GLM-5.3

GLM-5.3

Z.ai
MiniMax M3

MiniMax M3

MiniMax
+
+

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About

GLM-5.3 is Z.ai’s frontier coding model designed for complex software engineering, long-horizon agent tasks, and advanced post-training research. The model uses the same base model as GLM-5.2, with improvements coming from scaled post-training across more environments, more diverse tasks, and larger compute investment. GLM-5.3 delivers stronger coding performance, better task ownership, improved benchmark results, and greater efficiency across realistic development workflows. It is built to handle complex coding tasks, production-style engineering work, research environments, automation tasks, and agentic workflows that require multi-step execution. The model also shows emergent cyber capabilities in vulnerability discovery and exploitation-chain reasoning, with safety evaluation and hardening planned before open-weight release.

About

MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.

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

Software engineers, coding agent builders, AI researchers, ML infrastructure teams, security researchers, developer tool teams, automation teams, technical leaders, and organizations that need frontier coding models, long-horizon reasoning, production-style software engineering, benchmark-driven model evaluation, reinforcement learning research, coding-agent integrations, reasoning effort controls, ZCode workflows, and advanced technical task automation

Audience

MiniMax M3 is best suited for developers, AI engineers, coding assistant builders, enterprise automation teams, research teams, data teams, agent developers, and organizations that need open-weight AI for coding, long-context reasoning, multimodal understanding, tool use, repository analysis, and autonomous workflows

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

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 4.0 / 5

Pros & Cons from Real Users

Pros

  • The thing I like most is that GLM-5.3 feels aimed at serious engineering work, not casual prompting. It is built around coding agents, long-running software tasks, debugging, and the kind of multi-step execution that actually matters when you are working inside real repos. The post-training jump is also interesting. Z.ai is not just talking about a bigger model; it is pushing the idea that better training on agentic coding and cyber workflows can make the model more useful in practice.

Cons

  • The cybersecurity angle is impressive, but it is also where I would be most cautious. Strong vulnerability discovery and cyber reasoning can be useful for defense, audits, and secure engineering, but I would want very clear controls around how it is used.

Pros & Cons from Real Users

Pros

  • The multimodal side also makes it more flexible than a code-only model. Being able to work across text, images, video-style understanding, and code gives it more room to support real workflows instead of being boxed into one narrow use case. For agent builders, the best part is that M3 is clearly designed around tool use and multi-step execution. MiniMax specifically calls out autonomous task decomposition and tool invocation, which is exactly what matters when a model is powering coding assistants, workflow agents, or automated dev tools.

Cons

  • The main catch is infrastructure and trust. Even with sparse attention and MoE efficiency, this is still a large model, so deployment is not casual. I would also want to benchmark it on my own repos before depending on it for production work.

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

MiniMax
Founded: 2021
Singapore
www.minimax.io

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GLM-5

GLM-5

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MiniMax

MiniMax

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GLM-5.1

GLM-5.1

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Categories

Categories

Integrations

APIFree
Claude Code
Cline
ClinePass
Factory Droid
Hermes Agent
Kilo Code
Ollama
OpenClaw
Roo Code
Tabbit Browser
Together AI
Augment Code
Fireworks AI
MiniMax Agent
MiniMax Mavis
Pi Agent
Swift
Vercel AI Gateway
Zo Computer

Integrations

APIFree
Claude Code
Cline
ClinePass
Factory Droid
Hermes Agent
Kilo Code
Ollama
OpenClaw
Roo Code
Tabbit Browser
Together AI
Augment Code
Fireworks AI
MiniMax Agent
MiniMax Mavis
Pi Agent
Swift
Vercel AI Gateway
Zo Computer
Claim GLM-5.3 and update features and information
Claim GLM-5.3 and update features and information
Claim MiniMax M3 and update features and information
Claim MiniMax M3 and update features and information