Model Comparison
GLM-5 vs Gemini 2.5 Flash-LiteWhich is better in 2026?
GLM-5 significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is 8.9x cheaper per token.
Verdict: GLM-5 vs Gemini 2.5 Flash-Lite — which is better?
GLM-5 (by Zhipu AI) and Gemini 2.5 Flash-Lite (by Google) 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.
GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while Gemini 2.5 Flash-Lite is better at 0 benchmarks. GLM-5 significantly outperforms across most benchmarks.
On price, Gemini 2.5 Flash-Lite is roughly 8.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 2.5 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-5 if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you want the most recent training data — it shipped Feb 2026
Choose Gemini 2.5 Flash-Lite if…
- cost matters — it's about 8.9x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while Gemini 2.5 Flash-Lite is better at 0 benchmarks.
GLM-5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 10.0x more expensive than Gemini 2.5 Flash-Lite ($0.10/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 8.0x more expensive than Gemini 2.5 Flash-Lite ($0.40/1M tokens).
In conclusion, GLM-5 is more expensive than Gemini 2.5 Flash-Lite.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 2.5 Flash-Lite accepts 1,048,576 input tokens compared to GLM-5's 200,000 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 2.5 Flash-Lite supports multimodal inputs, whereas GLM-5 does not.
Gemini 2.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5
Gemini 2.5 Flash-Lite
License
Usage and distribution terms
GLM-5 is licensed under MIT, while Gemini 2.5 Flash-Lite uses Creative Commons Attribution 4.0 License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Creative Commons Attribution 4.0 License
Open weights
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while Gemini 2.5 Flash-Lite was released on 2025-06-17.
GLM-5 is 8 months newer than Gemini 2.5 Flash-Lite.
Feb 11, 2026
4 months ago
7mo newerJun 17, 2025
12 months ago
Knowledge Cutoff
When training data ends
Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while GLM-5's cutoff date is not specified.
We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, but cannot make a direct comparison without GLM-5's cutoff date.
—
Jan 2025
Provider Availability
GLM-5 is available from FriendliAI, ZAI. Gemini 2.5 Flash-Lite is available from Google.
GLM-5
Gemini 2.5 Flash-Lite
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
Detailed Comparison
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FAQ
Common questions about GLM-5 vs Gemini 2.5 Flash-Lite.