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

Mixtral 8x22B (MoE) on B300 SXM 288GB: Does It Fit, How Fast, What It Costs

Mixtral 8x22B (MoE) at AWQ 4-bit needs 77.6 GB for its weights and 92.6 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
92.6 GB needed / 288 GB available
Decode speed
213.3
tok/s per stream
Aggregate
2560
tok/s @ 8 concurrent
Cost / 1M tokens
$0.8681
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 GB92.6 GB213.32560886.7 ms$0.8681✓
2× B300576 GB92.6 GB362.78704458.7 ms$0.5106✓
4× B3001152 GB92.6 GB725.334816244.4 ms$0.2553✓
8× B3002304 GB92.6 GB1451139264137.2 ms$0.1277✓
Concurrency vs context length
On 1× B300 SXM 288GB at AWQ 4-bit. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K223962.1 MB✓ fits
8K1111.88 GB✓ fits
33K277.52 GB✓ fits
66K1315.03 GB✓ fits
131K630.06 GB✓ fits
Other GPUs that run Mixtral 8x22B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×7799$0.0712
A100 80GB SXM42×2176$0.3064
H100 SXM5 80GB2×3645$0.3811
AMD MI300X 192GB1×1696$0.4095
L40S 48GB2×940.0$0.4137
AMD MI325X 288GB1×1920$0.5064
Frequently asked questions

Can Mixtral 8x22B (MoE) run on B300 SXM 288GB?

Yes. Mixtral 8x22B (MoE) at AWQ 4-bit needs 92.6 GB including the KV cache, and B300 SXM 288GB has 288 GB — so it fits on a single GPU.

How fast is Mixtral 8x22B (MoE) on B300 SXM 288GB?

213.3 tokens/sec per stream and 2560 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 886.7 ms, and inter-token latency is 4.7 ms.

What does Mixtral 8x22B (MoE) on B300 SXM 288GB cost per million tokens?

$0.8681 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 Mixtral 8x22B (MoE) need on B300 SXM 288GB?

77.6 GB for the weights at AWQ 4-bit, plus 15.0 GB of KV cache for 8 concurrent requests at 8K context — 92.6 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is B300 SXM 288GB the right choice for Mixtral 8x22B (MoE)?

It works. Compare $0.8681 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.0534, and the fastest is 4× Cerebras CS-3 (WSE-3) at 87040 tok/s.

Adjust the workload yourself

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

Open in calculator