NVIDIA192 GB VRAM8,000 GB/s$6/hr

Phi-3 Mini 3.8B on B200 SXM 192GB: Does It Fit, How Fast, What It Costs

Phi-3 Mini 3.8B at FP16 needs 7.6 GB for its weights and 33.4 GB in total at 8K context with 8 concurrent users. That means it fits on a single B200 SXM 192GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
33.4 GB needed / 192 GB available
Decode speed
684.2
tok/s per stream
Aggregate
8211
tok/s @ 8 concurrent
Cost / 1M tokens
$0.2030
1× B200 SXM 192GB
What changes as you add B200 SXM 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× B200192 GB33.4 GB684.28211114.5 ms$0.2030✓
2× B200384 GB33.4 GB11632791672.4 ms$0.1194✓
4× B200768 GB33.4 GB232611166351.2 ms$0.0597✓
8× B2001536 GB33.4 GB465344665340.6 ms$0.0299✓
Concurrency vs context length
On 1× B200 SXM 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?
4K1141.61 GB✓ fits
8K573.22 GB✓ fits
33K1412.88 GB✓ fits
66K725.77 GB✓ fits
131K351.54 GB✓ fits
Other GPUs that run Phi-3 Mini 3.8B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×6253$0.0444
AMD MI300X 192GB1×5439$0.1277
A100 40GB SXM41×1591$0.1572
AMD MI325X 288GB1×6158$0.1579
A100 80GB SXM41×2053$0.1624
Intel Gaudi 3 128GB1×3387$0.1640
Frequently asked questions

Can Phi-3 Mini 3.8B run on B200 SXM 192GB?

Yes. Phi-3 Mini 3.8B at FP16 needs 33.4 GB including the KV cache, and B200 SXM 192GB has 192 GB — so it fits on a single GPU.

How fast is Phi-3 Mini 3.8B on B200 SXM 192GB?

684.2 tokens/sec per stream and 8211 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 114.5 ms, and inter-token latency is 1.5 ms.

What does Phi-3 Mini 3.8B on B200 SXM 192GB cost per million tokens?

$0.2030 per 1M output tokens at 1× B200 SXM 192GB ($6.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Phi-3 Mini 3.8B need on B200 SXM 192GB?

7.6 GB for the weights at FP16, plus 25.8 GB of KV cache for 8 concurrent requests at 8K context — 33.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is B200 SXM 192GB the right choice for Phi-3 Mini 3.8B?

It works. Compare $0.2030 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0209, and the fastest is 1× Cerebras CS-3 (WSE-3) at 20526 tok/s.

Adjust the workload yourself

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

Open in calculator