NVIDIA48 GB VRAM960 GB/s$0.8/hr

Qwen 3 30B-A3B (MoE) on RTX 6000 Ada 48GB: Does It Fit, How Fast, What It Costs

Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 30.0 GB for its weights and 36.4 GB in total at 8K context with 8 concurrent users. That means it fits on a single RTX 6000 Ada 48GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
36.4 GB needed / 48 GB available
Decode speed
312.0
tok/s per stream
Aggregate
3744
tok/s @ 8 concurrent
Cost / 1M tokens
$0.0594
1× RTX 6000 Ada 48GB
What changes as you add RTX 6000 Ada 48GBs
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× RTX48 GB36.4 GB312.037441.11 s$0.0594✓
2× RTX96 GB36.4 GB530.412730568.5 ms$0.0349✓
4× RTX192 GB36.4 GB106150918299.2 ms$0.0175✓
8× RTX384 GB36.4 GB2122203674164.6 ms$0.008729✓
Concurrency vs context length
On 1× RTX 6000 Ada 48GB at FP8 (E4M3). KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K44412.3 MB✓ fits
8K22824.6 MB✓ fits
33K53.22 GB✓ fits
66K26.44 GB✓ fits
131K112.88 GB✓ fits
Other GPUs that run Qwen 3 30B-A3B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×23762$0.0117
AMD MI300X 192GB1×20670$0.0336
A100 40GB SXM41×6045$0.0414
AMD MI325X 288GB1×23400$0.0415
A100 80GB SXM41×7800$0.0427
Intel Gaudi 3 128GB1×12870$0.0432
Frequently asked questions

Can Qwen 3 30B-A3B (MoE) run on RTX 6000 Ada 48GB?

Yes. Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 36.4 GB including the KV cache, and RTX 6000 Ada 48GB has 48 GB — so it fits on a single GPU.

How fast is Qwen 3 30B-A3B (MoE) on RTX 6000 Ada 48GB?

312.0 tokens/sec per stream and 3744 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 1.11 s, and inter-token latency is 3.2 ms.

What does Qwen 3 30B-A3B (MoE) on RTX 6000 Ada 48GB cost per million tokens?

$0.0594 per 1M output tokens at 1× RTX 6000 Ada 48GB ($0.8000/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 3 30B-A3B (MoE) need on RTX 6000 Ada 48GB?

30.0 GB for the weights at FP8 (E4M3), plus 6.4 GB of KV cache for 8 concurrent requests at 8K context — 36.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is RTX 6000 Ada 48GB the right choice for Qwen 3 30B-A3B (MoE)?

It works. Compare $0.0594 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.005513, and the fastest is 1× Cerebras CS-3 (WSE-3) at 78000 tok/s.

Adjust the workload yourself

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

Open in calculator