DeepSeek-V4-Flash-Max vs GLM-5.3-Flash
GLM-5.3-Flash significantly outperforms across most benchmarks. DeepSeek-V4-Flash-Max is 1.4x cheaper per token.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-Max outperforms in 0 benchmarks, while GLM-5.3-Flash is better at 2 benchmarks (Humanity's Last Exam, Toolathlon). GLM-5.3-Flash significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Flash-Max is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-Max
- cost matters — it's about 1.4x cheaper per token
Choose GLM-5.3-Flash
- you want the strongest raw capability — it leads on 2 of 2 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-Flash-Max outperforms in 0 benchmarks, while GLM-5.3-Flash is better at 2 benchmarks (Humanity's Last Exam, Toolathlon).
GLM-5.3-Flash significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Max ($0.14/1M tokens) is 1.1x cheaper than GLM-5.3-Flash ($0.15/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.28/1M tokens) is 1.8x cheaper than GLM-5.3-Flash ($0.50/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than DeepSeek-V4-Flash-Max.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 36.0B more parameters than DeepSeek-V4-Flash-Max, making it 12.7% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. DeepSeek-V4-Flash-Max can generate longer responses up to 393,216 tokens, while GLM-5.3-Flash is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
GLM-5.3-Flash supports multimodal inputs, whereas DeepSeek-V4-Flash-Max does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-Max
GLM-5.3-Flash
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-Flash-Max was released on 2026-04-23, while GLM-5.3-Flash was released on 2026-08-26.
GLM-5.3-Flash is 4 months newer than DeepSeek-V4-Flash-Max.
Apr 23, 2026
4 months ago
Aug 26, 2026
1 days ago
4mo 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-Flash-Max is available from DeepSeek. GLM-5.3-Flash is available from DeepInfra, Novita, ZAI.
DeepSeek-V4-Flash-Max
GLM-5.3-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Max and GLM-5.3-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Max vs GLM-5.3-Flash.