MiniMax M3

MiniMax M3

MiniMax
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About

GLM-5.3-Flash is Z.ai’s natively multimodal model in the GLM-5 series (previously previewed as Ox Alpha), designed to deliver strong coding, agentic, visual, and knowledge-work performance at relatively low inference cost. It uses 320 billion total parameters with 18 billion active parameters, along with a hybrid architecture that combines sparse and linear attention to reduce the cost of long-context processing. The model supports context lengths of up to one million tokens and was trained on a 30-trillion-token multimodal corpus. GLM-5.3-Flash can reason across text, images, documents, interfaces, dashboards, and other visual information while using that feedback to refine its own outputs. Z.ai reports substantial gains over GLM-5.2 on coding and agentic benchmarks, including DeepSWE and AutomationBench, while approaching higher-cost frontier models on several evaluations.

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

Developers, AI engineers, agent builders, researchers, and organizations that need cost-efficient multimodal reasoning, long-context processing, advanced coding, visual analysis, and autonomous workflow capabilities

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

$0.15 per 1M tokens (input)
Input: $0.15 per 1M tokens
Output: $0.50 per 1M tokens
Cached input: $0.03 per 1M tokens
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

Reviews/Ratings

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

Pros & Cons from Real Users

Pros

  • What makes it exciting is that it seems built for the exact workloads developers care about right now: long-horizon coding, complex reasoning, big-context analysis, and agentic workflows. A million-token context window is especially useful if you want to drop in a large repo, long spec, research corpus, or messy project history and have the model reason across it.

Cons

  • I would treat it as something exciting to test, not something to blindly trust with sensitive work. Even the independent Ox Alpha site warns that messages are processed by the upstream model API, so I would keep secrets, private code, and customer data out of it until there is a clearer owner, model card, privacy policy, and production story.

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: 2019
China
z.ai

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io

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Categories

Categories

Integrations

Claude Code
Hermes Agent
OpenClaw
OpenCode Go
OpenCode Zen
Pi Agent
APIFree
Cheaper Inference
Clawd.run
ClinePass
Factory Droid
Fireworks AI
GLM Coding Plan
Kilo Code
MaxHermes
MiniMax Code
Ollama
OpenRouter
Tabbit Browser
omp

Integrations

Claude Code
Hermes Agent
OpenClaw
OpenCode Go
OpenCode Zen
Pi Agent
APIFree
Cheaper Inference
Clawd.run
ClinePass
Factory Droid
Fireworks AI
GLM Coding Plan
Kilo Code
MaxHermes
MiniMax Code
Ollama
OpenRouter
Tabbit Browser
omp
Claim GLM-5.3-Flash and update features and information
Claim GLM-5.3-Flash and update features and information
Claim MiniMax M3 and update features and information
Claim MiniMax M3 and update features and information