Muse Spark OpenMeta
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RankGPTWeiwei Sun
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Related Products
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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.
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About
RankGPT is a Python toolkit designed to explore the use of generative Large Language Models (LLMs) like ChatGPT and GPT-4 for relevance ranking in Information Retrieval (IR). It introduces methods such as instructional permutation generation and a sliding window strategy to enable LLMs to effectively rerank documents. It supports various LLMs, including GPT-3.5, GPT-4, Claude, Cohere, and Llama2 via LiteLLM. RankGPT provides modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. It includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs. RankGPT's Model Zoo includes models like LiT5 and MonoT5, hosted on Hugging Face.
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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
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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
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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
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Audience
AI researchers needing a tool to leverage LLMs for advanced document reranking in information retrieval systems
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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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
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Pros & Cons from Real UsersPros
Cons
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationMeta
Founded: 2004
United States
research.meta.ai/blog/muse-spark-open
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Company InformationWeiwei Sun
United States
github.com/sunnweiwei/RankGPT
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Alternatives |
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Categories |
Categories |
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Integrations
Hugging Face
Supported
Baseten
Supported
ChatGPT
Not Supported
Claude
Not Supported
Cohere
Not Supported
Fireworks AI
Supported
GPT-3.5
Not Supported
GPT-4
Not Supported
Groq
Supported
LiteLLM
Not Supported
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Integrations
Hugging Face
Supported
Baseten
Not Supported
ChatGPT
Supported
Claude
Supported
Cohere
Supported
Fireworks AI
Not Supported
GPT-3.5
Supported
GPT-4
Supported
Groq
Not Supported
LiteLLM
Supported
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