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GPU × use-case guide · Code assistant

Is the A100 40GB PCIe a good GPU for code assistant?

The A100 40GB PCIe is a ampere NVIDIA GPU with 40 GB HBM2e (1555 GB/s), 312 TFLOPS BF16 / 312 TFLOPS FP8, and a 250 W TDP. Code assistant workloads care most about low time-to-first-token and high single-stream tokens/sec, since developers wait on completions in real time. Here's how the A100 40GB PCIe measures up.

VRAM
40 GB
Bandwidth
1555 GB/s
BF16
312 TFLOPS
Cheapest
$0.99/hr

What models fit on a single A100 40GB PCIe?

Weights only, reserving ~25% of the 40 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: Qwen 2.5 14B at BF16, Gemma 2 27B at FP8, Mixtral 8x7B (MoE) at INT4. Bigger models need tensor-parallel across 8 cards.

A100 40GB PCIe for code assistant, specifically

Code assistant is context-heavy, so the KV cache — not the weights — is what fills the 40 GB. On the A100 40GB PCIe you'll trade context length against batch size: long prompts mean fewer concurrent requests. Because it's latency-sensitive, run it at low batch sizes on a fast framework (vLLM ≈ 85% MFU) rather than maximising batch. Size it precisely on the calculator.

A100 40GB PCIe pricing across providers

ProviderOn-demand $/hrReserved $/hr
tensordock$0.99
lambda$1.1
vast_ai$1.1
runpod$1.44

Verdict

At 40 GB, the A100 40GB PCIe is a solid mid-to-high-tier choice for code assistant: single-card up to Qwen 2.5 14B (BF16) or Gemma 2 27B (FP8), and cost-effective at ~$0.99/hr.

See full A100 40GB PCIespecs & pricing, size your model on the calculator, or compare every GPU on the GPU list.