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DeepSeek V3.2 Exp vs GLM 5.2

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V3.2 Exp and GLM 5.2.

DeepSeek

DeepSeek V3.2 Exp

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

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Zhipu AI

GLM 5.2

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

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Technical Specifications

SpecificationDeepSeek V3.2 ExpGLM 5.2
ProviderDeepSeekZhipu AI
Context Window163,840 tokens1,048,576 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostablemanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2025-09-292026-06-16

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V3.2 Exp

$0.27

GLM 5.2

$0.93

Output Price per Million Tokens

DeepSeek V3.2 Exp

$0.41

GLM 5.2

$3.00

Want to test both models live?

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Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs8950.0%
DeepSeek V3.2 Exp
GLM 5.2
HumanEvalPython coding & logic synthesis
N/Avs9120.0%
DeepSeek V3.2 Exp
GLM 5.2
MATHComplex mathematical problem solving
N/Avs8050.0%
DeepSeek V3.2 Exp
GLM 5.2
GPQAGraduate-level expert reasoning
N/Avs5350.0%
DeepSeek V3.2 Exp
GLM 5.2
HellaSwagCommonsense reasoning and inference
N/Avs8980.0%
DeepSeek V3.2 Exp
GLM 5.2
MT-BenchMulti-turn conversation flow quality
N/Avs930.0%
DeepSeek V3.2 Exp
GLM 5.2

DeepSeek V3.2 Exp Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.