NVIDIA40 GB VRAM1,550 GB/s$0.9/hr

Qwen 3 4B on A100 40GB SXM4: 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 A100 40GB SXM4. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
17.7 GB needed / 40 GB available
Decode speed
125.9
tok/s per stream
Aggregate
1511
tok/s @ 8 concurrent
Cost / 1M tokens
$0.1654
1× A100 40GB SXM4
What changes as you add A100 40GB SXM4s
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× A10040 GB17.7 GB125.91511458.0 ms$0.1654✓
2× A10080 GB17.7 GB214.15138244.7 ms$0.0973✓
4× A100160 GB17.7 GB428.220553137.4 ms$0.0487✓
8× A100320 GB17.7 GB856.48221283.7 ms$0.0243✓
Concurrency vs context length
On 1× A100 40GB SXM4 at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K52618.5 MB✓ fits
8K261.21 GB✓ fits
33K64.83 GB✓ fits
66K39.66 GB✓ fits
131K119.33 GB✓ fits
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
AMD MI325X 288GB1×5850$0.1662
Frequently asked questions

Can Qwen 3 4B run on A100 40GB SXM4?

Yes. Qwen 3 4B at FP16 needs 17.7 GB including the KV cache, and A100 40GB SXM4 has 40 GB — so it fits on a single GPU.

How fast is Qwen 3 4B on A100 40GB SXM4?

125.9 tokens/sec per stream and 1511 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 458.0 ms, and inter-token latency is 7.9 ms.

What does Qwen 3 4B on A100 40GB SXM4 cost per million tokens?

$0.1654 per 1M output tokens at 1× A100 40GB SXM4 ($0.9000/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 A100 40GB SXM4?

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 A100 40GB SXM4 the right choice for Qwen 3 4B?

It works. Compare $0.1654 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