Gemini 4 Argon vs GLM-5.3
Gemini 4 Argon and GLM-5.3 are closely matched at 55.1 and 50.9 on the LLM Stats Score. GLM-5.3 is 2.1x cheaper per token.
Google · Zhipu AI · Updated for 2026
Which is better?
Gemini 4 Argon and GLM-5.3 are closely matched on the overall LLM Stats Score at 55.1 and 50.9.
In the 5 individual benchmarks reported for both models, Gemini 4 Argon wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3 is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 4 Argon
- you value its reported benchmark strengths — it wins 5 of 5 exact shared results
- you want the most recent training data — it shipped Sep 2026
Choose GLM-5.3
- cost matters — it's about 2.1x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for Gemini 4 Argon · 17 for GLM-5.3
Gemini 4 Argon outperforms in 5 benchmarks (Agents' Last Exam, AutomationBench, DeepSWE 1.1, PostTrainBench, Terminal-Bench 4.0), while GLM-5.3 is better at 0 benchmarks.
Gemini 4 Argon 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, Gemini 4 Argon ($2.00/1M tokens) is 1.7x more expensive than GLM-5.3 ($1.20/1M tokens).
For output processing, Gemini 4 Argon ($10.00/1M tokens) is 2.5x more expensive than GLM-5.3 ($4.00/1M tokens).
In conclusion, Gemini 4 Argon is more expensive than GLM-5.3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Both models can generate responses up to 1,048,576 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 4 Argon supports multimodal inputs, whereas GLM-5.3 does not.
Gemini 4 Argon can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 4 Argon
GLM-5.3
License
Usage and distribution terms
Gemini 4 Argon is licensed under a proprietary license, while GLM-5.3 uses GLM-5.3 License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
GLM-5.3 License
Open weights
Release Timeline
When each model was launched
Gemini 4 Argon was released on 2026-09-30, while GLM-5.3 was released on 2026-08-14.
Gemini 4 Argon is 2 months newer than GLM-5.3.
Sep 30, 2026
3 weeks ago
1mo newerAug 14, 2026
2 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Gemini 4 Argon is available from Google. GLM-5.3 is available from DeepInfra, FriendliAI, Novita, ZAI.
Gemini 4 Argon
GLM-5.3
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 4 Argon and GLM-5.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 4 Argon vs GLM-5.3.