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Qwen3-Coder 480B-A35B VRAM Requirements

Alibaba, China · Released July 22, 2025

Qwen3-Coder 480B-A35B has 480.1B parameters (35B active per token). In BF16 its weights alone take 894 GiB; quantized to 4-bit, about 270 GiB. Each 32K-token request adds 7.75 GiB of KV cache. Cheapest way to run it today: 7 × RTX 6000 Ada (48 GB) at $3.46 per hour.

Size your own setup in the calculator →

VRAM by precision and context length

Weights plus the KV cache of one request (BF16 cache), in GiB. Add 1 to 3 GiB for the inference engine itself.

Weights formatWeights only+ 8K context+ 32K context+ 128K context+ 256K context
BF16 / FP16894896902925956
FP8 / INT8449451457480511
4-bit (GGUF Q4_K_M)270272278301332

Qwen3-Coder 480B-A35B GGUF files

Exact size of each quantization in unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF (opens in a new tab), and the smallest GPU that runs it with llama.cpp, Ollama or LM Studio and an 8K-token context.

QuantizationFile sizeSmallest GPU
BF16894 GiBMore than 96 GB: see the calculator
UD-Q8_K_XL511 GiBMore than 96 GB: see the calculator
Q8_0475 GiBMore than 96 GB: see the calculator
UD-Q6_K_XL380 GiBMore than 96 GB: see the calculator
Q6_K367 GiBMore than 96 GB: see the calculator
Q5_K_M317 GiBMore than 96 GB: see the calculator
UD-Q5_K_XL317 GiBMore than 96 GB: see the calculator
Q5_K_S308 GiBMore than 96 GB: see the calculator
Q4_1280 GiBMore than 96 GB: see the calculator
Q4_K_M270 GiBMore than 96 GB: see the calculator
UD-Q4_K_XL257 GiBMore than 96 GB: see the calculator
Q4_K_S254 GiBMore than 96 GB: see the calculator
Q4_0253 GiBMore than 96 GB: see the calculator
IQ4_NL252 GiBMore than 96 GB: see the calculator
IQ4_XS243 GiBMore than 96 GB: see the calculator
Q3_K_M214 GiBMore than 96 GB: see the calculator
UD-Q3_K_XL198 GiBMore than 96 GB: see the calculator
Q3_K_S193 GiBMore than 96 GB: see the calculator
UD-IQ3_XXS188 GiBMore than 96 GB: see the calculator
UD-Q2_K_XL168 GiBMore than 96 GB: see the calculator
Q2_K_L163 GiBMore than 96 GB: see the calculator
Q2_K163 GiBMore than 96 GB: see the calculator
UD-IQ1_M139 GiBMore than 96 GB: see the calculator

Read every day from Hugging Face. Split files are added together; vision projectors are left out.

How many GPUs to run Qwen3-Coder 480B-A35B

Fewest GPUs that fit the weights plus one 8K-token request. Data-center GPUs use vLLM (90% of memory usable), the others llama.cpp. Several GPUs split the model with tensor or pipeline parallelism.

GPUBF16 / FP16FP8 / INT84-bit (GGUF Q4_K_M)
GeForce RTX 4090 24 GB48 (several servers)24 (several servers)16 (several servers)
GeForce RTX 5090 32 GB48 (several servers)24 (several servers)16 (several servers)
RTX PRO 6000 Blackwell 96 GB16 (several servers)64
Mac M5 Max 128 GB 96 GB usable16 (several servers)64
NVIDIA H100 80 GB16 (several servers)74
NVIDIA H200 141 GB843
NVIDIA B200 (HGX) 180 GB632

Cheapest way to run Qwen3-Coder 480B-A35B today

For each GPU: the fewest cards that fit Qwen3-Coder 480B-A35B with one 8K-token request, the most faithful weight format at that count, and the cheapest on-demand price (2026-10-10).

On-demand prices from RunPod, Vast.ai, Verda and Azure, checked every hour. Serving many users needs more KV cache, so more memory: size it in the calculator. Some links are affiliate links: StudioTV may earn a commission, at no extra cost to you.

