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GPU × use-case guide · Translation

Is the A100 80GB SXM a good GPU for translation?

The A100 80GB SXM is a ampere NVIDIA GPU with 80 GB HBM2e (2039 GB/s), 312 TFLOPS BF16 / 312 TFLOPS FP8, and a 400 W TDP. Translation workloads care most about high batch throughput and cost efficiency across many short-to-medium requests. Here's how the A100 80GB SXM measures up.

VRAM
80 GB
Bandwidth
2039 GB/s
BF16
312 TFLOPS
Cheapest
$1.69/hr

What models fit on a single A100 80GB SXM?

Weights only, reserving ~25% of the 80 GB for KV cache, activations and fragmentation. ✓ = fits on one card.

ModelBF16FP8INT4
Llama 3.1 8B
Qwen 2.5 14B
Gemma 2 27B
Mixtral 8x7B (MoE)
Llama 3.3 70B
Qwen 2.5 72B
Llama 3.1 405B

Largest single-card fit: Gemma 2 27B at BF16, Mixtral 8x7B (MoE) at FP8, Qwen 2.5 72B at INT4. Bigger models need tensor-parallel across 8 cards.

A100 80GB SXM for translation, specifically

Translation is throughput-bound rather than VRAM-bound, so the A100 80GB SXM's 2039 GB/s of bandwidth and 312 TFLOPS matter more than raw capacity. Because it runs offline, batch aggressively to push tokens-per-dollar down. Size it precisely on the calculator.

A100 80GB SXM pricing across providers

ProviderOn-demand $/hrReserved $/hr
fluidstack$1.69
tensordock$1.79
vast_ai$1.8
lambda$1.99$1.49
coreweave$2.21$1.62
runpod$2.72
aws$3.67$2.39
gcp$3.67$2.48
azure$3.67$2.45

Verdict

With 80 GB, the A100 80GB SXM is a data-center-class card that comfortably handles translation for models up to Gemma 2 27B at full precision on a single card — a strong pick if your budget supports ~$1.69/hr.

See full A100 80GB SXMspecs & pricing, size your model on the calculator, or compare every GPU on the GPU list.