GLM-5.1 Review 2026

Name: GLM-5.1
Brand: GLM-5.1
Availability: InStock

Honest pros, cons, and verdict on this automation & workflows tool

✅ Best-in-class open-source performance on reasoning, coding, and agentic tasks per Z.ai benchmarks (e.g., 77.8 on SWE-bench Verified, 96.9 on HMMT Nov. 2025)

Starting Price

Free

Free Tier

Yes

What is GLM-5.1?

GLM-5.1 is a large language model hosted on Hugging Face by zai-org, intended for chat and tool-calling workflows.

GLM-5.1 is a free open-source large language model from Z.ai (zai-org) hosted on Hugging Face, designed for complex systems engineering, long-horizon agentic tasks, reasoning, and tool-calling workflows. The model is distributed at no cost under an open-weights license, making it suitable for researchers, AI engineers, and enterprises seeking frontier-grade open models.

The GLM-5 architecture scales to 744B total parameters with 40B active parameters per forward pass (a Mixture-of-Experts design), up from GLM-4.5's 355B/32B configuration. Pre-training data was expanded from 23T to 28.5T tokens, and the model integrates DeepSeek Sparse Attention (DSA) to substantially reduce deployment cost while preserving long-context capacity. Z.ai's team also developed 'slime,' a novel asynchronous reinforcement learning infrastructure that improves RL training throughput, enabling fine-grained post-training iterations. On benchmarks, GLM-5 scores 30.5 on Humanity's Last Exam (50.4 with tools), 92.7 on AIME 2026 I, 96.9 on HMMT Nov. 2025, 86.0 on GPQA-Diamond, 77.8 on SWE-bench Verified, and 73.3 on SWE-bench Multilingual — closing the gap with frontier closed models like Claude Opus 4.5, Gemini 3 Pro, and GPT-5.2.

Key Features

✓744B total parameters with 40B active (MoE architecture)

✓28.5T tokens pre-training data

✓DeepSeek Sparse Attention (DSA) for efficient long-context

✓Tool-calling with structured XML format

✓OpenAI-compatible API when self-hosted

✓vLLM, SGLang, Transformers, Ollama, llama.cpp support

Pricing Breakdown

Open Weights (Self-hosted)

Free

✓Full model weights downloadable from Hugging Face
✓Use with vLLM, SGLang, Transformers, Ollama, llama.cpp
✓OpenAI-compatible API when self-served
✓Tool-calling and reasoning support
✓Subject to model license terms

Z.ai API Platform

Usage-based (see Z.ai)

per month

✓Managed GLM-5 endpoints
✓No infrastructure to run
✓Pay-per-token billing
✓Standard chat and tool-calling APIs
✓Hosted by Z.ai

Pros & Cons

✅Pros

•Best-in-class open-source performance on reasoning, coding, and agentic tasks per Z.ai benchmarks (e.g., 77.8 on SWE-bench Verified, 96.9 on HMMT Nov. 2025)
•Free open-weights download — no per-token API costs once self-hosted
•Massive 744B-parameter MoE with only 40B active per token, balancing capacity and inference cost
•DeepSeek Sparse Attention reduces long-context deployment cost meaningfully versus dense attention
•Wide deployment support: vLLM, SGLang, Transformers, Ollama, LM Studio, llama.cpp, Docker — covering most serving stacks
•Native tool-calling and chat templates ship with the model, simplifying agent integration
•Backed by Z.ai's 'slime' asynchronous RL infrastructure, with active iteration from GLM-4.5 to 4.7 to 5

❌Cons

•Running the full 744B-parameter model requires substantial GPU memory and multi-GPU infrastructure — out of reach for hobbyists
•Still trails frontier closed models like Gemini 3 Pro (91.9 GPQA) and GPT-5.2 on several benchmarks (HLE, GPQA-Diamond)
•Documentation on the Hugging Face card is sparse compared to commercial LLM platforms — most setup details live in external blogs and the GitHub repo
•No standalone polished web UI; users must self-host or use the separate Z.ai API platform
•Tool-calling uses a custom XML format that may require adapter code versus standard OpenAI function-calling JSON
•License terms and commercial-use specifics must be verified directly on the model card before production deployment

Who Should Use GLM-5.1?

