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

Mistral 7B v0.3 on B300 SXM 288GB: 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 B300 SXM 288GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
23.1 GB needed / 288 GB available
Decode speed
359.1
tok/s per stream
Aggregate
4309
tok/s @ 8 concurrent
Cost / 1M tokens
$0.5157
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 GB23.1 GB359.14309190.9 ms$0.5157✓
2× B300576 GB23.1 GB610.514652110.7 ms$0.3033✓
4× B3001152 GB23.1 GB12215860870.4 ms$0.1517✓
8× B3002304 GB23.1 GB244223443150.2 ms$0.0758✓
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?
4K509549.8 MB✓ fits
8K2541.07 GB✓ fits
33K634.29 GB✓ fits
66K318.59 GB✓ fits
131K1517.18 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 B300 SXM 288GB?

Yes. Mistral 7B v0.3 at FP16 needs 23.1 GB including the KV cache, and B300 SXM 288GB has 288 GB — so it fits on a single GPU.

How fast is Mistral 7B v0.3 on B300 SXM 288GB?

359.1 tokens/sec per stream and 4309 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 190.9 ms, and inter-token latency is 2.8 ms.

What does Mistral 7B v0.3 on B300 SXM 288GB cost per million tokens?

$0.5157 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 Mistral 7B v0.3 need on B300 SXM 288GB?

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 B300 SXM 288GB the right choice for Mistral 7B v0.3?

It works. Compare $0.5157 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