DeepSeek-V3 0324 vs GLM-4.6
GLM-4.6 leads the LLM Stats Score 29.1 to 13.5. DeepSeek-V3 0324 is 2.2x cheaper per token.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
GLM-4.6 leads the overall LLM Stats Score 29.1 to 13.5, ranking #129 overall.
In the 1 individual benchmarks reported for both models, GLM-4.6 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 0324 is roughly 2.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-4.6 also accepts a larger context window (202,752 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
- cost matters — it's about 2.2x cheaper per token
Choose GLM-4.6
- overall performance matters — it scores 29.1 and ranks #129 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 202,752 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for DeepSeek-V3 0324 · 7 for GLM-4.6
DeepSeek-V3 0324 outperforms in 0 benchmarks, while GLM-4.6 is better at 1 benchmark (GPQA).
GLM-4.6 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 0324 ($0.24/1M tokens) is 2.1x cheaper than GLM-4.6 ($0.50/1M tokens).
For output processing, DeepSeek-V3 0324 ($0.90/1M tokens) is 2.2x cheaper than GLM-4.6 ($2.00/1M tokens).
In conclusion, GLM-4.6 is more expensive than DeepSeek-V3 0324.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 0324 has 314.0B more parameters than GLM-4.6, making it 88.0% larger.
Context Window
Maximum input and output token capacity
GLM-4.6 accepts 202,752 input tokens compared to DeepSeek-V3 0324's 163,840 tokens. GLM-4.6 can generate longer responses up to 202,752 tokens, while DeepSeek-V3 0324 is limited to 163,840 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.6 supports multimodal inputs, whereas DeepSeek-V3 0324 does not.
GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3 0324
GLM-4.6
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while GLM-4.6 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-4.6 was released on 2025-09-30.
GLM-4.6 is 6 months newer than DeepSeek-V3 0324.
Mar 25, 2025
1.5 years ago
Sep 30, 2025
11 months ago
6mo 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 DeepInfra, Novita. GLM-4.6 is available from DeepInfra, Fireworks.
DeepSeek-V3 0324
GLM-4.6
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and GLM-4.6 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 0324 vs GLM-4.6.