DeepSeek-V4-Pro-0813 vs GLM-5.3
GLM-5.3 shows notably better performance in the majority of benchmarks. DeepSeek-V4-Pro-0813 is 4.0x cheaper per token.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 outperforms in 2 benchmarks (NL2Repo, Toolathlon), while GLM-5.3 is better at 5 benchmarks (Agents' Last Exam, AutomationBench, CyberGym, Humanity's Last Exam, Terminal-Bench 2.1). GLM-5.3 shows notably better performance in the majority of benchmarks.
On price, DeepSeek-V4-Pro-0813 is roughly 4.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-0813 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- cost matters — it's about 4.0x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Choose GLM-5.3
- you want the strongest raw capability — it leads on 5 of 7 shared benchmarks
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-0813 outperforms in 2 benchmarks (NL2Repo, Toolathlon), while GLM-5.3 is better at 5 benchmarks (Agents' Last Exam, AutomationBench, CyberGym, Humanity's Last Exam, Terminal-Bench 2.1).
GLM-5.3 shows notably better performance in the majority of benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 3.2x cheaper than GLM-5.3 ($1.40/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 5.1x cheaper than GLM-5.3 ($4.40/1M tokens).
In conclusion, GLM-5.3 is more expensive than DeepSeek-V4-Pro-0813.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 847.0B more parameters than GLM-5.3, making it 112.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to GLM-5.3's 1,000,000 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while GLM-5.3 is limited to 128,000 tokens.
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while GLM-5.3 was released on 2026-08-14.
GLM-5.3 is 0 month newer than DeepSeek-V4-Pro-0813.
Aug 13, 2026
1 weeks ago
Aug 14, 2026
1 weeks ago
1d 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-0813 is available from DeepSeek, DeepInfra, Novita, Together. GLM-5.3 is available from ZAI.
DeepSeek-V4-Pro-0813
GLM-5.3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and GLM-5.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs GLM-5.3.