Model Comparison
DeepSeek-V4-Pro-Max vs GLM-5.2Which is better in 2026?
GLM-5.2 shows notably better performance in the majority of benchmarks. GLM-5.2 is 1.4x cheaper per token.
Verdict: DeepSeek-V4-Pro-Max vs GLM-5.2 — which is better?
DeepSeek-V4-Pro-Max (by DeepSeek) and GLM-5.2 (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V4-Pro-Max outperforms in 2 benchmarks (HMMT Feb 26, Toolathlon), while GLM-5.2 is better at 6 benchmarks (FrontierSWE, GPQA, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, SWE-Bench Pro). GLM-5.2 shows notably better performance in the majority of benchmarks.
On price, GLM-5.2 is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-V4-Pro-Max if…
- you want predictable pricing at $1.60/M input and $3.20/M output
Choose GLM-5.2 if…
- you want the strongest raw capability — it leads on 6 of 8 shared benchmarks
- cost matters — it's about 1.4x cheaper per token
- you want the most recent training data — it shipped Jun 2026
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-Max outperforms in 2 benchmarks (HMMT Feb 26, Toolathlon), while GLM-5.2 is better at 6 benchmarks (FrontierSWE, GPQA, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, SWE-Bench Pro).
GLM-5.2 shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-Max ($1.60/1M tokens) is 1.7x more expensive than GLM-5.2 ($0.95/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($3.20/1M tokens) is 1.1x more expensive than GLM-5.2 ($3.00/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than GLM-5.2.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-Max has 847.0B more parameters than GLM-5.2, making it 112.5% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-Max was released on 2026-04-23, while GLM-5.2 was released on 2026-06-16.
GLM-5.2 is 2 months newer than DeepSeek-V4-Pro-Max.
Apr 23, 2026
2 months ago
Jun 16, 2026
1 months ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-Max is available from Novita, DeepInfra, DeepSeek, Fireworks, Together. GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI.
DeepSeek-V4-Pro-Max
GLM-5.2
Outputs Comparison
Key Takeaways
DeepSeek-V4-Pro-Max
View detailsDeepSeek
GLM-5.2
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and GLM-5.2 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Pro-Max vs GLM-5.2.