DeepCoder

DeepCoder

Agentica Project
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About

DeepCoder is a fully open source code-reasoning and generation model released by Agentica Project in collaboration with Together AI. It is fine-tuned from DeepSeek-R1-Distilled-Qwen-14B using distributed reinforcement learning, achieving a 60.6% accuracy on LiveCodeBench (representing an 8% improvement over the base), a performance level that matches that of proprietary models such as o3-mini (2025-01-031 Low) and o1 while using only 14 billion parameters. It was trained over 2.5 weeks on 32 H100 GPUs with a curated dataset of roughly 24,000 coding problems drawn from verified sources (including TACO-Verified, PrimeIntellect SYNTHETIC-1, and LiveCodeBench submissions), each problem requiring a verifiable solution and at least five unit tests to ensure reliability for RL training. To handle long-range context, DeepCoder employs techniques such as iterative context lengthening and overlong filtering.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers, researchers, and enthusiasts wanting a tool to generate, debug, or reason about code without relying on proprietary models

Audience

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

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

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
Free Trial

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

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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Agentica Project
Founded: 2025
United States
agentica-project.com

Company Information

DeepSeek
Founded: 2023
China
deepseek.com

Alternatives

DeepSWE

DeepSWE

Agentica Project

Alternatives

Devstral 2

Devstral 2

Mistral AI
Devstral Small 2

Devstral Small 2

Mistral AI
GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
DeepScaleR

DeepScaleR

Agentica Project
DeepSeek-V4

DeepSeek-V4

DeepSeek

Categories

Categories

Integrations

Together AI
Bash
Buda
C
Cheaper Inference
ClinePass
DeepSeek
Go
HTML
JavaScript
Kotlin
MoClaw
Objective-C
OpenTag
Oxlo.ai
PowerShell
Reasonix
TypeScript
XML
ZooClaw

Integrations

Together AI
Bash
Buda
C
Cheaper Inference
ClinePass
DeepSeek
Go
HTML
JavaScript
Kotlin
MoClaw
Objective-C
OpenTag
Oxlo.ai
PowerShell
Reasonix
TypeScript
XML
ZooClaw
Claim DeepCoder and update features and information
Claim DeepCoder and update features and information
Claim DeepSeek-V4-Pro and update features and information
Claim DeepSeek-V4-Pro and update features and information