 PlusΔ 6.2FrontierMath v2 (Tier 4): GLM-5 scored 2.100%; Qwen3.6 Plus scored 8.333%. Qwen3.6 Plus wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 56.2%B 61.6%Winner: Qwen3.6 PlusΔ 5.4Terminal-Bench 2.0: GLM-5 scored 56.2%; Qwen3.6 Plus scored 61.6%. Qwen3.6 Plus wins this benchmark. - Source ↗
SuperGPQA
KnowledgeA 66.8%B 71.6%Winner: Qwen3.6 PlusΔ 4.8SuperGPQA: GLM-5 scored 66.8%; Qwen3.6 Plus scored 71.6%. Qwen3.6 Plus wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5 | Qwen3.6 Plus | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5$1 input / $3.2 output | Qwen3.6 PlusNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-574 tok/s | Qwen3.6 PlusNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-51.64 s | Qwen3.6 PlusNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5200K | Qwen3.6 Plus1M | Qwen3.6 Plus lists the larger context window. |
Benchmark Deep Dive
AgenticQwen3.6 Plus wins18 benchmarks
| Benchmark | GLM-5 | Qwen3.6 Plus | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.2% | 61.6% | Qwen3.6 Plus leads |
| Claw-EvalSource | 57.7% | 58.8% | Qwen3.6 Plus leads |
| QwenClawBenchSource | 54.1% | 57.2% | Qwen3.6 Plus leads |
| τ³-bench resultsSource | 65.6% | 70.7% | Qwen3.6 Plus leads |
| DeepPlanningSource | 14.6% | 41.5% | Qwen3.6 Plus leads |
| ToolathlonSource | 38% | 39.8% | Qwen3.6 Plus leads |
| MCP AtlasSource | 31.1% | 48.2% | Qwen3.6 Plus leads |
| MCP-TasksSource | 60.8% | 74.1% | Qwen3.6 Plus leads |
| WideResearchSource | 69.8% | 74.3% | Qwen3.6 Plus leads |
| τ²-bench resultsSource | 98.2% | 97.7% | GLM-5 leads |
| CyberGymSource | 43.2% | — | Not comparable |
| APEX-Agents-AASource | 14.5% | — | Not comparable |
| Gert LabsSource | 50.99% | 50.60% | GLM-5 leads |
| VITA-BenchSource | — | 44.3% | Not comparable |
| AA Agentic IndexSource | — | 27.6% | Not comparable |
| GDPval-AASource | — | 31.8% | Not comparable |
| GDPval-AASource | — | 1135 | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
CodingQwen3.6 Plus wins10 benchmarks
| Benchmark | GLM-5 | Qwen3.6 Plus | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.8% | 78.8% | Qwen3.6 Plus leads |
| SWE-bench Verified*Source | 72.8% | — | Not comparable |
| SWE-bench ProSource | 55.1% | 56.6% | Qwen3.6 Plus leads |
| SWE MultilingualSource | 73.3% | 73.8% | Qwen3.6 Plus leads |
| SWE-RebenchSource | 62.8% | — | Not comparable |
| React Native EvalsSource | 74.8% | — | Not comparable |
| AA-SciCodeSource | 46.2% | 40.7% | GLM-5 leads |
| LiveCodeBench v6Source | — | 87.1% | Not comparable |
| Vibe Code BenchSource | — | 25.56% | Not comparable |
| AA Coding IndexSource | — | 54.5% | Not comparable |
ReasoningQwen3.6 Plus wins4 benchmarks
KnowledgeGLM-5 wins14 benchmarks
| Benchmark | GLM-5 | Qwen3.6 Plus | Result |
|---|---|---|---|
| GPQASource | 86% | 90.4% | Qwen3.6 Plus leads |
| GPQA-DSource | 86.0% | — | Not comparable |
| SuperGPQASource | 66.8% | 71.6% | Qwen3.6 Plus leads |
| MMLU-ProSource | 85.7% | 88.5% | Qwen3.6 Plus leads |
| MMLU-Pro (Arcee)Source | 85.8% | — | Not comparable |
| HLESource | 50.4% | 28.8% | GLM-5 leads |
| Artificial Analysis Intelligence IndexSource | 39.5% | 39.6% | Qwen3.6 Plus leads |
| AA-GPQA DiamondSource | 82.0% | 88.2% | Qwen3.6 Plus leads |
| AA-HLESource | 27.2% | 25.7% | GLM-5 leads |
| AA-Omniscience IndexSource | 2.0% | 2.7% | Qwen3.6 Plus leads |
| AA-Omniscience AccuracySource | 26.9% | 26.2% | GLM-5 leads |
| AA-Omniscience Hallucination RateSource | 34.0% | 32.0% | Qwen3.6 Plus leads |
| MMLU-ReduxSource | — | 94.5% | Not comparable |
| C-EvalSource | — | 93.3% | Not comparable |
MathQwen3.6 Plus wins8 benchmarks
| Benchmark | GLM-5 | Qwen3.6 Plus | Result |
|---|---|---|---|
| AIME26Source | 95.8% | 95.3% | GLM-5 leads |
| AIME25 (Arcee)Source | 93.3% | — | Not comparable |
| HMMT Feb 2025Source | 97.5% | 96.7% | GLM-5 leads |
| HMMT Nov 2025Source | 96.9% | 94.6% | GLM-5 leads |
| HMMT Feb 2026Source | 86.4% | 87.8% | Qwen3.6 Plus leads |
| MMAnswerBenchSource | 82.5% | 83.8% | Qwen3.6 Plus leads |
| FrontierMath v2 (Tiers 1-3)Source | 16.434% | 26.207% | Qwen3.6 Plus leads |
| FrontierMath v2 (Tier 4)Source | 2.100% | 8.333% | Qwen3.6 Plus leads |
MultilingualQwen3.6 Plus wins2 benchmarks
Multimodal9 benchmarks
| Benchmark | GLM-5 | Qwen3.6 Plus | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1278 | 1249 | GLM-5 leads |
| MMMUSource | — | 86.0% | Not comparable |
| MMMU-ProSource | — | 78.8% | Not comparable |
| MathVisionSource | — | 88.0% | Not comparable |
| VideoMMMUSource | — | 84.0% | Not comparable |
| ScreenSpot ProSource | — | 68.2% | Not comparable |
| CharXivSource | — | 81.5% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| AA-MMMU-ProSource | — | 78.0% | Not comparable |
Frequently Asked Questions (8)
Which is better, GLM-5 or Qwen3.6 Plus?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 65.2. The biggest single separator in this matchup is HLE, where the scores are 50.4% and 28.8%.
Which is better for knowledge tasks, GLM-5 or Qwen3.6 Plus?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 57.1. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for coding in this comparison, averaging 70.3 versus 66.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, GLM-5 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for math in this comparison, averaging 60.5 versus 56.3. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Which is better for reasoning, GLM-5 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for reasoning in this comparison, averaging 62 versus 60.8. Inside this category, AA-LCR is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for agentic tasks in this comparison, averaging 61.6 versus 56.2. Inside this category, DeepPlanning is the benchmark that creates the most daylight between them.
Which is better for instruction following, GLM-5 or Qwen3.6 Plus?
GLM-5 has the edge for instruction following in this comparison, averaging 92.6 versus 82.3. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
Which is better for multilingual tasks, GLM-5 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for multilingual tasks in this comparison, averaging 84.7 versus 83.1. Inside this category, NOVA-63 is the benchmark that creates the most daylight between them.
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