LFM2.5 vs. Muse Spark Open Comparison


LFM2.5 Liquid AI	Muse Spark Open Meta	+	+
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About Liquid AI’s LFM2.5 is the next generation of on-device AI foundation models designed to deliver high-performance, efficient AI inference on edge devices such as phones, laptops, vehicles, IoT systems, and embedded hardware without relying on cloud compute. It extends the previous LFM2 architecture by significantly increasing the pretraining scale and reinforcement learning stages, yielding a family of hybrid models around 1.2 billion parameters that balance instruction following, reasoning, and multimodal capabilities for real-world agentic use cases. The LFM2.5 family includes Base (for fine-tuning and customization), Instruct (general-purpose instruction-tuned), Japanese-optimized, Vision-Language, and Audio-Language variants, all optimized for fast, on-device inference under tight memory constraints and available as open-weight models deployable via frameworks like llama.cpp, MLX, vLLM, and ONNX.	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.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Supported iPad Supported Android Supported Chromebook Not Supported	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
Audience Developers and organizations building on-device AI applications and intelligent agents that need efficient, high-quality AI models capable of running locally on consumer, edge, or embedded hardware	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
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported
API Offers API Not Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Supported	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
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 Read all reviews
	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.
Training Documentation Supported Webinars Not Supported Live Online Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information Liquid AI Founded: 2023 United States www.liquid.ai/blog/introducing-lfm2-5-the-next-generation-of-on-device-ai	Company Information Meta Founded: 2004 United States research.meta.ai/blog/muse-spark-open
Alternatives Muse Spark Open Meta	Alternatives Gemini 4 Argon Google
Llama 3.1 Meta	Claude Sonnet 5.5 Anthropic
MedGemma Google DeepMind	Claude Fable 5.1 Anthropic
HunyuanOCR Tencent	Muse Glimmer Meta
Reka Flash 3 Reka View All	Laguna XS 2.1 Poolside View All
Categories AI Models Supported	Categories AI Coding Models Supported AI Models Supported AI Reasoning Models Supported AI Receptionists Supported Foundation Models Supported Large Language Models Supported Multimodal Models Supported

Integrations Hugging Face Supported Amazon Bedrock Supported Baseten Not Supported ElevenLabs Supported Fireworks AI Not Supported Gemma 3 Supported Gemma 4 Supported Groq Not Supported LEAP Supported Llama Supported Llama 3.2 Supported Modal Not Supported Nebius Not Supported OpenRouter Not Supported Qwen3 Supported Together AI Not Supported vLLM Not Supported Show More Integrations View All 9 Integrations	Integrations Hugging Face Supported Amazon Bedrock Not Supported Baseten Supported ElevenLabs Not Supported Fireworks AI Supported Gemma 3 Not Supported Gemma 4 Not Supported Groq Supported LEAP Not Supported Llama Not Supported Llama 3.2 Not Supported Modal Supported Nebius Supported OpenRouter Supported Qwen3 Not Supported Together AI Supported vLLM Supported Show More Integrations View All 9 Integrations
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