Recursive Flint

Recursive Flint

Recursive
SWE-2 Flash

SWE-2 Flash

Cognition
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About

Recursive Flint is a 40-billion-parameter mixture-of-experts language model for agentic coding on local hardware. It activates about 2.5 billion parameters per token and supports reasoning, multi-turn tool use, and context windows up to 512,000 tokens. Developers can use Flint with coding agents to inspect codebases, fix bugs, implement features, and write tests while running inference on their own hardware. Its weights are published under the Apache 2.0 license. Flint works with llama.cpp, Ollama, Unsloth, LM Studio, vLLM, and SGLang; Recursive also provides rec, an inference engine optimized for Apple Silicon M4 Pro and M5 Pro/Max. Setup documentation and examples help developers run the model locally. Flint is for developers and technical teams that want to operate and adapt a code-focused model on their own systems.

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 Not Supported
Mac Supported
Linux Not 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

Software developers and technical teams building or using coding agents, especially those seeking to run a coding model locally.

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 Supported

API

Offers API Not Supported

Screenshots and Videos

No images available

Screenshots and Videos

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

Pricing

$20/month
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:

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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

  • 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

Recursive
Founded: 2026
United States
recursive.com/updates/introducing-recursive-flint

Company Information

Cognition
Founded: 2023
United States
cognition.com

Alternatives

Laguna XS 2.1

Laguna XS 2.1

Poolside

Alternatives

GPT-6.1 Sol

GPT-6.1 Sol

OpenAI
Inkling

Inkling

Thinking Machines Lab

Categories

AI Coding Models Supported
AI Models Supported

Categories

AI Coding Models Supported
AI Models Supported

Integrations

.NET Not Supported
C Not Supported
C# Not Supported
C++ Not Supported
Dart Not Supported
Go Not Supported
HTML Not Supported
JSON Not Supported
MATLAB Not Supported
Ollama Supported
OpenRouter Supported
PHP Not Supported
PowerShell Not Supported
Python Not Supported
Ruby Not Supported
Scala Not Supported
Solidity Not Supported
TypeScript Not Supported
Unsloth Supported
YAML Not Supported

Integrations

.NET Supported
C Supported
C# Supported
C++ Supported
Dart Supported
Go Supported
HTML Supported
JSON Supported
MATLAB Supported
Ollama Not Supported
OpenRouter Not Supported
PHP Supported
PowerShell Supported
Python Supported
Ruby Supported
Scala Supported
Solidity Supported
TypeScript Supported
Unsloth Not Supported
YAML Supported
Claim Recursive Flint and update features and information
Claim Recursive Flint and update features and information
Claim SWE-2 Flash and update features and information
Claim SWE-2 Flash and update features and information