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

Gemma 2 9B on RTX PRO 6000 Blackwell 96GB: Does It Fit, How Fast, What It Costs

Gemma 2 9B at FP16 needs 18.0 GB for its weights and 40.5 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
40.5 GB needed / 96 GB available
Decode speed
64.71
tok/s per stream
Aggregate
776.5
tok/s @ 8 concurrent
Cost / 1M tokens
$0.5366
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 GB40.5 GB64.71776.52.40 s$0.5366✓
2× RTX192 GB40.5 GB110.026401.22 s$0.3156✓
4× RTX384 GB40.5 GB220.010561624.4 ms$0.1578✓
8× RTX768 GB40.5 GB440.042243327.2 ms$0.0789✓
Concurrency vs context length
On 1× RTX PRO 6000 Blackwell 96GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K551.41 GB✓ fits
8K272.82 GB✓ fits
33K611.27 GB✓ fits
66K322.55 GB✓ fits
131K145.10 GB✓ fits
Other GPUs that run Gemma 2 9B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×2640$0.1052
AMD MI300X 192GB1×2297$0.3024
AMD MI325X 288GB1×2600$0.3739
A100 80GB SXM41×866.7$0.3846
Intel Gaudi 3 128GB1×1430$0.3885
H100 SXM5 80GB1×1452$0.4784
Frequently asked questions

Can Gemma 2 9B run on RTX PRO 6000 Blackwell 96GB?

Yes. Gemma 2 9B at FP16 needs 40.5 GB including the KV cache, and RTX PRO 6000 Blackwell 96GB has 96 GB — so it fits on a single GPU.

How fast is Gemma 2 9B on RTX PRO 6000 Blackwell 96GB?

64.71 tokens/sec per stream and 776.5 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 2.40 s, and inter-token latency is 15.5 ms.

What does Gemma 2 9B on RTX PRO 6000 Blackwell 96GB cost per million tokens?

$0.5366 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 Gemma 2 9B need on RTX PRO 6000 Blackwell 96GB?

18.0 GB for the weights at FP16, plus 22.5 GB of KV cache for 8 concurrent requests at 8K context — 40.5 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is RTX PRO 6000 Blackwell 96GB the right choice for Gemma 2 9B?

It works. Compare $0.5366 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.0248, and the fastest is 8× RTX 3080 10GB at 17916 tok/s.

Adjust the workload yourself

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

Open in calculator