GLM-5.2 vs GLM-5V-Turbo
GLM-5.2 leads the LLM Stats Score 45.6 to 30.4. GLM-5.2 is 1.6x cheaper per token.
Zhipu AI · Zhipu AI · Updated for 2026
Which is better?
GLM-5.2 leads the overall LLM Stats Score 45.6 to 30.4, ranking #27 overall.
On price, GLM-5.2 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.2 also accepts a larger context window (1,048,576 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 GLM-5.2
- overall performance matters — it scores 45.6 and ranks #27 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- cost matters — it's about 1.6x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jun 2026
- you need open weights you can self-host or fine-tune
Choose GLM-5V-Turbo
- you want predictable pricing at $1.20/M input and $4.00/M output
At a glance
The differences that matter most.
Individual benchmarks
19 reported for GLM-5.2 · 19 for GLM-5V-Turbo
GLM-5.2 and GLM-5V-Turbodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.75/1M tokens) is 1.6x cheaper than GLM-5V-Turbo ($1.20/1M tokens).
For output processing, GLM-5.2 ($2.40/1M tokens) is 1.7x cheaper than GLM-5V-Turbo ($4.00/1M tokens).
In conclusion, GLM-5V-Turbo 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
GLM-5.2 accepts 1,048,576 input tokens compared to GLM-5V-Turbo's 200,000 tokens. GLM-5.2 can generate longer responses up to 1,048,576 tokens, while GLM-5V-Turbo is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GLM-5V-Turbo supports multimodal inputs, whereas GLM-5.2 does not.
GLM-5V-Turbo can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.2
GLM-5V-Turbo
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while GLM-5V-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-5.2 was released on 2026-06-16, while GLM-5V-Turbo was released on 2026-04-02.
GLM-5.2 is 3 months newer than GLM-5V-Turbo.
Jun 16, 2026
2 months ago
2mo newerApr 2, 2026
5 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. GLM-5V-Turbo is available from ZAI.
GLM-5.2
GLM-5V-Turbo
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and GLM-5V-Turbo side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs GLM-5V-Turbo.