NVIDIA24 GB VRAM600 GB/s$0.36/hr

Qwen 3 4B on A10G 24GB: Does It Fit, How Fast, What It Costs

Qwen 3 4B at FP16 needs 8.0 GB for its weights and 17.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single A10G 24GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
17.7 GB needed / 24 GB available
Decode speed
48.75
tok/s per stream
Aggregate
585.0
tok/s @ 8 concurrent
Cost / 1M tokens
$0.1709
1× A10G 24GB
What changes as you add A10G 24GBs
Tensor-parallel degree vs VRAM, throughput, and cost. Cost scales linearly with GPU count; decode throughput scales near-linearly too, so cost per token stays roughly flat.
GPUsTotal VRAMVRAM neededDecode tok/sAggregate tok/sTTFTCost / 1M tokFits?
1× A10G24 GB17.7 GB48.75585.04.28 s$0.1709✓
2× A10G48 GB17.7 GB82.8819892.16 s$0.1006✓
4× A10G96 GB17.7 GB165.879561.09 s$0.0503✓
8× A10G192 GB17.7 GB331.531824561.5 ms$0.0251✓
Concurrency vs context length
On 1× A10G 24GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K26618.5 MB✓ fits
8K131.21 GB✓ fits
33K34.83 GB✓ fits
66K19.66 GB✓ fits
131K019.33 GB✗ does not fit
Other GPUs that run Qwen 3 4B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 3090 24GB1×912.6$0.0761
RTX 5090 32GB1×1747$0.0795
RTX 4090 24GB1×982.8$0.1131
AMD MI300X 192GB1×5168$0.1344
V100 SXM2 32GB1×877.5$0.1583
A100 40GB SXM41×1511$0.1654
Frequently asked questions

Can Qwen 3 4B run on A10G 24GB?

Yes. Qwen 3 4B at FP16 needs 17.7 GB including the KV cache, and A10G 24GB has 24 GB — so it fits on a single GPU.

How fast is Qwen 3 4B on A10G 24GB?

48.75 tokens/sec per stream and 585.0 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 4.28 s, and inter-token latency is 20.5 ms.

What does Qwen 3 4B on A10G 24GB cost per million tokens?

$0.1709 per 1M output tokens at 1× A10G 24GB ($0.3600/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 3 4B need on A10G 24GB?

8.0 GB for the weights at FP16, plus 9.7 GB of KV cache for 8 concurrent requests at 8K context — 17.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is A10G 24GB the right choice for Qwen 3 4B?

It works. Compare $0.1709 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 2× RTX 3080 10GB at $0.0441, and the fastest is 1× Cerebras CS-3 (WSE-3) at 19500 tok/s.

Adjust the workload yourself

Same formulas, your context length, concurrency, and quantisation.

Open in calculator