✓Self-hosted enterprise coding assistants where data cannot leave the network — GLM-5.1's 77.8 SWE-bench Verified score makes it a credible Copilot alternative on internal infrastructure
✓Long-horizon autonomous agents that perform multi-step tool calls (browsing, code execution, file operations) and benefit from the model's native tool-calling chat template
✓Research labs benchmarking open-source frontier models on reasoning, math (AIME, HMMT), and graduate-level science (GPQA-Diamond) without paying per-token API fees
✓Multilingual software engineering teams leveraging the 73.3 SWE-bench Multilingual score for non-English codebases where many closed models underperform
✓High-volume batch inference workloads (document analysis, code review, synthetic data generation) where the free open weights eliminate API spend at scale
✓Fine-tuning and post-training experimentation, taking advantage of the open weights and Z.ai's slime asynchronous RL infrastructure for custom domain adaptation

Who Should Skip GLM-5.1?

×You're concerned about running the full 744b-parameter model requires substantial gpu memory and multi-gpu infrastructure — out of reach for hobbyists
×You're concerned about still trails frontier closed models like gemini 3 pro (91.9 gpqa) and gpt-5.2 on several benchmarks (hle, gpqa-diamond)
×You're concerned about documentation on the hugging face card is sparse compared to commercial llm platforms — most setup details live in external blogs and the github repo

Alternatives to Consider

Qwen 3

Large language model and AI assistant developed by Alibaba, offering chat-based AI capabilities.

Starting at See pricing

Learn more →

Our Verdict

✅

GLM-5.1 is a solid choice

GLM-5.1 delivers on its promises as a automation & workflows tool. While it has some limitations, the benefits outweigh the drawbacks for most users in its target market.

Try GLM-5.1 →Compare Alternatives →

Frequently Asked Questions

What is GLM-5.1?

GLM-5.1 is a large language model hosted on Hugging Face by zai-org, intended for chat and tool-calling workflows.

Is GLM-5.1 good?

Yes, GLM-5.1 is good for automation & workflows work. Users particularly appreciate best-in-class open-source performance on reasoning, coding, and agentic tasks per z.ai benchmarks (e.g., 77.8 on swe-bench verified, 96.9 on hmmt nov. 2025). However, keep in mind running the full 744b-parameter model requires substantial gpu memory and multi-gpu infrastructure — out of reach for hobbyists.

Is GLM-5.1 free?

Yes, GLM-5.1 offers a free tier. However, premium features unlock additional functionality for professional users.

Who should use GLM-5.1?

GLM-5.1 is best for Self-hosted enterprise coding assistants where data cannot leave the network — GLM-5.1's 77.8 SWE-bench Verified score makes it a credible Copilot alternative on internal infrastructure and Long-horizon autonomous agents that perform multi-step tool calls (browsing, code execution, file operations) and benefit from the model's native tool-calling chat template. It's particularly useful for automation & workflows professionals who need 744b total parameters with 40b active (moe architecture).

What are the best GLM-5.1 alternatives?

Popular GLM-5.1 alternatives include Qwen 3. Each has different strengths, so compare features and pricing to find the best fit.

More about GLM-5.1

Pricing Alternatives Free vs Paid Pros & Cons Worth It?Tutorial

📖 GLM-5.1 Overview 💰 GLM-5.1 Pricing 🆚 Free vs Paid 🤔 Is it Worth It?

Last verified March 2026

What is GLM-5.1?

GLM-5.1 is a large language model hosted on Hugging Face by zai-org, intended for chat and tool-calling workflows.

