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Description
Muse Glimmer is an open-weights model featuring 30 billion parameters, developed by Meta Superintelligence Labs, and is fine-tuned for continuous local agent operations. Its compact design allows it to function on a standard Mac or PC equipped with a single consumer GPU, making it ideal for various tasks such as local agent management, function calling, programming, and LLM-as-a-judge evaluations without reliance on cloud services or internet connectivity. This innovative model integrates advanced capabilities such as long-horizon execution, accurate tool invocation, multimodal comprehension, extended memory for context, and effective instruction following. It is proficient in accomplishing end-to-end tasks as an agent, maintains the ability to engage in multi-step reasoning over lengthy processes, can recover gracefully from failed or unanticipated tool engagements, and interprets interleaved text and images using a specialized perception encoder designed for analyzing screenshots, graphs, and document files. Furthermore, Muse Glimmer is compatible with OpenClaw and other orchestration frameworks, allowing for adjustable reasoning efforts, and has been developed with a diverse dataset encompassing over 100 languages. The model's versatility ensures that it can adapt to various applications, thus enhancing its utility in different domains.
Description
Qwen 4 is the upcoming fourth-generation foundation model in Alibaba’s Qwen AI family. Alibaba publicly confirmed at its 2026 Apsara Conference that the model is currently being trained. The company has not yet released technical specifications, model weights, API access, pricing, benchmark results, or a launch date for Qwen 4. Its development forms part of Alibaba’s broader effort to advance foundation models capable of increasingly complex and long-horizon work. The Qwen team is also researching recursive self-improvement, in which models use empirical feedback to identify weaknesses, design experiments, evaluate results, and iteratively improve training processes. Alibaba demonstrated this approach with Qwen3.8-Max, which completed 33 automated optimization cycles during a month-long experiment and improved its Artificial Analysis score from 40 to 45. These experiments provide context for Alibaba’s model-development direction but do not establish specific Qwen 4 capabilities. Alibaba has additionally outlined Qwen 4.5 and Qwen 5 models that could eventually scale to between 5 trillion and 10 trillion parameters. Until Qwen 4 is released, its exact architecture, modalities, performance, deployment options, and licensing remain to be announced.
API Access
Has API
Yes
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
Hermes Agent
Yes
Hugging Face
Yes
Ollama
Yes
OpenClaw
Yes
Alibaba Cloud
No
Alibaba Cloud Model Studio
No
Cherry Studio
No
Cline
No
Model Context Protocol (MCP)
No
ModelScope
No
Integrations
Hermes Agent
Yes
Hugging Face
Yes
Ollama
Yes
OpenClaw
Yes
Alibaba Cloud
Yes
Alibaba Cloud Model Studio
Yes
Cherry Studio
Yes
Cline
Yes
Model Context Protocol (MCP)
Yes
ModelScope
Yes
Pricing Details
Free
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
meta.ai/
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai