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Qwen3-Next-80B-A3B-Instruct-AWQ-4bit GPU Requirements: VRAM & Cheapest GPU

Qwen3-Next-80B-A3B-Instruct-AWQ-4bit has about 83.8B parameters. See exactly how much GPU memory it needs at FP16, INT8, and INT4, and the cheapest GPU to run it, with live hourly pricing from 5+ data center partners.

83.8BParameters
46 GBMin VRAM
$0.82/hrCheapest
< 2 minDeploy
cyankiwi/Qwen3-Next-80B-A3B-Instruct-AWQ-4bit
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83.8B paramstext-generationqwen3_next658.8K downloads64 likesupdated May 6, 2026

To run Qwen3-Next-80B-A3B-Instruct-AWQ-4bit for inference at FP16, you need roughly 183 GB of VRAM. The cheapest fit on Spheron is 2x RTX PRO 6000 96GB at about $1.82/hr. Quantize to INT4 to run it on a smaller, cheaper GPU.

GB VRAM REQUIRED
FP16INFERENCEBATCH 1CTX 4k

Estimated peak VRAM including weights, activations, and KV cache. Add 10% headroom for production traffic.

RANKCONFIGURATIONPER GPUTOTAL $/HR
  • 01
    2× RTX PRO 6000 96GBCHEAPEST
    Blackwell · GDDR7
    $0.91/hr$1.82/hr
  • 02
    1× B200 192GB
    Blackwell · HBM3e
    $2.69/hr$2.69/hr
  • 03
    4× A100 80GB
    Ampere · HBM2e
    $0.82/hr$3.28/hr
  • 04
    1× B300 288GB
    Blackwell Ultra · HBM3e
    $3.32/hr$3.32/hr
  • 05
    2× GH200 96GB
    Grace Hopper · HBM3
    $1.88/hr$3.76/hr

Live pricing aggregated from 5+ data center partners. Per-minute billing, no commitments.

VRAM required to run Qwen3-Next-80B-A3B-Instruct-AWQ-4bit

Estimated peak VRAM at context length 4,096 and batch size 1, including weights, activations, and KV cache. Quantizing to INT8 (Q8) or INT4 (Q4) cuts memory roughly in half and in quarter.

PrecisionInferenceLoRA fine-tuneFull fine-tune
FP16183 GB274 GB731 GB
INT891 GB137 GB365 GB
INT446 GB68 GB183 GB

Cheapest GPU to run Qwen3-Next-80B-A3B-Instruct-AWQ-4bit by precision

FP16
VRAM required183GB

Full precision. Best quality, highest memory.

Cheapest GPU
2x RTX PRO 6000 96GB
Blackwell · GDDR7
$1.82/hr · $0.91/hr/gpu
2x RTX PRO 6000 96GB on Spheron
INT8
VRAM required91GB

8-bit quantized. ~2x smaller, minimal quality loss.

Cheapest GPU
RTX PRO 6000 96GB
Blackwell · GDDR7
$0.91/hr
RTX PRO 6000 96GB on Spheron
INT4
VRAM required46GB

4-bit quantized. ~4x smaller, runs on smaller GPUs.

Cheapest GPU
A100 80GB
Ampere · HBM2e
$0.82/hr
A100 80GB on Spheron

Inference vs fine-tuning Qwen3-Next-80B-A3B-Instruct-AWQ-4bit

InferenceWeights + KV cache
LoRA fine-tune~1.5×+ low-rank adapter
Full fine-tune~4×+ gradients + optimizer state

Inference only holds the model weights plus a KV cache, so it is the cheapest setup. LoRA fine-tuning adds a small adapter and roughly 50% more memory. Full fine-tuning holds gradients and optimizer state on top of the weights, which is about 4x the inference footprint, so it often needs multiple GPUs even when inference fits on one. For Qwen3-Next-80B-A3B-Instruct-AWQ-4bit, an on-demand RTX PRO 6000 96GB instance covers inference and LoRA, while a full fine-tune needs several times that memory and often spans multiple GPUs. Check the live GPU pricing for current rates.

Deployment guideDeploy Qwen 3 step by stepHands-on production setup, GPU configs, and benchmarks for Qwen3-Next-80B-A3B-Instruct-AWQ-4bit.Read guide

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