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Model comparison

GLM-4.6 vs Qwen3.5-35B-A3B

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.12/100
Margin
1.9pts
winning →
56.97/100
0 category wins0 category wins

Public leaderboard positions: GLM-4.6 #85 (Supported); Qwen3.5-35B-A3B #72 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.6 and Qwen3.5-35B-A3B share 11 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to GLM-4.6; 17 to Qwen3.5-35B-A3B.

Updated July 23, 2026
Shared results
11
GLM-4.6 only
3
Qwen3.5-35B-A3B only
17
Comparable categories
0 / 8

Benchmark data for GLM-4.6 and Qwen3.5-35B-A3B is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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.

Qwen3.5-35B-A3B has 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 scores and score margins for GLM-4.6 and Qwen3.5-35B-A3B
CategoryGLM-4.6ΔQwen3.5-35B-A3B
AgenticGLM-4.6Not measuredMarginNo overlapQwen3.5-35B-A3B51.0
CodingGLM-4.6Not measuredMarginNo overlapQwen3.5-35B-A3B60.6
ReasoningGLM-4.6Not measuredMarginNo overlapQwen3.5-35B-A3B59.0
KnowledgeGLM-4.6Not measuredMarginNo overlapQwen3.5-35B-A3B81.6
MathGLM-4.63.4MarginNo overlapQwen3.5-35B-A3BNot measured
MultilingualGLM-4.6Not measuredMarginNo overlapQwen3.5-35B-A3B81.0
Inst. FollowingGLM-4.6Not measuredMarginNo overlapQwen3.5-35B-A3B91.9

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGLM-4.6Qwen3.5-35B-A3BComparison
Input / output priceUSD per 1M tokensGLM-4.6Not availableQwen3.5-35B-A3B$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondGLM-4.6Not availableQwen3.5-35B-A3BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-4.6Not availableQwen3.5-35B-A3BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-4.6200KQwen3.5-35B-A3B262KQwen3.5-35B-A3B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
τ²-bench resultsSource 76.9%89.2%Qwen3.5-35B-A3B leads
Terminal-Bench 2.0Source 40.5%Not comparable
BrowseCompSource 61%Not comparable
OSWorld-VerifiedSource 54.5%Not comparable
Gert LabsSource 28.96%Not comparable
Coding
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
Vibe Code BenchSource 3.09%Not comparable
AA-SciCodeSource 33.1%37.7%Qwen3.5-35B-A3B leads
SWE-bench VerifiedSource 69.2%Not comparable
SWE-RebenchSource 53.7%Not comparable
Reasoning
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
AA-LCRSource 26.3%62.7%Qwen3.5-35B-A3B leads
CritPtSource 0.0%0.9%Qwen3.5-35B-A3B leads
LongBench v2Source 59%Not comparable
Knowledge
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
Artificial Analysis Intelligence IndexSource 23.0%29.3%Qwen3.5-35B-A3B leads
AA-GPQA DiamondSource 63.2%84.5%Qwen3.5-35B-A3B leads
AA-HLESource 5.2%19.7%Qwen3.5-35B-A3B leads
AA-Omniscience IndexSource -31.6%-46.4%GLM-4.6 leads
AA-Omniscience AccuracySource 20.8%20.5%GLM-4.6 leads
AA-Omniscience Hallucination RateSource 66.1%84.0%GLM-4.6 leads
MMLU-ProSource 85.3%Not comparable
SuperGPQASource 63.4%Not comparable
GPQASource 84.2%Not comparable
Math
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
FrontierMath v2 (Tiers 1-3)Source 3.819%Not comparable
FrontierMath v2 (Tier 4)Source 2.128%Not comparable
Multilingual
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
MMLU-ProXSource 81%Not comparable
Multimodal
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
MMMUSource 81.4%Not comparable
MMVUSource 72.3%Not comparable
MathVisionSource 83.9%Not comparable
V*Source 92.7%Not comparable
AA-MMMU-ProSource 72.7%Not comparable
Inst. Following
BenchmarkGLM-4.6Qwen3.5-35B-A3BResult
AA-IFBenchSource 36.7%72.5%Qwen3.5-35B-A3B leads
IFEvalSource 91.9%Not comparable
Frequently Asked Questions (3)

Can I compare GLM-4.6 and Qwen3.5-35B-A3B 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 GLM-4.6 and Qwen3.5-35B-A3B today?

Qwen3.5-35B-A3B: $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.

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Last updated: July 23, 2026

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