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

GPT-NeoX 20B on RTX PRO 6000 Blackwell 96GB: Does It Fit, How Fast, What It Costs

GPT-NeoX 20B at FP8 (E4M3) needs 20.0 GB for its weights and 90.9 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
90.9 GB needed / 96 GB available
Decode speed
87.36
tok/s per stream
Aggregate
1048
tok/s @ 8 concurrent
Cost / 1M tokens
$0.3975
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 GB90.9 GB87.3610485.28 s$0.3975✓
2× RTX192 GB90.9 GB148.535642.66 s$0.2338✓
4× RTX384 GB90.9 GB297.0142571.34 s$0.1169✓
8× RTX768 GB90.9 GB594.057029687.0 ms$0.0585✓
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?
4K174.43 GB✓ fits
8K88.86 GB✓ fits
33K235.43 GB✓ fits
66K170.87 GB✓ fits
131K0141.73 GB✗ does not fit
Other GPUs that run GPT-NeoX 20B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×14257$0.0390
A100 80GB SXM42×3978$0.1676
H100 SXM5 80GB2×6663$0.2084
AMD MI300X 192GB1×3101$0.2240
L40S 48GB2×1718$0.2263
AMD MI325X 288GB1×3510$0.2770
Frequently asked questions

Can GPT-NeoX 20B run on RTX PRO 6000 Blackwell 96GB?

Yes. GPT-NeoX 20B at FP8 (E4M3) needs 90.9 GB including the KV cache, and RTX PRO 6000 Blackwell 96GB has 96 GB — so it fits on a single GPU.

How fast is GPT-NeoX 20B on RTX PRO 6000 Blackwell 96GB?

87.36 tokens/sec per stream and 1048 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 5.28 s, and inter-token latency is 11.4 ms.

What does GPT-NeoX 20B on RTX PRO 6000 Blackwell 96GB cost per million tokens?

$0.3975 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 GPT-NeoX 20B need on RTX PRO 6000 Blackwell 96GB?

20.0 GB for the weights at FP8 (E4M3), plus 70.9 GB of KV cache for 8 concurrent requests at 8K context — 90.9 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is RTX PRO 6000 Blackwell 96GB the right choice for GPT-NeoX 20B?

It works. Compare $0.3975 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.0292, and the fastest is 4× Cerebras CS-3 (WSE-3) at 159120 tok/s.

Adjust the workload yourself

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

Open in calculator