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Model comparison

GLM-4.6 vs Qwen3.5-122B-A10B

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
5.4pts
winning →
60.56/100
0 category wins0 category wins

Public leaderboard positions: GLM-4.6 #85 (Supported); Qwen3.5-122B-A10B #47 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.6 and Qwen3.5-122B-A10B share 11 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to GLM-4.6; 20 to Qwen3.5-122B-A10B.

Updated July 23, 2026
Shared results
11
GLM-4.6 only
3
Qwen3.5-122B-A10B only
20
Comparable categories
0 / 8

Benchmark data for GLM-4.6 and Qwen3.5-122B-A10B 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.

Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B
CategoryGLM-4.6ΔQwen3.5-122B-A10B
AgenticGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B56.4
CodingGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B72.0
ReasoningGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B60.2
KnowledgeGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B83.6
MathGLM-4.63.4MarginNo overlapQwen3.5-122B-A10BNot measured
MultilingualGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B82.2
MultimodalGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B77.2
Inst. FollowingGLM-4.6Not measuredMarginNo overlapQwen3.5-122B-A10B93.4

Operational comparison

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

MetricGLM-4.6Qwen3.5-122B-A10BComparison
Input / output priceUSD per 1M tokensGLM-4.6Not availableQwen3.5-122B-A10B$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondGLM-4.6Not availableQwen3.5-122B-A10BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-4.6Not availableQwen3.5-122B-A10BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-4.6200KQwen3.5-122B-A10B262KQwen3.5-122B-A10B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
τ²-bench resultsSource 76.9%93.6%Qwen3.5-122B-A10B leads
Terminal-Bench 2.0Source 49.4%Not comparable
BrowseCompSource 63.8%Not comparable
OSWorld-VerifiedSource 58%Not comparable
AA Agentic IndexSource 20.7%Not comparable
GDPval-AASource 23.9%Not comparable
GDPval-AASource 978Not comparable
Coding
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
Vibe Code BenchSource 3.09%Not comparable
AA-SciCodeSource 33.1%42.0%Qwen3.5-122B-A10B leads
SWE-bench VerifiedSource 72%Not comparable
AA Coding IndexSource 45.7%Not comparable
Reasoning
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
AA-LCRSource 26.3%66.7%Qwen3.5-122B-A10B leads
CritPtSource 0.0%0.6%Qwen3.5-122B-A10B leads
LongBench v2Source 60.2%Not comparable
Knowledge
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
Artificial Analysis Intelligence IndexSource 23.0%32.3%Qwen3.5-122B-A10B leads
AA-GPQA DiamondSource 63.2%85.7%Qwen3.5-122B-A10B leads
AA-HLESource 5.2%23.4%Qwen3.5-122B-A10B leads
AA-Omniscience IndexSource -31.6%-39.6%GLM-4.6 leads
AA-Omniscience AccuracySource 20.8%24.7%Qwen3.5-122B-A10B leads
AA-Omniscience Hallucination RateSource 66.1%85.5%GLM-4.6 leads
MMLU-ProSource 86.7%Not comparable
SuperGPQASource 67.1%Not comparable
GPQASource 86.6%Not comparable
Math
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
FrontierMath v2 (Tiers 1-3)Source 3.819%Not comparable
FrontierMath v2 (Tier 4)Source 2.128%Not comparable
Multilingual
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
MMLU-ProXSource 82.2%Not comparable
Multimodal
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
MMMUSource 83.9%Not comparable
MMVUSource 74.7%Not comparable
MathVisionSource 86.2%Not comparable
CharXivSource 77.2%Not comparable
V*Source 93.2%Not comparable
AA-MMMU-ProSource 75.0%Not comparable
Inst. Following
BenchmarkGLM-4.6Qwen3.5-122B-A10BResult
AA-IFBenchSource 36.7%75.7%Qwen3.5-122B-A10B leads
IFEvalSource 93.4%Not comparable
Frequently Asked Questions (3)

Can I compare GLM-4.6 and Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B today?

Qwen3.5-122B-A10B: $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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