**The Future of Coding is Here: Qwen3-Coder-Subsequent Revolutionizes the Way We Write Code**
Hey fellow coders! I’m stoked to share some incredible news with you all – the Qwen group has just released Qwen3-Coder-Subsequent, a groundbreaking open-source language model designed specifically for coding experts and local development. This game-changer is built on the Qwen3-Subsequent-80B-A3B backbone and leverages a sparse Combination-of-Experts (MoE) structure with hybrid attention.
For those not familiar, let me break it down: Qwen3-Coder-Subsequent is a powerful tool that can help you write better code, faster, and with greater accuracy. Whether you’re a seasoned developer or a coding newbie, this model is designed to simplify your workflow and accelerate your coding journey.
**What Sets Qwen3-Coder-Subsequent Apart?**
First off, this model boasts an impressive 80 billion parameters, but only 3 billion are active per token, which reduces inference costs while retaining high capability for specialized experts. That’s right, folks – this model is designed to be efficient, even with complex coding tasks.
The Qwen3-Coder-Subsequent model also features a hybrid attention stack, comprising Gated DeltaNet, Gated Attention, and MoE blocks over 48 layers with a hidden dimension of 2048. This architecture is optimized for long-horizon reasoning in code modification and agent workflows.
But that’s not all – Qwen3-Coder-Subsequent is trained on large-scale executable tasks and reinforcement learning on top of Qwen3-Subsequent-80B-A3B-Base. This means it can plan, call tools, run tests, and recover from failures like a pro, rather than just completing quick code snippets.
**The Numbers Don’t Lie – Qwen3-Coder-Subsequent Delivers**
The benchmarks are impressive, to say the least! Qwen3-Coder-Subsequent has achieved robust scores on SWE-Bench Verified, SWE-Bench Professional, SWE-Bench Multilingual, Terminal-Bench 2.0, and Aider, often matching or surpassing much larger MoE models with 10-20 times more active parameters.
**Deployment Options Galore – Choose Your Preference**
Qwen3-Coder-Subsequent can be deployed on servers using SGLang and vLLM, with OpenAI-compatible APIs. Or, you can deploy it locally using GGUF quantizations for llama.cpp, making it perfect for IDE brokers, CLI tools, and local personal coding copilots.
**Get Ready to Experience the Power of Qwen3-Coder-Subsequent**
Ready to take your coding skills to the next level with Qwen3-Coder-Subsequent? Check out the paper, repo, model weights, and technical details to learn more. Follow us on Twitter, join our 100k+ ML SubReddit, and subscribe to our Newsletter to stay up-to-date with the latest developments in machine learning.
In conclusion, Qwen3-Coder-Subsequent is a revolutionary coding language model that has the potential to transform the way we write code. With its impressive benchmarks, deployment options, and capabilities, this model is set to revolutionize the coding world.
