Model comparison

DeepSeek V3.2 vs GLM-4.6

Data verified July 23, 2026

Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek V3.2

DeepSeek

55.4/100

Margin

0.3pts

← winning

GLM-4.6

Z.AI

55.12/100

1 category wins0 category wins

Public leaderboard positions: DeepSeek V3.2 #82 (Supported); GLM-4.6 #85 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.2 and GLM-4.6 share 13 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to DeepSeek V3.2; 1 to GLM-4.6.

Updated July 23, 2026

Shared results: 13
DeepSeek V3.2 only: 6
GLM-4.6 only: 1
Comparable categories: 1 / 8

Pick DeepSeek V3.2 if you want the stronger benchmark profile. GLM-4.6 only becomes the better choice if you need the larger 200K context window or you want the stronger reasoning-first profile.

Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 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

DeepSeek V3.2 has the cleaner BenchAlign overall profile here, landing at 55.4 versus 55.12. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

DeepSeek V3.2's sharpest advantage is in mathematics, where it averages 17.1 against 3.4. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 22.100% to 3.819%.

GLM-4.6 is the reasoning model in the pair, while DeepSeek V3.2 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. GLM-4.6 gives you the larger context window at 200K, compared with 128K 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-4.6
Category	DeepSeek V3.2	Δ	GLM-4.6
Math	DeepSeek V3.217.1	Margin← 13.7	GLM-4.63.4
Coding	DeepSeek V3.260.9	MarginNo overlap	GLM-4.6Not measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

A · DeepSeek V3.2B · GLM-4.6

FrontierMath v2 (Tiers 1-3)
Math
Source ↗
A 22.100%B 3.819%
Winner: DeepSeek V3.2Δ 18.3
FrontierMath v2 (Tiers 1-3): DeepSeek V3.2 scored 22.100%; GLM-4.6 scored 3.819%. DeepSeek V3.2 wins this benchmark.
FrontierMath v2 (Tier 4)
Math
Source ↗
A 2.100%B 2.128%
Winner: GLM-4.6Δ 0
FrontierMath v2 (Tier 4): DeepSeek V3.2 scored 2.100%; GLM-4.6 scored 2.128%. GLM-4.6 wins this benchmark.

Operational comparison

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

Metric	DeepSeek V3.2	GLM-4.6	Comparison
Input / output priceUSD per 1M tokens	DeepSeek V3.2$0.28 input / $0.42 output	GLM-4.6Not available	A complete price comparison is not available.
Generation speedtokens per second	DeepSeek V3.235 tok/s	GLM-4.6Not available	A complete speed comparison is not available.
First-answer latencyseconds to first token	DeepSeek V3.23.75 s	GLM-4.6Not available	A complete latency comparison is not available.
Context windowmaximum listed tokens	DeepSeek V3.2128K	GLM-4.6200K	GLM-4.6 lists the larger context window.

Benchmark Deep Dive

Agentic

4 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
Claw-EvalSource	40.2%	—	Not comparable
VITA-BenchSource	18.5%	—	Not comparable
τ²-bench resultsSource	78.9%	76.9%	DeepSeek V3.2 leads
Gert LabsSource	29.57%	—	Not comparable

Coding

4 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
SWE-RebenchSource	60.9%	—	Not comparable
React Native EvalsSource	71.5%	—	Not comparable
AA-SciCodeSource	38.7%	33.1%	DeepSeek V3.2 leads
Vibe Code BenchSource	—	3.09%	Not comparable

Reasoning

2 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
AA-LCRSource	39.0%	26.3%	DeepSeek V3.2 leads
CritPtSource	0.9%	0.0%	DeepSeek V3.2 leads

Knowledge

6 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
Artificial Analysis Intelligence IndexSource	24.7%	23.0%	DeepSeek V3.2 leads
AA-GPQA DiamondSource	75.1%	63.2%	DeepSeek V3.2 leads
AA-HLESource	10.5%	5.2%	DeepSeek V3.2 leads
AA-Omniscience IndexSource	-46.7%	-31.6%	GLM-4.6 leads
AA-Omniscience AccuracySource	24.2%	20.8%	DeepSeek V3.2 leads
AA-Omniscience Hallucination RateSource	93.5%	66.1%	GLM-4.6 leads

MathDeepSeek V3.2 wins

2 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
FrontierMath v2 (Tiers 1-3)Source	22.100%	3.819%	DeepSeek V3.2 leads
FrontierMath v2 (Tier 4)Source	2.100%	2.128%	GLM-4.6 leads

Multimodal

1 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
Design Arena WebsiteSource	1204	—	Not comparable

Inst. Following

1 benchmarks

Benchmark	DeepSeek V3.2	GLM-4.6	Result
AA-IFBenchSource	49.0%	36.7%	DeepSeek V3.2 leads

Frequently Asked Questions (2)

Which is better, DeepSeek V3.2 or GLM-4.6?

DeepSeek V3.2 is ahead on BenchLM's BenchAlign leaderboard, 55.4 to 55.12. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 22.100% and 3.819%.

Which is better for math, DeepSeek V3.2 or GLM-4.6?

DeepSeek V3.2 has the edge for math in this comparison, averaging 17.1 versus 3.4. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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