Model Comparison
GLM-5 vs DeepSeek-V4-Pro-MaxWhich is better in 2026?
DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks. GLM-5 is 1.4x cheaper per token.
Verdict: GLM-5 vs DeepSeek-V4-Pro-Max — which is better?
GLM-5 (by Zhipu AI) and DeepSeek-V4-Pro-Max (by DeepSeek) 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.
GLM-5 outperforms in 0 benchmarks, while DeepSeek-V4-Pro-Max is better at 4 benchmarks (BrowseComp, MCP Atlas, SWE-Bench Verified, Terminal-Bench 2.0). DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks.
On price, GLM-5 is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-Max also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-5 if…
- cost matters — it's about 1.4x cheaper per token
Choose DeepSeek-V4-Pro-Max if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 outperforms in 0 benchmarks, while DeepSeek-V4-Pro-Max is better at 4 benchmarks (BrowseComp, MCP Atlas, SWE-Bench Verified, Terminal-Bench 2.0).
DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 1.7x cheaper than DeepSeek-V4-Pro-Max ($1.74/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 1.1x cheaper than DeepSeek-V4-Pro-Max ($3.48/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than GLM-5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-Max has 856.0B more parameters than GLM-5, making it 115.1% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-Max accepts 1,048,576 input tokens compared to GLM-5's 200,000 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while DeepSeek-V4-Pro-Max is limited to 65,536 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
GLM-5 was released on 2026-02-11, while DeepSeek-V4-Pro-Max was released on 2026-04-23.
DeepSeek-V4-Pro-Max is 2 months newer than GLM-5.
Feb 11, 2026
3 months ago
Apr 23, 2026
1 months ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5 is available from FriendliAI, ZAI. DeepSeek-V4-Pro-Max is available from DeepInfra, DeepSeek.
GLM-5
DeepSeek-V4-Pro-Max
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
DeepSeek-V4-Pro-Max
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about GLM-5 vs DeepSeek-V4-Pro-Max.