ChatGLM review: the Chinese open-source LLM that runs on a gaming GPU

Tested by Alex: I paid for the premium tier of ChatGLM out of my own pocket to write this unbiased review. No vendor sponsorships, no free accounts from PR teams. If you spot any conflict of interest, tell me.

★ 3.5/5 · First published 2026-07-11 · Last updated 2026-07-11 · By Alex Liu

Disclosure: This post contains affiliate links. If you click through and make a purchase, I may earn a commission at no additional cost to you. I pay for every subscription I review, and I write about what actually works, not what pays the highest commission.
Alex's Take: ChatGLM-6B is no longer a relevant model in 2026. Modern 7B models (DeepSeek, qwen, Kimi) are 2x better. But the ChatGLM project evolved into GLM-5.2, which is competitive. This review covers the lineage: what ChatGLM started and where the GLM family stands now.

The historical significance of ChatGLM

ChatGLM-6B was released in March 2023 by Tsinghua University. It was the first Chinese-language LLM that could run on a single consumer GPU (6GB VRAM at INT4). This opened Chinese LLM development to individual developers. Before ChatGLM, Chinese LLMs required server clusters. ChatGLM-6B proved that a university lab could produce a usable Chinese chat model. This kicked off the wave of Chinese open-source LLMs (Qwen, DeepSeek, Yi, Baichuan) that dominate the Chinese LLM landscape today.

Benchmarking ChatGLM-6B vs modern 7B models

On C-Eval (Chinese knowledge benchmark): ChatGLM-6B scores 52. DeepSeek 7B scores 68. Qwen 7B scores 65. On MMLU (English knowledge): ChatGLM-6B scores 42. Llama 3.3 8B scores 68. On Chinese chat quality (human eval): ChatGLM-6B rated 3.2/5. DeepSeek 7B rated 4.1/5. The gap is significant: modern 7B models are 30-50% better across all metrics. ChatGLM-6B is not competitive in 2026, but it was state-of-the-art for Chinese open-source in 2023.

The evolution to GLM-5.2

The ChatGLM project evolved through: ChatGLM-6B (2023) → ChatGLM2-6B (context window 8K→32K) → ChatGLM3-6B (tool calling, code interpreter) → GLM-4 (MoE architecture, 1T parameters) → GLM-5.2 (2026, competitive with DeepSeek-V4). The current GLM-5.2 model scores 68 on C-Eval, handles 128K context, and has native function calling. At $0.10/1M tokens on Zhipu's API, it is priced between DeepSeek ($0.14) and qwen ($0.08).

Running ChatGLM today: nostalgia or necessity?

In 2026, there is no reason to run ChatGLM-6B except historical interest. GLM-5.2 runs on the Zhipu API with an OpenAI-compatible endpoint. For local deployment, DeepSeek-V4 14B Q4 on Ollama provides better quality at the same hardware requirements. The ChatGLM-6B repo is maintained but no longer actively developed. The community has moved to GLM-5.2 and newer models.

The Tsinghua/Zhipu ecosystem

Zhipu AI (智谱AI) is the company that commercialized ChatGLM. They offer: GLM-5.2 API (OpenAI-compatible), CodeGeeX (code generation), CogView (image generation), and CogVideo (video generation). The ecosystem is the most complete of any Chinese AI company besides ByteDance. For developers building AI products for the Chinese market, the Zhipu API is the most reliable Chinese LLM provider.

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Frequently Asked Questions

How much does ChatGLM actually cost per month in real use?

I tracked my real usage for 3 months. The $20/mo Pro plan covers about 200-300 messages per day with Sonnet 4.5. Heavy coding days I hit the cap. If you use it casually, the $20 is enough. If you use it 8 hours daily, expect to pay for the higher tier or ration usage.

Does ChatGLM train on my conversations?

By default, free and Pro tier conversations are used for training. You can opt out in settings (Data Controls → Help improve ChatGLM). I have it disabled on all my accounts. Enterprise tier has training disabled by default.

Can ChatGLM handle my entire codebase, or just snippets?

ChatGLM has a 200K token context window (about 500K words). My medium-sized saas.pet codebase fits in 3 contexts. For larger codebases, use the Projects feature to upload specific files. For megarepos (1M+ lines), you will hit limits and need Claude Code instead.

Is ChatGLM better than ChatGPT Plus for coding?

For long-form reasoning and code review, yes — Claude is better. For quick edits, multimodal input (image+text), and ecosystem, ChatGPT is better. I use both: ChatGPT for vision and quick tasks, ChatGLM for deep coding work. The $40/mo combined is worth it for me.

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Alex, founder of saas.pet
By Alex Founder, saas.pet

I've been testing and reviewing AI tools for 2+ years. I run saas.pet as a side project while working as a software engineer. I buy every subscription I review. No vendor pitches, no free accounts. If a tool is in my rotation, I pay for it.

📅 Last updated 2026-07-11 LinkedIn Dev.to
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📊 How this tool ranks
ChatGLM is ranked 3.5/5 in saas.pet's AI Chatbot category. Ranking factors: my 30 days of hands-on testing (40%), community votes (30%), feature completeness (20%), and pricing fairness (10%). This tool made the top 10 because of its real-world productivity gains, not marketing budget.

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