SWE-2 Flash

SWE-2 Flash

Cognition
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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

SWE-2 Flash is an AI coding model developed by Cognition to provide fast, cost-efficient software engineering capabilities for autonomous development agents. Built on Thinking Machines' Inkling-Small foundation model, it uses mid-training and reinforcement learning to improve coding performance, reasoning, and task execution. The model supports software development activities such as code generation, code reviews, feature development, documentation updates, and automated engineering workflows. SWE-2 Flash generates approximately 200 tokens per second, making it three times faster and five times less expensive than the larger SWE-2 model. Its 276-billion-parameter mixture-of-experts architecture activates approximately 12 billion parameters during inference to balance performance and computational efficiency. SWE-2 Flash is available through Devin Desktop and CLI, with Cognition also developing a secure model-weight sharing program for trusted research and enterprise partners.

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

Software developers, AI coding assistant users, software engineering teams, DevOps professionals, autonomous agent developers, AI researchers, enterprise development organizations, and cybersecurity researchers seeking fast, cost-efficient AI coding, automated code reviews, feature implementation, software maintenance, technical reasoning, and agentic development workflows

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 Not 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

$20/month
Free Version 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

  • This is the kind of model I would use all day for normal engineering work. It is fast enough that it does not feel like I am waiting on the model, but it is still strong enough for feature work, code review, docs, automations, and debugging. The speed is probably the biggest win. Cognition says it runs at around 200 tokens per second versus about 60 for SWE-2, and that difference matters a lot once an agent starts iterating through files and tools. The cost-performance balance is also really good. It is one-fifth the price of SWE-2, while scoring 45.5 on FrontierCode 1.1 Main, 60.1 on DeepSWE 1.1, and 89.9 on SWE-Bench Pro v2 Hard.

Cons

  • My main complaint is that it is not the model I would choose for the hardest repo-wide work. SWE-2 still has a noticeable edge on some tougher benchmarks, so I would move up when the task really needs it.

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

Cognition
Founded: 2023
United States
cognition.com

Alternatives

Alternatives

GPT-6.1 Sol

GPT-6.1 Sol

OpenAI
GPT-6.1 Sol

GPT-6.1 Sol

OpenAI
Inkling

Inkling

Thinking Machines Lab
Inkling

Inkling

Thinking Machines Lab

Categories

Categories

AI Coding Models Supported
AI Models Supported

Integrations

.NET Not Supported
Baseten Supported
C# Not Supported
C++ Not Supported
Cerebras Not Supported
Dart Not Supported
Devin Desktop Not Supported
HTML Not Supported
Kotlin Not Supported
Kubernetes Not Supported
Objective-C Not Supported
Python Not Supported
R Not Supported
SQL Not Supported
Scala Not Supported
Terraform Not Supported
Together AI Supported
TypeScript Not Supported
XML Not Supported
YAML Not Supported

Integrations

.NET Supported
Baseten Not Supported
C# Supported
C++ Supported
Cerebras Supported
Dart Supported
Devin Desktop Supported
HTML Supported
Kotlin Supported
Kubernetes Supported
Objective-C Supported
Python Supported
R Supported
SQL Supported
Scala Supported
Terraform Supported
Together AI Not Supported
TypeScript Supported
XML Supported
YAML Supported
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information
Claim SWE-2 Flash and update features and information
Claim SWE-2 Flash and update features and information