Qwen3.8-Max

Qwen3.8-Max

Alibaba
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About

Muse Spark Open is an open-weight, natively multimodal language model for developers and organizations building AI applications, coding systems, and agentic workflows. The released model has 816 billion total parameters, 42 billion active parameters, and a 1-million-token context window. Teams can download the model weights, run inference through supported engines such as vLLM, SGLang, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp, or Unsloth, and customize the model using PyTorch. It supports long-context reasoning, software engineering, coding, tool use, and multimodal inputs. Deployment options include cloud inference through listed API providers or self-hosting on compatible GPU systems; Meta documents a desktop setup using two Apple M5 Ultra Mac Studio computers. The model is released under the Muse Model License with limited commercial terms.

About

Qwen3.8-Max is Qwen’s most capable model to date, built as a Max-class AI model for coding, work, research, long-horizon tasks, and multimodal agents. It scales to 2.4 trillion parameters with 95 billion active parameters and is available through QwenCloud. The model is designed to complete complex, open-ended tasks end to end with greater reliability and minimal human involvement. Qwen3.8-Max supports autonomous coding workflows, agentic development, research reproduction, visual reasoning, document understanding, video analysis, and real-world productivity tasks. It can integrate with popular agent frameworks and coding assistants, including Claude Code, Codex, Qoder CLI, Qwen Code, and OpenClaw. Built for developers, researchers, enterprises, and AI agent builders, Qwen3.8-Max helps teams automate sophisticated work across code, documents, tools, interfaces, and multimodal content.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers, machine learning engineers, software engineers, AI researchers, enterprise development teams, and organizations seeking customizable open-weight multimodal models for local inference, autonomous agents, complex coding, and long-context AI applications

Audience

Developers and AI teams that need scalable access to text, image, video, audio, and multimodal AI models for building applications

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$0
Model weights are available at no charge under the Muse Model License, which has limited commercial-use terms. Hosted inference providers set their own usage prices.
Free Version Supported
Free Trial Not Supported

Pricing

$2 per 1M (input)
$2 per 1 million tokens (input), $6 per 1 million tokens (output)
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Reviews/Ratings

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

Pros & Cons from Real Users

Pros

  • Meta finally opened up a genuinely frontier-level Muse model. The 1M-token context window and 42B active parameters make it strong enough for large repos, long agent sessions, multimodal work, and complex coding without feeling like a stripped-down open model. The local deployment story is also a huge deal. Being able to run something this capable on two M5 Ultra Mac Studios is impressive, especially for teams that want more control over data, infrastructure, and customization. I also like how much of the stack is open around it. Muse Spark Open works with MLX, vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, and Unsloth, and Meta is making the weights available through Hugging Face, SageMaker, Google Cloud Model Garden, and Microsoft Foundry.

Cons

  • Even though it is technically desktop-capable, needing two M5 Ultra Mac Studios for the full local experience is still a serious setup, so most developers will probably use hosted inference instead.

Pros & Cons from Real Users

Pros

  • Qwen3.8-Max is really interesting from a developer’s perspective. A 2.4T-parameter model that can handle text, images, video, and documents has a lot of potential for coding agents, repo analysis, multimodal debugging, and workflows where the model needs to understand more than just plain text.

Cons

  • The biggest downside is that a lot of the hype still needs proof. Alibaba is claiming Qwen3.8-Max trails only Fable 5, but current reports say there are no public benchmark scores, no model card, no activated-parameter count, and no independent leaderboard results yet.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Meta
Founded: 2004
United States
research.meta.ai/blog/muse-spark-open

Company Information

Alibaba
Founded: 1999
China
qwen.ai

Alternatives

Alternatives

Laguna XS 2.1

Laguna XS 2.1

Poolside
Qwen 4

Qwen 4

Alibaba

Categories

AI Coding Models Supported
AI Models Supported
AI Receptionists Supported
Foundation Models Supported
Multimodal Models Supported

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

Hugging Face Supported
Alibaba Cloud Not Supported
Alibaba Cloud Model Studio Not Supported
Baseten Supported
Cherry Studio Not Supported
ClinePass Not Supported
Happy Shrimp 1.0 Not Supported
Hermes Agent Not Supported
Modal Supported
Model Context Protocol (MCP) Not Supported
ModelScope Not Supported
OpenClaw Not Supported
OpenRouter Supported
Python Not Supported
Qwen Not Supported
Qwen Code Not Supported
Qwen Studio Not Supported
QwenCloud Not Supported
QwenWork Not Supported
vLLM Supported

Integrations

Hugging Face Supported
Alibaba Cloud Supported
Alibaba Cloud Model Studio Supported
Baseten Not Supported
Cherry Studio Supported
ClinePass Supported
Happy Shrimp 1.0 Supported
Hermes Agent Supported
Modal Not Supported
Model Context Protocol (MCP) Supported
ModelScope Supported
OpenClaw Supported
OpenRouter Not Supported
Python Supported
Qwen Supported
Qwen Code Supported
Qwen Studio Supported
QwenCloud Supported
QwenWork Supported
vLLM Not Supported
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information
Claim Qwen3.8-Max and update features and information
Claim Qwen3.8-Max and update features and information