GLM-5

GLM-5

Z.ai
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Google AI Studio
    30 Ratings
    Visit Website
  • Concord
    237 Ratings
    Visit Website
  • Planview AdaptiveWork
    714 Ratings
    Visit Website
  • Teradata VantageCloud
    1,124 Ratings
    Visit Website
  • ONLYOFFICE Docs
    715 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Interfacing Integrated Management System (IMS)
    66 Ratings
    Visit Website
  • Evertune
    1 Rating
    Visit Website
  • JS7 JobScheduler
    1 Rating
    Visit Website

About

GLM-5 is Z.ai’s latest large language model built for complex systems engineering and long-horizon agentic tasks. It scales significantly beyond GLM-4.5, increasing total parameters and training data while integrating DeepSeek Sparse Attention to reduce deployment costs without sacrificing long-context capacity. The model combines enhanced pre-training with a new asynchronous reinforcement learning infrastructure called slime, improving training efficiency and post-training refinement. GLM-5 achieves best-in-class performance among open-source models across reasoning, coding, and agent benchmarks, narrowing the gap with leading frontier models. It ranks highly on evaluations such as Vending Bench 2, demonstrating strong long-term planning and operational capabilities. The model is open-sourced under the MIT License.

About

Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.

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

AI researchers, developers, and engineering teams seeking an open-source, high-performance foundation model for advanced reasoning, coding, and long-horizon agentic applications

Audience

Muse Spark 1.1 is best suited for developers, AI engineers, enterprises, agent builders, coding tool teams, research teams, and productivity-focused users that need a multimodal reasoning model for agentic workflows, coding, computer use, long-context tasks, tool orchestration, and advanced automation

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

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.0 / 5
design 5.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Spark 1.1 has been awesome for the way I actually build with AI: agents, coding workflows, tool calls, debugging loops, and messy real-world tasks that do not fit neatly into a single prompt. It feels much stronger than the first version when I need it to reason through code, work across multiple steps, understand context, and keep an agent moving without constantly falling apart. The multimodal side is also a big plus because being able to work with docs, screenshots, images, and other inputs makes it way more useful for building practical AI products.

Cons

  • It is still early, so I would not call it perfect yet. Like any advanced model, you still need good scaffolding, evals, guardrails, and monitoring if you are putting it into production agent workflows. I also want to see the API ecosystem, docs, examples, and integration patterns mature more, because those things matter a lot when you are building real agentic systems instead of just testing prompts.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Z.ai
Founded: 2023
China
z.ai/

Company Information

Meta
Founded: 2004
United States
meta.ai

Alternatives

Alternatives

GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
Claude Opus 4.5

Claude Opus 4.5

Anthropic
Grok 4.6

Grok 4.6

SpaceXAI
Claude Opus 4.6

Claude Opus 4.6

Anthropic
Claude Opus 5

Claude Opus 5

Anthropic
GLM-5.3

GLM-5.3

Z.ai
ERNIE 5.1

ERNIE 5.1

Baidu

Categories

Categories

Integrations

Claude Code
OpenClaw
.NET
APIFree
Cline
Facebook Messenger
GLM-5-Turbo
Instagram
Kilo Code
Kotlin
LangChain
Meta Model API
Muse Code
Muse Spark
Muse Video
OpenAI Codex
OpenRouter
Ruby
Rust
Shiori

Integrations

Claude Code
OpenClaw
.NET
APIFree
Cline
Facebook Messenger
GLM-5-Turbo
Instagram
Kilo Code
Kotlin
LangChain
Meta Model API
Muse Code
Muse Spark
Muse Video
OpenAI Codex
OpenRouter
Ruby
Rust
Shiori
Claim GLM-5 and update features and information
Claim GLM-5 and update features and information
Claim Muse Spark 1.1 and update features and information
Claim Muse Spark 1.1 and update features and information