KV cache: how memory grows with context

Architecture: MoE 160 experts · 62 layers, full attention (GQA, 8 KV heads × 128). Every layer keeps keys and values for every token (grouped-query attention), so the cache grows linearly with context. Only 35B parameters are active per token, but all 480B must sit in memory: VRAM depends on the total, speed on the active part.

Context per requestBF16 cacheFP8 cache
8K tokens1.94 GiB0.97 GiB
32K tokens7.75 GiB3.88 GiB
128K tokens31.0 GiB15.5 GiB
256K tokens62.0 GiB31.0 GiB

Qwen3-Coder 480B-A35B VRAM FAQ

How much VRAM does Qwen3-Coder 480B-A35B need?

In BF16 the weights alone take 894 GiB (960 GB). In FP8 that is 449 GiB, and about 270 GiB with 4-bit quantization (Q4_K_M). Each request then adds KV cache: 1.94 GiB at 8K tokens and 7.75 GiB at 32K (BF16 cache).

Can Qwen3-Coder 480B-A35B run on a single RTX 4090 (24 GB)?

No. Even in 4-bit it needs 16 (several servers) RTX 4090s. In 4-bit it needs 4 H100 GPUs.

What is the cheapest way to run Qwen3-Coder 480B-A35B?

On 2026-10-10, the cheapest on-demand setup is 7 × RTX 6000 Ada (48 GB) with 4-bit (GGUF Q4_K_M) weights on Vast.ai, at $3.46 per hour (about $2,524.34 per month). Next: 4 × NVIDIA A100 80GB with 4-bit (GGUF Q4_K_M) weights on Vast.ai, at $3.74 per hour. Sized for one 8K-token request; prices are checked every hour.

How many H100 GPUs does Qwen3-Coder 480B-A35B need?

With one request and an 8K-token context: 16 (several servers) in BF16, 7 in FP8 and 4 in 4-bit (vLLM, 90% of memory usable). Serving many users at once needs more memory for their KV caches: the calculator sizes that for you.

Qwen3-Coder 480B-A35B VRAM badge

For a model card or a README: the 4-bit size and the smallest GPU it fits on, linked to this page. Data as JSON: /api/models/qwen3-coder-480b-a35b.json.

Qwen3-Coder 480B-A35B VRAM badge

[![Qwen3-Coder 480B-A35B VRAM](https://studiotvai.com/badge/qwen3-coder-480b-a35b.svg)](https://studiotvai.com/vram-requirements/qwen3-coder-480b-a35b)

Other models

Same family (coding models): Qwen3-Coder-Next 80B-A3B · Qwen3-Coder 30B-A3B

All models: Llama 3.1 8B · Mistral Small 3.2 24B · Qwen3 32B · Llama 3.3 70B · Llama 3.1 405B · Qwen3.5 4B · Qwen3.5 9B · Qwen3.8 27B · Qwen3.6 35B-A3B · Qwen3.5 122B-A10B · Qwen3.8-Flash-Next · LFM2.5 8B-A1B · LFM2 24B-A2B · Gemma 4 12B · Gemma 4 31B · Gemma 4 26B-A4B · gpt-oss 20B · gpt-oss 120B · Llama 4 Scout 17B-16E · Llama 4 Maverick 17B-128E · Kolibri-1 · Nemotron 3 Nano 30B-A3B · Nemotron 3 Super 120B-A12B · MiniMax M2.7 · DeepSeek R1 · Kimi K2.6 · GLM-5.3 · GLM-5.3-Flash · DeepSeek V4 Flash · DeepSeek V4 Pro · DeepSeek V4.1 Flash · MiMo-V2.6 Pro · MiMo-V2.6 Flash · Kimi K3 · Mistral Large 4 · Qwen3-Coder-Next 80B-A3B · Qwen3-Coder 30B-A3B · DeepSeek V4 Flash Vision Exp · Qwen3.8 2.4T-A95B · Ornith 1.5 397B · Ornith 1.5 35B-A3B · Ornith 1.5 9B · Atria Dawn Preview · Intern S2 397B · Clef · Clef Flash · D1 3B · Humanizer · JEV 27B VL · Mellum2.1 12B-A2.5B · LightOnOCR-3 4B · Spark-X2.5 4B · Agnes-3.0-Qwen

Estimates, not guarantees: computed from the official config.json with the same engine as the LLM VRAM Calculator. Real usage depends on your engine version and settings.