Pricing Breakdown

Open Weights (Self-hosted)

Free

✓Full model weights downloadable from Hugging Face
✓Use with vLLM, SGLang, Transformers, Ollama, llama.cpp
✓OpenAI-compatible API when self-served
✓Tool-calling and reasoning support
✓Subject to model license terms

Z.ai API Platform

Usage-based (see Z.ai)

per month

✓Managed GLM-5 endpoints
✓No infrastructure to run
✓Pay-per-token billing
✓Standard chat and tool-calling APIs
✓Hosted by Z.ai

Pros & Cons

✅Pros

•Best-in-class open-source performance on reasoning, coding, and agentic tasks per Z.ai benchmarks (e.g., 77.8 on SWE-bench Verified, 96.9 on HMMT Nov. 2025)
•Free open-weights download — no per-token API costs once self-hosted
•Massive 744B-parameter MoE with only 40B active per token, balancing capacity and inference cost
•DeepSeek Sparse Attention reduces long-context deployment cost meaningfully versus dense attention
•Wide deployment support: vLLM, SGLang, Transformers, Ollama, LM Studio, llama.cpp, Docker — covering most serving stacks
•Native tool-calling and chat templates ship with the model, simplifying agent integration
•Backed by Z.ai's 'slime' asynchronous RL infrastructure, with active iteration from GLM-4.5 to 4.7 to 5

❌Cons

•Running the full 744B-parameter model requires substantial GPU memory and multi-GPU infrastructure — out of reach for hobbyists
•Still trails frontier closed models like Gemini 3 Pro (91.9 GPQA) and GPT-5.2 on several benchmarks (HLE, GPQA-Diamond)
•Documentation on the Hugging Face card is sparse compared to commercial LLM platforms — most setup details live in external blogs and the GitHub repo
•No standalone polished web UI; users must self-host or use the separate Z.ai API platform
•Tool-calling uses a custom XML format that may require adapter code versus standard OpenAI function-calling JSON
•License terms and commercial-use specifics must be verified directly on the model card before production deployment

Who Should Use GLM-5.1?

✓Self-hosted enterprise coding assistants where data cannot leave the network — GLM-5.1's 77.8 SWE-bench Verified score makes it a credible Copilot alternative on internal infrastructure
✓Long-horizon autonomous agents that perform multi-step tool calls (browsing, code execution, file operations) and benefit from the model's native tool-calling chat template
✓Research labs benchmarking open-source frontier models on reasoning, math (AIME, HMMT), and graduate-level science (GPQA-Diamond) without paying per-token API fees
✓Multilingual software engineering teams leveraging the 73.3 SWE-bench Multilingual score for non-English codebases where many closed models underperform
✓High-volume batch inference workloads (document analysis, code review, synthetic data generation) where the free open weights eliminate API spend at scale
✓Fine-tuning and post-training experimentation, taking advantage of the open weights and Z.ai's slime asynchronous RL infrastructure for custom domain adaptation

Who Should Skip GLM-5.1?

×You're concerned about running the full 744b-parameter model requires substantial gpu memory and multi-gpu infrastructure — out of reach for hobbyists
×You're concerned about still trails frontier closed models like gemini 3 pro (91.9 gpqa) and gpt-5.2 on several benchmarks (hle, gpqa-diamond)
×You're concerned about documentation on the hugging face card is sparse compared to commercial llm platforms — most setup details live in external blogs and the github repo

Frequently Asked Questions

What is GLM-5.1?

GLM-5.1 is a large language model hosted on Hugging Face by zai-org, intended for chat and tool-calling workflows.

Is GLM-5.1 good?

Is GLM-5.1 free?

Yes, GLM-5.1 offers a free tier. However, premium features unlock additional functionality for professional users.

Who should use GLM-5.1?

What are the best GLM-5.1 alternatives?

Popular GLM-5.1 alternatives include Qwen 3. Each has different strengths, so compare features and pricing to find the best fit.