DeepSeek-V3 0324 vs GLM-5.3-Flash
GLM-5.3-Flash leads the LLM Stats Score 51.6 to 13.7. GLM-5.3-Flash is 2.1x cheaper per token.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 13.7, ranking #11 overall.
On price, GLM-5.3-Flash is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V3 0324
- you want predictable pricing at $0.28/M input and $1.14/M output
Choose GLM-5.3-Flash
- overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 2.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Individual benchmarks
5 reported for DeepSeek-V3 0324 · 15 for GLM-5.3-Flash
DeepSeek-V3 0324 and GLM-5.3-Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 0324 ($0.28/1M tokens) is 1.9x more expensive than GLM-5.3-Flash ($0.15/1M tokens).
For output processing, DeepSeek-V3 0324 ($1.14/1M tokens) is 2.3x more expensive than GLM-5.3-Flash ($0.50/1M tokens).
In conclusion, DeepSeek-V3 0324 is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 0324 has 351.0B more parameters than GLM-5.3-Flash, making it 109.7% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to DeepSeek-V3 0324's 163,840 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while GLM-5.3-Flash is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
GLM-5.3-Flash supports multimodal inputs, whereas DeepSeek-V3 0324 does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3 0324
GLM-5.3-Flash
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while GLM-5.3-Flash uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while GLM-5.3-Flash was released on 2026-08-26.
GLM-5.3-Flash is 17 months newer than DeepSeek-V3 0324.
Mar 25, 2025
1.4 years ago
Aug 26, 2026
2 days ago
1.4yr 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-V3 0324 is available from Novita. GLM-5.3-Flash is available from DeepInfra, Novita, ZAI.
DeepSeek-V3 0324
GLM-5.3-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and GLM-5.3-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 0324 vs GLM-5.3-Flash.