Model Comparison
GLM-4.6 vs GPT-3.5 TurboWhich is better in 2026?
GLM-4.6 significantly outperforms across most benchmarks. GPT-3.5 Turbo is 1.2x cheaper per token.
Verdict: GLM-4.6 vs GPT-3.5 Turbo — which is better?
GLM-4.6 (by Zhipu AI) and GPT-3.5 Turbo (by OpenAI) 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-4.6 outperforms in 1 benchmarks (GPQA), while GPT-3.5 Turbo is better at 0 benchmarks. GLM-4.6 significantly outperforms across most benchmarks.
On price, GPT-3.5 Turbo 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.
Choose GLM-4.6 if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- 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
Choose GPT-3.5 Turbo if…
- cost matters — it's about 1.2x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
GLM-4.6 outperforms in 1 benchmarks (GPQA), while GPT-3.5 Turbo is better at 0 benchmarks.
GLM-4.6 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-4.6 ($0.55/1M tokens) is 1.1x more expensive than GPT-3.5 Turbo ($0.50/1M tokens).
For output processing, GLM-4.6 ($2.00/1M tokens) is 1.3x more expensive than GPT-3.5 Turbo ($1.50/1M tokens).
In conclusion, GLM-4.6 is more expensive than GPT-3.5 Turbo.*
* 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 GPT-3.5 Turbo's 16,385 tokens. GLM-4.6 can generate longer responses up to 131,072 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
Input Capabilities
Supported data types and modalities
GLM-4.6 supports multimodal inputs, whereas GPT-3.5 Turbo does not.
GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-4.6
GPT-3.5 Turbo
License
Usage and distribution terms
GLM-4.6 is licensed under MIT, while GPT-3.5 Turbo uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-4.6 was released on 2025-09-30, while GPT-3.5 Turbo was released on 2023-03-21.
GLM-4.6 is 31 months newer than GPT-3.5 Turbo.
Sep 30, 2025
9 months ago
2.5yr newerMar 21, 2023
3.3 years ago
Knowledge Cutoff
When training data ends
GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while GLM-4.6's cutoff date is not specified.
We can confirm GPT-3.5 Turbo's training data extends to 2021-09-30, but cannot make a direct comparison without GLM-4.6's cutoff date.
—
Sep 2021
Provider Availability
GLM-4.6 is available from Fireworks, DeepInfra. GPT-3.5 Turbo is available from Azure, OpenAI.
GLM-4.6
GPT-3.5 Turbo
Outputs Comparison
Key Takeaways
GLM-4.6
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GLM-4.6 and GPT-3.5 Turbo side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GLM-4.6 vs GPT-3.5 Turbo.