NVIDIA80 GB VRAM2,000 GB/s$1.2/hr

Mixtral 8x7B (MoE) on A100 80GB SXM4: Does It Fit, How Fast, What It Costs

Mixtral 8x7B (MoE) at FP8 (E4M3) needs 46.7 GB for its weights and 55.3 GB in total at 8K context with 8 concurrent users. That means it fits on a single A100 80GB SXM4. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
55.3 GB needed / 80 GB available
Decode speed
151.2
tok/s per stream
Aggregate
1814
tok/s @ 8 concurrent
Cost / 1M tokens
$0.1838
1× A100 80GB SXM4
What changes as you add A100 80GB SXM4s
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× A10080 GB55.3 GB151.218141.39 s$0.1838✓
2× A100160 GB55.3 GB257.06167711.3 ms$0.1081✓
4× A100320 GB55.3 GB514.024670370.7 ms$0.0540✓
8× A100640 GB55.3 GB102898679200.3 ms$0.0270✓
Concurrency vs context length
On 1× A100 80GB SXM4 at FP8 (E4M3). KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K62549.8 MB✓ fits
8K311.07 GB✓ fits
33K74.29 GB✓ fits
66K38.59 GB✓ fits
131K117.18 GB✓ fits
Other GPUs that run Mixtral 8x7B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×5526$0.0503
AMD MI300X 192GB1×4807$0.1445
L40S 48GB2×2664$0.1460
AMD MI325X 288GB1×5442$0.1787
Intel Gaudi 3 128GB1×2993$0.1856
H100 SXM5 80GB1×3038$0.2286
Frequently asked questions

Can Mixtral 8x7B (MoE) run on A100 80GB SXM4?

Yes. Mixtral 8x7B (MoE) at FP8 (E4M3) needs 55.3 GB including the KV cache, and A100 80GB SXM4 has 80 GB — so it fits on a single GPU.

How fast is Mixtral 8x7B (MoE) on A100 80GB SXM4?

151.2 tokens/sec per stream and 1814 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 1.39 s, and inter-token latency is 6.6 ms.

What does Mixtral 8x7B (MoE) on A100 80GB SXM4 cost per million tokens?

$0.1838 per 1M output tokens at 1× A100 80GB SXM4 ($1.20/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Mixtral 8x7B (MoE) need on A100 80GB SXM4?

46.7 GB for the weights at FP8 (E4M3), plus 8.6 GB of KV cache for 8 concurrent requests at 8K context — 55.3 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is A100 80GB SXM4 the right choice for Mixtral 8x7B (MoE)?

It works. Compare $0.1838 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.0119, and the fastest is 2× Cerebras CS-3 (WSE-3) at 61674 tok/s.

Adjust the workload yourself

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

Open in calculator