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Model comparison

DeepSeek V3.2 vs GLM-4.5

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.4/100
Margin
2.2pts
winning →
57.56/100
0 category wins0 category wins

Public leaderboard positions: DeepSeek V3.2 #82 (Supported); GLM-4.5 #68 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.2 and GLM-4.5 share 1 comparable benchmark result. 0 of 8 categories are comparable. 18 results are unique to DeepSeek V3.2; 0 to GLM-4.5.

Updated July 20, 2026
Shared results
1
DeepSeek V3.2 only
18
GLM-4.5 only
0
Comparable categories
0 / 8

Benchmark data for DeepSeek V3.2 and GLM-4.5 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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.

GLM-4.5 is priced at $0.60 input / $2.20 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2.

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 DeepSeek V3.2 and GLM-4.5
CategoryDeepSeek V3.2ΔGLM-4.5
CodingDeepSeek V3.260.9MarginNo overlapGLM-4.5Not measured
MathDeepSeek V3.217.1MarginNo overlapGLM-4.5Not measured

Operational comparison

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

MetricDeepSeek V3.2GLM-4.5Comparison
Input / output priceUSD per 1M tokensDeepSeek V3.2$0.28 input / $0.42 outputGLM-4.5$0.6 input / $2.2 outputDeepSeek V3.2 has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3.235 tok/sGLM-4.551 tok/sGLM-4.5 has the higher measured throughput.
First-answer latencyseconds to first tokenDeepSeek V3.23.75 sGLM-4.51.45 sGLM-4.5 reaches the first token sooner.
Context windowmaximum listed tokensDeepSeek V3.2128KGLM-4.5128KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.2GLM-4.5Result
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
τ²-bench resultsSource 78.9%Not comparable
Gert LabsSource 29.57%Not comparable
Coding
BenchmarkDeepSeek V3.2GLM-4.5Result
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
AA-SciCodeSource 38.7%Not comparable
Reasoning
BenchmarkDeepSeek V3.2GLM-4.5Result
AA-LCRSource 39.0%Not comparable
CritPtSource 0.9%Not comparable
Knowledge
BenchmarkDeepSeek V3.2GLM-4.5Result
Artificial Analysis Intelligence IndexSource 24.7%Not comparable
AA-GPQA DiamondSource 75.1%Not comparable
AA-HLESource 10.5%Not comparable
AA-Omniscience IndexSource -46.7%Not comparable
AA-Omniscience AccuracySource 24.2%Not comparable
AA-Omniscience Hallucination RateSource 93.5%Not comparable
Math
BenchmarkDeepSeek V3.2GLM-4.5Result
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
Multimodal
BenchmarkDeepSeek V3.2GLM-4.5Result
Design Arena WebsiteSource 12061202DeepSeek V3.2 leads
Inst. Following
BenchmarkDeepSeek V3.2GLM-4.5Result
AA-IFBenchSource 49.0%Not comparable
Frequently Asked Questions (3)

Can I compare DeepSeek V3.2 and GLM-4.5 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 DeepSeek V3.2 and GLM-4.5 today?

DeepSeek V3.2: $0.28 input / $0.42 output per 1M tokens GLM-4.5: $0.60 input / $2.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

Related Comparisons

Last updated: July 20, 2026

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