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LatestQwen · AlibabaQwen3-Coder-480B-A35B
Qwen · AlibabaCode

Qwen Releases 480B Open-Source Model for Code Agents

The new flagship coding model from Alibaba's Qwen team uses a massive Mixture-of-Experts architecture and is released under a permissive Apache-2.0 license.

Jul 22, 2025
Major releaseApache 2.0
Qwen3-Coder-30B-A3B-Instruct

Alibaba's Qwen team has released a powerful new open-source model specialized for code generation and agentic tasks. The model, named Qwen3-Coder-480B-A35B-Instruct, marks a significant entry into the high-end landscape of AI coding assistants, combining immense scale with an efficient architecture.

At its core, Qwen3-Coder is a Mixture-of-Experts (MoE) model. While it contains a massive 480 billion total parameters, it only activates a sparse 35 billion for any given input. This design aims to provide the vast knowledge capacity of a very large model while maintaining more manageable computational requirements for inference, striking a balance between power and efficiency.

Long Context and a Permissive License

Beyond its MoE architecture, the model boasts two key features that set it apart. First is its exceptionally long context window of 262,144 tokens, allowing it to process and reason over entire codebases or lengthy project histories. This is critical for complex, multi-file software development tasks.

Second, and perhaps most importantly for the community, Qwen3-Coder is released under the Apache-2.0 license. This permissive license allows for both commercial and research use, giving developers a powerful, unrestricted foundation to build sophisticated new tools and coding agents. You can find the model and its details on its Hugging Face repository.

Sources

  • Qwen/Qwen3-Coder-480B-A35B-Instruct

    Hugging Face

    Visit
OlderZ.ai Releases 355B Parameter GLM-4.5 Under MIT LicenseZhipu AI · Text / LLM · last yearNewerQwen Releases Wan2.2, a 14B Image-to-Video ModelQwen · Alibaba · Image → Video · last year

Get the model

Hugging Face

Specs

Parameters480B · MoE
Context window262K tokens
Size960.3 GB
PrecisionBF16
ArchitectureQwen3MoeForCausalLM
LicenseAPACHE-2.0
Downloads58.2K
Likes1.4K

Can you run it?

Needs a multi-GPU server — about 291.1 GB at 4-bit.

  • BF16 (as published)

    Multi-node cluster

    963.4 GB
  • 8-bit

    8×H100 80 GB node

    511.9 GB
  • 4-bit

    4×H100 80 GB · 512 GB Mac Studio

    291.1 GB
Your machine
GGUF builds
  • Mixture-of-experts: every expert must be loaded, so memory follows total parameters, not the active slice.
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

CodeText / LLM
2 versions — view changelog

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