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Qwen · open-weights

Qwen3-Coder 480B-A35B Instruct

Qwen3-Coder 480B-A35B Instruct is an open-weights language model from Qwen, released April 1, 2025. It has 480B parameters (mixture-of-experts, 35B active). The context window is 256K tokens. API price: $1.5 input / $7.5 output per million tokens.

Today, we're announcing Qwen3-Coder, our most agentic code model to date. Qwen3-Coder is available in multiple sizes, but we're excited to introduce its most powerful variant first: Qwen3-Coder-480B-A35B-Instruct.

Check it against your own PC →

Lab
Qwen
Released
April 1, 2025
Weights
Open apache-2.0
Parameters
480B MoE · 35B active
Context
256K
Price / M tokens
$1.5 / $7.5 in / out
Epoch ECI
not yet rated

Can you run Qwen3-Coder 480B-A35B Instruct locally?

Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.

GPU memoryVerdictBest quantVRAMRAMtok/s
6 GB VRAMToo large––––
8 GB VRAMToo large––––
12 GB VRAMToo large––––
16 GB VRAMToo large––––
24 GB VRAMToo large––––
32 GB VRAMToo large––––

Ready-made quantizations on Hugging Face: unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF · bartowski/Qwen_Qwen3-Coder-480B-A35B-Instruct-GGUF · lmstudio-community/Qwen3-Coder-480B-A35B-Instruct-GGUF · unsloth/Qwen3-Coder-480B-A35B-Instruct-1M-GGUF · tachyphylaxis/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF · DevQuasar/Qwen.Qwen3-Coder-480B-A35B-Instruct-GGUF

Benchmark results

Epoch AI has not published results for Qwen3-Coder 480B-A35B Instruct yet. New models are usually evaluated within days to weeks.

Links

Announcement · Hugging Face: Qwen/Qwen3-Coder-480B-A35B-Instruct

More from Qwen

Qwen3.8 Omni Flash · Qwen3.8 Max (0902) · Qwen3.8 Flash · Qwen3.8 Flash Next · Qwen 3.8 27B · Qwen3.8-2.4T-A95B · Qwen 3.8 Max · Qwen3.7 Flash

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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