Qwen3 32B VRAM needed and GPU rental cost

Qwen3 32B has 32.8 billion parameters (from the model card). Weights alone take 65.6 GB at FP16. With a 20% allowance for the KV cache and activations, plan for about 79 GB of VRAM at FP16, 39 GB at FP8 and 20 GB at INT4. The cheapest public on-demand way to hold it at FP8 is 1x L40S at Massed Compute, $0.97/hr.

Parameters
32.8B
From the model card
FP16
79 GB
Estimated VRAM
FP8
39 GB
Estimated VRAM
INT4
20 GB
Estimated VRAM

Memory and cost

Estimated VRAM and the cheapest public rental that fits

Each row is a way to run or tune Qwen3 32B. The option is the cheapest on-demand price we track, from rows we rate high or medium confidence, on one node of up to 8 GPUs. Change the precision or hours in the calculator.

Qwen3 32B memory estimate and cheapest rental by mode
ModeEstimated VRAMCheapest public on-demand optionPer month (730 h)Source
Inference, FP16 or BF1679 GB1x A100 at Thunder Compute, $1.09 per hour$795.70Source
Inference, FP8 or INT839 GB1x L40S at Massed Compute, $0.97 per hour$708.10Source
Inference, INT4 (4-bit)20 GB1x L40S at Massed Compute, $0.97 per hour$708.10Source
Fine-tune, LoRA (16-bit base)79 GB1x A100 at Thunder Compute, $1.09 per hour$795.70Source
Fine-tune, QLoRA (4-bit base)20 GB1x L40S at Massed Compute, $0.97 per hour$708.10Source
Fine-tune, full (Adam, mixed precision)630 GB8x A100 at Thunder Compute, $8.72 per hour$6,365.60Source
How to read this. Memory is an estimate, not a benchmark. Multi-GPU setups need fast links between GPUs, and the cheapest row may be a marketplace or PCIe listing. Check the source page before you rent.

Fit by chip

How many GPUs Qwen3 32B needs, by chip

Number of GPUs whose combined memory covers the estimate. Compare the chips on their price pages.

GPUs needed by chip and precision
PrecisionL40S
48 GB
A100
80 GB
H100
80 GB
H200
141 GB
B200
180 GB
MI300X
192 GB
B300
288 GB
FP16 (79 GB)2111111
FP8 (39 GB)1111111
INT4 (20 GB)1111111

FAQ

Qwen3 32B questions

How much VRAM does Qwen3 32B need?

About 79 GB at FP16, 39 GB at FP8 and 20 GB at INT4. These are estimates: parameters times bytes per parameter, plus 20% for the KV cache and activations. Long contexts and large batches need more.

Can Qwen3 32B run on one H100?

An H100 has 80 GB. At FP16 it needs 1 H100 GPUs, at FP8 1 and at INT4 1, by this estimate.

What does it cost to rent a GPU for Qwen3 32B?

At FP8 the cheapest public on-demand option we track is 1x L40S at Massed Compute, $0.97/hr, about $708.10 for a 730-hour month. At INT4 it is 1x L40S at Massed Compute, $0.97/hr. Prices change often, so check the source link on each row. Last checked Nov 9, 2026.

How are these estimates made?

Memory is the parameter count times bytes per parameter (2 for FP16, 1 for FP8, 0.5 for INT4), times 1.2. Fine-tuning uses 2 bytes for LoRA, 0.5 for QLoRA and 16 for full fine-tuning with Adam (2 weights, 2 gradients, 12 optimizer bytes), times 1.2. Real usage depends on the framework, context length and batch size.

Need this capacity?

Tell us the GPU, count, term, region and budget. We reply with the public prices that match and the checks to run before you pay. Free, and we do not sell compute.