Gemini 1.0 Pro vs GLM-4.6
GLM-4.6 leads the LLM Stats Score 29.4 to -5.3. Gemini 1.0 Pro is 1.2x cheaper per token.
Google · Zhipu AI · Updated for 2026
Which is better?
GLM-4.6 leads the overall LLM Stats Score 29.4 to -5.3, ranking #121 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, Gemini 1.0 Pro is roughly 1.2x 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 (131,072 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 Gemini 1.0 Pro
- cost matters — it's about 1.2x cheaper per token
Choose GLM-4.6
- overall performance matters — it scores 29.4 and ranks #121 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 131,072 token context window
- you want the most recent training data — it shipped Sep 2025
- 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
9 reported for Gemini 1.0 Pro · 7 for GLM-4.6
Gemini 1.0 Pro 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, Gemini 1.0 Pro ($0.50/1M tokens) is 1.1x cheaper than GLM-4.6 ($0.55/1M tokens).
For output processing, Gemini 1.0 Pro ($1.50/1M tokens) is 1.3x cheaper than GLM-4.6 ($2.00/1M tokens).
In conclusion, GLM-4.6 is more expensive than Gemini 1.0 Pro.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-4.6 accepts 131,072 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. GLM-4.6 can generate longer responses up to 131,072 tokens, while Gemini 1.0 Pro is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.6 supports multimodal inputs, whereas Gemini 1.0 Pro does not.
GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.0 Pro
GLM-4.6
License
Usage and distribution terms
Gemini 1.0 Pro is licensed under a proprietary license, while GLM-4.6 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 1.0 Pro was released on 2024-02-15, while GLM-4.6 was released on 2025-09-30.
GLM-4.6 is 20 months newer than Gemini 1.0 Pro.
Feb 15, 2024
2.6 years ago
Sep 30, 2025
11 months ago
1.6yr newerKnowledge Cutoff
When training data ends
Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while GLM-4.6's cutoff date is not specified.
We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without GLM-4.6's cutoff date.
Feb 2024
—
Provider Availability
Gemini 1.0 Pro is available from Google. GLM-4.6 is available from Fireworks, DeepInfra.
Gemini 1.0 Pro
GLM-4.6
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.0 Pro and GLM-4.6 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.0 Pro vs GLM-4.6.