Model comparison
GLM-4.6 vs Qwen3.6-27B
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.6 #85 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.6 and Qwen3.6-27B share 11 comparable benchmark results. 1 of 8 categories are comparable. 3 results are unique to GLM-4.6; 43 to Qwen3.6-27B.
Updated July 23, 2026- Shared results
- 11
- GLM-4.6 only
- 3
- Qwen3.6-27B only
- 43
- Comparable categories
- 1 / 8
Pick GLM-4.6 if you want the stronger benchmark profile. Qwen3.6-27B 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 11 shared benchmark results across 5 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
GLM-4.6 has the cleaner BenchAlign overall profile here, landing at 55.12 versus 53.82. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.6-27B gives you the larger context window at 262K, compared with 200K for GLM-4.6.
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-4.6 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | GLM-4.63.4 | Margin→ 85.8 | Qwen3.6-27B89.2 |
| Agentic | GLM-4.6Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | GLM-4.6Not measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Knowledge | GLM-4.6Not measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Multimodal | GLM-4.6Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.6 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.6Not available | Qwen3.6-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.6Not available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.6Not available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.6200K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | GLM-4.6 | Qwen3.6-27B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 76.9% | 94.2% | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding9 benchmarks
| Benchmark | GLM-4.6 | Qwen3.6-27B | Result |
|---|---|---|---|
| Vibe Code BenchSource | 3.09% | — | Not comparable |
| AA-SciCodeSource | 33.1% | 39.8% | Qwen3.6-27B leads |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | GLM-4.6 | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.0% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 63.2% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 5.2% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -31.6% | -19.8% | Qwen3.6-27B leads |
| AA-Omniscience AccuracySource | 20.8% | 19.2% | GLM-4.6 leads |
| AA-Omniscience Hallucination RateSource | 66.1% | 48.3% | Qwen3.6-27B leads |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
MathQwen3.6-27B wins7 benchmarks
| Benchmark | GLM-4.6 | Qwen3.6-27B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 3.819% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.128% | — | Not comparable |
| HMMT Feb 2025Source | — | 93.8% | Not comparable |
| HMMT Nov 2025Source | — | 90.7% | Not comparable |
| HMMT Feb 2026Source | — | 84.3% | Not comparable |
| MMAnswerBenchSource | — | 80.8% | Not comparable |
| AIME26Source | — | 94.1% | Not comparable |
Multimodal16 benchmarks
| Benchmark | GLM-4.6 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-4.6 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 36.7% | 67.6% | Qwen3.6-27B leads |
Frequently Asked Questions (2)
Which is better, GLM-4.6 or Qwen3.6-27B?
GLM-4.6 is ahead on BenchLM's BenchAlign leaderboard, 55.12 to 53.82.
Which is better for math, GLM-4.6 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 3.4. GLM-4.6 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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