AMD192 GB VRAM5,300 GB/s$2.5/hr

Qwen 2.5-VL 72B (VLM) on AMD MI300X 192GB: 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 AMD MI300X 192GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
93.5 GB needed / 192 GB available
Decode speed
71.77
tok/s per stream
Aggregate
861.3
tok/s @ 8 concurrent
Cost / 1M tokens
$0.8063
1× AMD MI300X 192GB
What changes as you add AMD MI300X 192GBs
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× AMD192 GB93.5 GB71.77861.31.85 s$0.8063✓
2× AMD384 GB93.5 GB122.02928940.8 ms$0.4743✓
4× AMD768 GB93.5 GB244.011713485.4 ms$0.2372✓
8× AMD1536 GB93.5 GB488.046852257.7 ms$0.1186✓
Concurrency vs context length
On 1× AMD MI300X 192GB 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?
4K891.34 GB✓ fits
8K442.68 GB✓ fits
33K1110.74 GB✓ fits
66K521.47 GB✓ fits
131K242.95 GB✓ fits
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
L40S 48GB2×477.4$0.8147
AMD MI325X 288GB1×975.0$0.9972
Intel Gaudi 3 128GB1×536.3$1.04
Frequently asked questions

Can Qwen 2.5-VL 72B (VLM) run on AMD MI300X 192GB?

Yes. Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 93.5 GB including the KV cache, and AMD MI300X 192GB has 192 GB — so it fits on a single GPU.

How fast is Qwen 2.5-VL 72B (VLM) on AMD MI300X 192GB?

71.77 tokens/sec per stream and 861.3 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 1.85 s, and inter-token latency is 13.9 ms.

What does Qwen 2.5-VL 72B (VLM) on AMD MI300X 192GB cost per million tokens?

$0.8063 per 1M output tokens at 1× AMD MI300X 192GB ($2.50/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 AMD MI300X 192GB?

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 AMD MI300X 192GB the right choice for Qwen 2.5-VL 72B (VLM)?

It works. Compare $0.8063 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