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GLM-5.1

Free plan

#1 on SWE-Bench Pro — open-source coding model that beats GPT-5.4 and Claude Opus 4.6

4.7

15 reviews

Free plan

from $10/mo

For developers

Audience

Platform Availability
Web
API
Tags
open sourcecodingLLMMoESWE-BenchZhipu AIautonomousagents

About GLM-5.1

GLM-5.1 Overview

GLM-5.1 is the flagship model from Chinese company Zhipu AI (also known as Z.ai), which claimed the #1 spot on SWE-Bench Pro with a score of 58.4, surpassing GPT-5.4 and Claude Opus 4.6. It is a fully open model under the MIT license, available for download on HuggingFace.

About Zhipu AI

Zhipu AI is one of China's leading AI companies, founded in 2019. The company has IPO'd on the Hong Kong Stock Exchange and is one of the biggest players in the open model space. GLM models were originally developed at Tsinghua University and have evolved into competitive commercial products.

Architecture

GLM-5.1 uses a Mixture of Experts (MoE) architecture with a total of 744B parameters, of which only 40B are active per request. This achieves the performance of a giant model at significantly lower computational cost. The model was trained on Huawei Ascend clusters, demonstrating that world-class training is possible without NVIDIA chips.

Coding Capabilities

GLM-5.1's headline achievement is its #1 ranking on SWE-Bench Pro, the most authoritative benchmark for evaluating real-world coding abilities of AI. The model scored 58.4, surpassing GPT-5.4 (56.8) and Claude Opus 4.6 (55.2). This means GLM-5.1 can solve real tasks from open-source projects — finding and fixing bugs, implementing new features, and writing tests.

A unique capability is autonomous work on a task for up to 8 hours. The model can independently analyze a codebase, plan changes, implement them, run tests, and iteratively improve the solution. This makes it one of the most powerful AI coders in the world.

Context Window

GLM-5.1 supports 200K input tokens and up to 128K output tokens. This large window lets you load entire codebases into context and receive detailed, comprehensive responses.

Developer Tool Integration

The model is compatible with major AI coding tools:

  • Claude Code — via model configuration settings
  • Cursor — via the Z.ai API endpoint
  • Cline — via the standard OpenAI-compatible API
  • VS Code — via the Continue extension

API & Pricing

Z.ai offers a cloud API at $1.40 per 1M input tokens and $4.40 per 1M output tokens. For developers who want a full AI-powered development environment, GLM Coding is available at $10/month — an integrated environment with priority model access.

Open Source

All model weights are available on HuggingFace under the MIT license. This means full freedom of use — commercial use, modification, and distribution without restrictions. However, self-hosting the 744B-parameter model requires serious hardware (multiple A100/H100 GPUs).

Comparison with Competitors

Compared to GPT-5.4 and Claude Opus 4.6, GLM-5.1 excels specifically in practical coding tasks. In general tasks (reasoning, knowledge, creative writing), competitors may be stronger, but for developers GLM-5.1 offers the best price-to-performance ratio, especially given its open-source nature.

Conclusion

GLM-5.1 is a landmark model demonstrating that open-source models can compete with proprietary solutions at the highest level. For developers who need a powerful AI coding assistant, GLM-5.1 is one of the best options on the market.

GLM-5.1 features

🏆

#1 SWE-Bench Pro

Score 58.4, beating GPT-5.4 and Claude Opus 4.6

🧠

744B MoE

744B parameters with 40B active for efficient inference

8-Hour Autonomy

Can work on coding tasks autonomously for up to 8 hours

📖

200K Context

200K input tokens, up to 128K output tokens

Pros and cons

Pros

  • #1 on SWE-Bench Pro
  • Fully open source (MIT)
  • 8-hour autonomous coding
  • Compatible with Cursor, Claude Code
  • 200K context window

Cons

  • New model, limited community
  • API pricing not the cheapest
  • Requires powerful hardware for self-hosting
  • Documentation mainly in Chinese and English

Pricing

Open Source

Free
  • MIT license
  • HuggingFace weights
  • Self-hosted

API

$1.40/ per 1M input tokens
  • $4.40/1M output
  • Cloud inference
  • Rate limits
Popular

GLM Coding

$10/ per month
  • Integrated coding environment
  • Priority access
  • Extended limits

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