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GLM 5

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Facing slow, brittle AI decisions for complex tasks? Meet GLM 5, a 745B parameter model engineered for agentic intelligence, frontier-level reasoning, and autonomous tool use.

Stop Wasting Time on Manual Coding

With GLM 5, high-level code generation and debugging accelerate software engineering across languages.

Achieve Verifiable, Scalable Results

Its long-context processing via DeepSeek sparse attention enables multi-step workflows with reliable, scalable reasoning.

Open, Hardware-Independent & Open-Weight

GLM 5 runs on Huawei Ascend/MindSpore with an expected MIT license for open-weight commercial use.

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How GLM 5 Works In 3 Steps?

  1. 1. Sign up for GLM 5

    Create your account to access GLM 5's agentic AI and API.
  2. 2. Get API access tokens

    Generate keys to query GLM 5 for autonomous planning and tool use.
  3. 3. Build autonomous workflows

    Assemble agent-based tasks to leverage GLM 5's reasoning.

Customer Reviews for GLM 5

Overall Analytics

Comprehensive review insights and historical performance

Very Positive (2) 5.0/5 2 reviews 100% recommend — Monthly growth
6-month timeline
Most helpful
Zoe Clark
Zoe Clark 0

As a solo data scientist prototyping agent-driven workflows, GLM 5 lets the agent plan a multi-step pipeline (data prep, feature extraction, evaluation) and automatically invoke my local tooling through adapters. The real win is watching it replan on the fly when results don’t meet expectations.

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Recent Review Statistics

Sentiment analysis and trends from the last Last 30 days

5.0/5
2 reviews
Very Positive (2) New reviews
Trend: Steady Velocity: 0.1/day Engagement: 0%
Velocity utilization 14%
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Showing 1 - 2 of 2 reviews .

User avatar for Zoe Clark

Zoe Clark

5.0
Recommends

Autonomous planning that orchestrates my multi-step pipeline

Used for week to month

What I liked

  • Hero Feature: Autonomous planning that orchestrates a multi-step pipeline without constant prompting.
  • Tool integration: adapters let the agent call your local tooling automatically.
  • Context retention: long-context reasoning helps track data lineage and intermediate results.

What could be better

  • Pebble in the Shoe: Initial tool discovery latency during early runs slows the cadence of experiments.
  • Pebble in the Shoe: Sometimes it selects suboptimal tool orders, requiring manual intervention to steer the flow.
  • Pebble in the Shoe: Adapter documentation is adequate but lacks hands-on examples for custom tools.

As a solo data scientist prototyping agent-driven workflows, GLM 5 lets the agent plan a multi-step pipeline (data prep, feature extraction, evaluation) and automatically invoke my local tooling through adapters. The real win is watching it replan on the fly when results don’t meet expectations.

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User avatar for Fatima Al-Sayed

Fatima Al-Sayed

5.0
Recommends

Long-context reasoning shines for proofs, with open deployment a bonus

Used for 1-3 months

What I liked

  • Hero Feature: Long-context processing that preserves proof context across multiple steps.
  • Open-weight licensing enabling reproducible, open research and collaboration.
  • High-level code generation speeds up prototype math experiments.

What could be better

  • Pebble in the Shoe: No built-in formal proof checker to automatically verify each derivation step.
  • Pebble in the Shoe: Fine-tuning workflows and configuring academic toolchains could be documented more clearly.
  • Pebble in the Shoe: Initial setup for integrating niche math libraries requires additional wrappers.

As a university researcher exploring open-source AI for mathematical proofs, GLM 5's long-context processing keeps track of huge derivations and supports multi-step reasoning across chapters of notes. The open-weight license makes collaboration easy, and the high-level code generation helps with rapid prototypes.

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GLM 5: Features, Advantages & FAQs

Explore everything you need to know about GLM 5

Core Features
  • Autonomous planning: Enables multi-step decision making
  • Tool integration: Enables autonomous tool use
  • Long-context processing: Handles large-context reasoning efficiently
  • Hardware independence: Runs without vendor lock
  • Open-weight licensing: MIT-like license for open deployment
Advantages
  • High cost efficiency: Lower token costs vs rivals
  • Sparse attention DeepSeek: Efficient long-context processing
  • Open-weight availability under MIT license
  • Hardware-independent: Runs on Huawei Ascend/MindSpore
  • Optimized for agentic intelligence and tool use
Use Cases
  • Developing autonomous AI agents for multi-step workflows
  • High-level code generation and debugging
  • Complex mathematical proofs and scientific reasoning
  • Enterprise-scale content generation
  • Open-source research and fine-tuning

Frequently Asked Questions

What makes GLM-5 different from other models?

GLM-5 is a 745B parameter model with agentic intelligence, open-weight availability, and hardware independence.

When is the GLM 5 release date?

GLM 5 is scheduled for a February 2026 launch.

Is GLM 5 open source?

GLM 5 will have an expected MIT license for open-weight commercial use.

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Best Primary Tasks for GLM 5 — Top Use Cases & Workflows

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