Recursive Flint

Recursive Flint

Recursive
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About

DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.

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.

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 Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI researchers, developers, and enterprises seeking a powerful open-source language model for large-scale reasoning, coding, and long-context AI applications

Audience

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

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 Not Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

$0.435 per 1M tokens (input)
$0.435 per 1 million input tokens (cache miss), $0.003625 per 1 million input tokens (cache hit), and $0.87 per 1 million output tokens
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5

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

Pros & Cons from Real Users

Pros

  • DeepSeek-V4-Pro is one of those models I keep coming back to because it handles serious work without feeling ridiculously expensive. For coding, repo analysis, long debugging threads, and agent-style workflows, the 1M-token context window is a huge advantage. I also like that it feels strong across both reasoning and implementation. I can use it to think through architecture, explain a messy bug, generate a fix, write tests, and then sanity-check the tradeoffs without constantly switching models. The Pro-Max reasoning mode is especially useful when I need it to slow down and really work through something. It is not the mode I would use for every quick answer, but for hard technical problems, it gives the model a lot more room to reason. The open-weight angle is a big plus too. As someone who uses it heavily, I like having more flexibility than a purely closed API model gives me.

Cons

  • It is still not something I would run on autopilot. For production code, I always review diffs, run tests, and check edge cases because even strong models can make confident mistakes. It can also be overkill for simple tasks. If I just need a quick explanation, small script, or lightweight edit, DeepSeek-V4-Flash may be the better fit. The size is another consideration. Open weights are great, but self-hosting a 1.6T-parameter MoE model is not casual infrastructure.

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

DeepSeek
Founded: 2023
China
deepseek.com

Company Information

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

Alternatives

Alternatives

Laguna XS 2.1

Laguna XS 2.1

Poolside
DeepSeek-V4

DeepSeek-V4

DeepSeek

Categories

AI Coding Models Supported
AI Models Supported

Categories

AI Coding Models Supported
AI Models Supported

Integrations

.NET Supported
Bash Supported
Buda Supported
C# Supported
C++ Supported
CSS Supported
ClinePass Supported
DeepSeek Harness Supported
Go Supported
HTML Supported
Java Supported
Novita AI Supported
Objective-C Supported
OfoxAI Supported
Oxlo.ai Supported
Swift Supported
TypeScript Supported
XML Supported
YAML Supported
vLLM Not Supported

Integrations

.NET Not Supported
Bash Not Supported
Buda Not Supported
C# Not Supported
C++ Not Supported
CSS Not Supported
ClinePass Not Supported
DeepSeek Harness Not Supported
Go Not Supported
HTML Not Supported
Java Not Supported
Novita AI Not Supported
Objective-C Not Supported
OfoxAI Not Supported
Oxlo.ai Not Supported
Swift Not Supported
TypeScript Not Supported
XML Not Supported
YAML Not Supported
vLLM Supported
Claim DeepSeek-V4-Pro and update features and information
Claim DeepSeek-V4-Pro and update features and information
Claim Recursive Flint and update features and information
Claim Recursive Flint and update features and information