NVIDIA96 GB VRAM1,792 GB/s$1.5/hr

Qwen 2.5-VL 72B (VLM) on RTX PRO 6000 Blackwell 96GB: Does It Fit, How Fast, What It Costs

Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 72.0 GB for its weights and 93.5 GB in total at 8K context with 8 concurrent users. That means it fits on a single RTX PRO 6000 Blackwell 96GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
93.5 GB needed / 96 GB available
Decode speed
24.27
tok/s per stream
Aggregate
291.2
tok/s @ 8 concurrent
Cost / 1M tokens
$1.43
1× RTX PRO 6000 Blackwell 96GB
What changes as you add RTX PRO 6000 Blackwell 96GBs
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× RTX96 GB93.5 GB24.27291.218.95 s$1.43✓
2× RTX192 GB93.5 GB41.25990.19.49 s$0.8417✓
4× RTX384 GB93.5 GB82.5139604.76 s$0.4208✓
8× RTX768 GB93.5 GB165.0158412.40 s$0.2104✓
Concurrency vs context length
On 1× RTX PRO 6000 Blackwell 96GB 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?
4K171.34 GB✓ fits
8K82.68 GB✓ fits
33K210.74 GB✓ fits
66K121.47 GB✓ fits
131K042.95 GB✗ does not fit
Other GPUs that run Qwen 2.5-VL 72B (VLM)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×3960$0.1403
A100 80GB SXM42×1105$0.6033
H100 SXM5 80GB2×1851$0.7504
AMD MI300X 192GB1×861.3$0.8063
L40S 48GB2×477.4$0.8147
AMD MI325X 288GB1×975.0$0.9972
Frequently asked questions

Can Qwen 2.5-VL 72B (VLM) run on RTX PRO 6000 Blackwell 96GB?

Yes. Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 93.5 GB including the KV cache, and RTX PRO 6000 Blackwell 96GB has 96 GB — so it fits on a single GPU.

How fast is Qwen 2.5-VL 72B (VLM) on RTX PRO 6000 Blackwell 96GB?

24.27 tokens/sec per stream and 291.2 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 18.95 s, and inter-token latency is 41.2 ms.

What does Qwen 2.5-VL 72B (VLM) on RTX PRO 6000 Blackwell 96GB cost per million tokens?

$1.43 per 1M output tokens at 1× RTX PRO 6000 Blackwell 96GB ($1.50/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 2.5-VL 72B (VLM) need on RTX PRO 6000 Blackwell 96GB?

72.0 GB for the weights at FP8 (E4M3), plus 21.5 GB of KV cache for 8 concurrent requests at 8K context — 93.5 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is RTX PRO 6000 Blackwell 96GB the right choice for Qwen 2.5-VL 72B (VLM)?

It works. Compare $1.43 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.1052, and the fastest is 4× Cerebras CS-3 (WSE-3) at 44200 tok/s.

Adjust the workload yourself

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

Open in calculator