Model Comparison
Gemini 2.0 Flash vs GLM-4.5Which is better in 2026?
GLM-4.5 significantly outperforms across most benchmarks. Gemini 2.0 Flash is 4.0x cheaper per token.
Verdict: Gemini 2.0 Flash vs GLM-4.5 — which is better?
Gemini 2.0 Flash (by Google) and GLM-4.5 (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 2.0 Flash outperforms in 0 benchmarks, while GLM-4.5 is better at 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro). GLM-4.5 significantly outperforms across most benchmarks.
On price, Gemini 2.0 Flash is roughly 4.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 2.0 Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 2.0 Flash if…
- cost matters — it's about 4.0x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
Choose GLM-4.5 if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- you want the most recent training data — it shipped Jul 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 2.0 Flash outperforms in 0 benchmarks, while GLM-4.5 is better at 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro).
GLM-4.5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 2.0 Flash ($0.10/1M tokens) is 4.0x cheaper than GLM-4.5 ($0.40/1M tokens).
For output processing, Gemini 2.0 Flash ($0.40/1M tokens) is 4.0x cheaper than GLM-4.5 ($1.60/1M tokens).
In conclusion, GLM-4.5 is more expensive than Gemini 2.0 Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 2.0 Flash accepts 1,048,576 input tokens compared to GLM-4.5's 131,072 tokens. GLM-4.5 can generate longer responses up to 131,072 tokens, while Gemini 2.0 Flash is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Gemini 2.0 Flash supports multimodal inputs, whereas GLM-4.5 does not.
Gemini 2.0 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 2.0 Flash
GLM-4.5
License
Usage and distribution terms
Gemini 2.0 Flash is licensed under a proprietary license, while GLM-4.5 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 2.0 Flash was released on 2024-12-01, while GLM-4.5 was released on 2025-07-28.
GLM-4.5 is 8 months newer than Gemini 2.0 Flash.
Dec 1, 2024
1.6 years ago
Jul 28, 2025
11 months ago
7mo newerKnowledge Cutoff
When training data ends
Gemini 2.0 Flash has a documented knowledge cutoff of 2024-08-01, while GLM-4.5's cutoff date is not specified.
We can confirm Gemini 2.0 Flash's training data extends to 2024-08-01, but cannot make a direct comparison without GLM-4.5's cutoff date.
Aug 2024
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Provider Availability
Gemini 2.0 Flash is available from Google. GLM-4.5 is available from DeepInfra, Fireworks, Novita.
Gemini 2.0 Flash
GLM-4.5
Outputs Comparison
Key Takeaways
GLM-4.5
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Gemini 2.0 Flash and GLM-4.5 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Gemini 2.0 Flash vs GLM-4.5.