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

Qwen2 7B on AMD MI300X 192GB: Does It Fit, How Fast, What It Costs

Qwen2 7B at FP16 needs 15.2 GB for its weights and 19.0 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
19.0 GB needed / 192 GB available
Decode speed
226.0
tok/s per stream
Aggregate
2713
tok/s @ 8 concurrent
Cost / 1M tokens
$0.2560
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 GB19.0 GB226.02713225.5 ms$0.2560✓
2× AMD384 GB19.0 GB384.39223128.1 ms$0.1506✓
4× AMD768 GB19.0 GB768.63689179.1 ms$0.0753✓
8× AMD1536 GB19.0 GB153714756554.5 ms$0.0376✓
Concurrency vs context length
On 1× AMD MI300X 192GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K752240.5 MB✓ fits
8K376481.0 MB✓ fits
33K941.88 GB✓ fits
66K473.76 GB✓ fits
131K237.52 GB✓ fits
Other GPUs that run Qwen2 7B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 3090 24GB1×479.1$0.1450
RTX 5090 32GB1×917.2$0.1514
RTX 4090 24GB1×515.9$0.2154
V100 SXM2 32GB1×460.6$0.3015
A100 40GB SXM41×793.3$0.3151
AMD MI325X 288GB1×3071$0.3166
Frequently asked questions

Can Qwen2 7B run on AMD MI300X 192GB?

Yes. Qwen2 7B at FP16 needs 19.0 GB including the KV cache, and AMD MI300X 192GB has 192 GB — so it fits on a single GPU.

How fast is Qwen2 7B on AMD MI300X 192GB?

226.0 tokens/sec per stream and 2713 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 225.5 ms, and inter-token latency is 4.4 ms.

What does Qwen2 7B on AMD MI300X 192GB cost per million tokens?

$0.2560 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 Qwen2 7B need on AMD MI300X 192GB?

15.2 GB for the weights at FP16, plus 3.8 GB of KV cache for 8 concurrent requests at 8K context — 19.0 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is AMD MI300X 192GB the right choice for Qwen2 7B?

It works. Compare $0.2560 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 2× RTX 3080 10GB at $0.0840, and the fastest is 1× Cerebras CS-3 (WSE-3) at 10236 tok/s.

Adjust the workload yourself

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

Open in calculator