NVIDIA288 GB VRAM8,000 GB/s$8/hr

OLMo 2 13B on B300 SXM 288GB: Does It Fit, How Fast, What It Costs

OLMo 2 13B at FP16 needs 26.0 GB for its weights and 36.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single B300 SXM 288GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
36.7 GB needed / 288 GB available
Decode speed
200.0
tok/s per stream
Aggregate
2400
tok/s @ 8 concurrent
Cost / 1M tokens
$0.9259
1× B300 SXM 288GB
What changes as you add B300 SXM 288GBs
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× B300288 GB36.7 GB200.02400319.0 ms$0.9259✓
2× B300576 GB36.7 GB340.08160174.9 ms$0.5447✓
4× B3001152 GB36.7 GB680.032640102.5 ms$0.2723✓
8× B3002304 GB36.7 GB136013056066.2 ms$0.1362✓
Concurrency vs context length
On 1× B300 SXM 288GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K390687.2 MB✓ fits
8K1951.34 GB✓ fits
33K485.37 GB✓ fits
66K2410.74 GB✓ fits
131K1221.47 GB✓ fits
Other GPUs that run OLMo 2 13B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×1828$0.1520
AMD MI300X 192GB1×1590$0.4368
A100 40GB SXM41×465.0$0.5376
AMD MI325X 288GB1×1800$0.5401
A100 80GB SXM41×600.0$0.5556
Intel Gaudi 3 128GB1×990.0$0.5612
Frequently asked questions

Can OLMo 2 13B run on B300 SXM 288GB?

Yes. OLMo 2 13B at FP16 needs 36.7 GB including the KV cache, and B300 SXM 288GB has 288 GB — so it fits on a single GPU.

How fast is OLMo 2 13B on B300 SXM 288GB?

200.0 tokens/sec per stream and 2400 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 319.0 ms, and inter-token latency is 5.0 ms.

What does OLMo 2 13B on B300 SXM 288GB cost per million tokens?

$0.9259 per 1M output tokens at 1× B300 SXM 288GB ($8.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does OLMo 2 13B need on B300 SXM 288GB?

26.0 GB for the weights at FP16, plus 10.7 GB of KV cache for 8 concurrent requests at 8K context — 36.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is B300 SXM 288GB the right choice for OLMo 2 13B?

It works. Compare $0.9259 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0717, and the fastest is 1× Cerebras CS-3 (WSE-3) at 6000 tok/s.

Adjust the workload yourself

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

Open in calculator