GLM-5.1

GLM-5.1

Zhipu AI
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About

GLM-5.1 is the latest iteration of Z.ai’s GLM series, designed as a frontier-level, agent-oriented AI model optimized for coding, reasoning, and long-horizon workflows. It builds on the GLM-5 architecture, which uses a Mixture-of-Experts (MoE) design to deliver high performance while keeping inference costs efficient, and is part of a broader push toward open-weight, developer-accessible models. A core focus of GLM-5.1 is enabling agentic behavior, meaning it can plan, execute, and iterate across multi-step tasks rather than simply responding to single prompts. It is specifically designed to handle complex workflows such as debugging code, navigating repositories, and executing chained operations with sustained context. Compared to earlier models, GLM-5.1 improves reliability in long interactions, maintaining coherence across extended sessions and reducing breakdowns in multi-step reasoning.

About

Muse Glimmer is a 30-billion-parameter open-weights model from Meta Superintelligence Labs, optimized for always-on local agent workflows. Small enough to run on a Mac or PC with a single consumer GPU, it is designed for local agents, function calling, coding, and LLM-as-a-judge evaluation without depending on cloud infrastructure or network access. The model combines long-horizon execution, precise tool calling, multimodal understanding, long-context memory, and instruction following. It can complete end-to-end agentic tasks, sustain multi-step reasoning across extended workflows, recover from failed or unexpected tool calls, and accept interleaved text and images through a dedicated perception encoder for interpreting screenshots, charts, and documents. Muse Glimmer works with OpenClaw and other agentic orchestration patterns, supports controllable reasoning effort, and is trained on data from more than 100 languages.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and AI teams who need a cost-efficient, agent-capable model for coding, automation, and long multi-step workflows with flexible deployment options

Audience

Developers building private, always-on AI agents that need strong reasoning, tool use, and multimodal capabilities on local hardware

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Open source
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Glimmer is exciting because it brings serious AI capability closer to the device. An open-weight model that can run on a laptop or desktop is a big deal for developers, builders, and AI power users who want more control. I like that it is focused on agentic tasks, not just basic chat. If it can handle reasoning, coding help, workflow automation, and local experimentation well, it could be really useful for private projects and always-on agents. The open-weight angle is the biggest win. Being able to download, modify, and run the model locally makes Muse Glimmer feel much more flexible than a closed API-only model.

Cons

  • I would still want to test it hard before trusting it for serious work. Smaller local models can be impressive, but they still need to prove themselves on coding, tool use, long tasks, and messy real-world prompts. Running locally also means the experience depends on your hardware. Even if it works on consumer devices, performance, speed, and setup may vary a lot.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Zhipu AI
Founded: 2023
China
z.ai/

Company Information

Meta
Founded: 2004
United States
meta.ai/

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Categories

Categories

Integrations

Hermes Agent
Ollama
OpenClaw
Canopy Wave
Claude Code
Dessix
GLM Coding Plan
Hugging Face
JavaScript
Kilo Code
LM Studio
PHP
Python
Qoder
Rust
Tabbit Browser
Vercel AI Gateway
Z.ai
pandas
scikit-learn

Integrations

Hermes Agent
Ollama
OpenClaw
Canopy Wave
Claude Code
Dessix
GLM Coding Plan
Hugging Face
JavaScript
Kilo Code
LM Studio
PHP
Python
Qoder
Rust
Tabbit Browser
Vercel AI Gateway
Z.ai
pandas
scikit-learn
Claim GLM-5.1 and update features and information
Claim GLM-5.1 and update features and information
Claim Muse Glimmer and update features and information
Claim Muse Glimmer and update features and information