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

Mistral 7B v0.3 on RTX PRO 6000 Blackwell 96GB: Does It Fit, How Fast, What It Costs

Mistral 7B v0.3 at FP16 needs 14.5 GB for its weights and 23.1 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
23.1 GB needed / 96 GB available
Decode speed
80.44
tok/s per stream
Aggregate
965.3
tok/s @ 8 concurrent
Cost / 1M tokens
$0.4316
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 GB23.1 GB80.44965.31.94 s$0.4316✓
2× RTX192 GB23.1 GB136.83282986.3 ms$0.2539✓
4× RTX384 GB23.1 GB273.513128508.1 ms$0.1270✓
8× RTX768 GB23.1 GB547.052513269.1 ms$0.0635✓
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?
4K151549.8 MB✓ fits
8K751.07 GB✓ fits
33K184.29 GB✓ fits
66K98.59 GB✓ fits
131K417.18 GB✓ fits
Other GPUs that run Mistral 7B v0.3
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 3090 24GB1×504.2$0.1377
RTX 5090 32GB1×965.3$0.1439
RTX 4090 24GB1×543.0$0.2046
AMD MI300X 192GB1×2855$0.2432
V100 SXM2 32GB1×484.8$0.2865
A100 40GB SXM41×834.9$0.2994
Frequently asked questions

Can Mistral 7B v0.3 run on RTX PRO 6000 Blackwell 96GB?

Yes. Mistral 7B v0.3 at FP16 needs 23.1 GB including the KV cache, and RTX PRO 6000 Blackwell 96GB has 96 GB — so it fits on a single GPU.

How fast is Mistral 7B v0.3 on RTX PRO 6000 Blackwell 96GB?

80.44 tokens/sec per stream and 965.3 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 1.94 s, and inter-token latency is 12.4 ms.

What does Mistral 7B v0.3 on RTX PRO 6000 Blackwell 96GB cost per million tokens?

$0.4316 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 Mistral 7B v0.3 need on RTX PRO 6000 Blackwell 96GB?

14.5 GB for the weights at FP16, plus 8.6 GB of KV cache for 8 concurrent requests at 8K context — 23.1 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is RTX PRO 6000 Blackwell 96GB the right choice for Mistral 7B v0.3?

It works. Compare $0.4316 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0399, and the fastest is 1× Cerebras CS-3 (WSE-3) at 10773 tok/s.

Adjust the workload yourself

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

Open in calculator