Model Comparison
Gemini 3.1 Pro vs GLM-5.2Which is better in 2026?
GLM-5.2 shows notably better performance in the majority of benchmarks. GLM-5.2 is 2.6x cheaper per token.
Verdict: Gemini 3.1 Pro vs GLM-5.2 — which is better?
Gemini 3.1 Pro (by Google) and GLM-5.2 (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Gemini 3.1 Pro outperforms in 1 benchmarks (GPQA), while GLM-5.2 is better at 3 benchmarks (Humanity's Last Exam, MCP Atlas, SWE-Bench Pro). GLM-5.2 shows notably better performance in the majority of benchmarks.
On price, GLM-5.2 is roughly 2.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.1 Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 3.1 Pro if…
- you process long inputs — it offers a 1,048,576 token context window
Choose GLM-5.2 if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
- cost matters — it's about 2.6x cheaper per token
- you want the most recent training data — it shipped Jun 2026
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.1 Pro outperforms in 1 benchmarks (GPQA), while GLM-5.2 is better at 3 benchmarks (Humanity's Last Exam, MCP Atlas, SWE-Bench Pro).
GLM-5.2 shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.1 Pro ($2.50/1M tokens) is 1.8x more expensive than GLM-5.2 ($1.40/1M tokens).
For output processing, Gemini 3.1 Pro ($15.00/1M tokens) is 3.4x more expensive than GLM-5.2 ($4.40/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than GLM-5.2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.1 Pro accepts 1,048,576 input tokens compared to GLM-5.2's 1,000,000 tokens. GLM-5.2 can generate longer responses up to 131,072 tokens, while Gemini 3.1 Pro is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 3.1 Pro supports multimodal inputs, whereas GLM-5.2 does not.
Gemini 3.1 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 3.1 Pro
GLM-5.2
License
Usage and distribution terms
Gemini 3.1 Pro is licensed under a proprietary license, while GLM-5.2 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Gemini 3.1 Pro was released on 2026-02-19, while GLM-5.2 was released on 2026-06-16.
GLM-5.2 is 4 months newer than Gemini 3.1 Pro.
Feb 19, 2026
3 months ago
Jun 16, 2026
0 days ago
3mo newerKnowledge Cutoff
When training data ends
Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while GLM-5.2's cutoff date is not specified.
We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without GLM-5.2's cutoff date.
Jan 2025
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Provider Availability
Gemini 3.1 Pro is available from Google. GLM-5.2 is available from FriendliAI, Novita, ZAI.
Gemini 3.1 Pro
GLM-5.2
Outputs Comparison
Key Takeaways
GLM-5.2
View detailsZhipu AI
Detailed Comparison
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FAQ
Common questions about Gemini 3.1 Pro vs GLM-5.2.