T4 vs A100: cloud rental cost compared
Short answer: pick the A100 when you're training, fine-tuning, or serving anything beyond light, low-batch inference. Pick the T4 when you're running light inference on a small model and want the lowest possible hourly cost.
You can rent both by the hour, no purchase required. A100 from $0.735/GPU/hr across 7 providers; T4 from $0.158/GPU/hr across 1 provider. The T4 is 79% cheaper at the entry rate.
Specs side by side
Price by provider
Which should you pick: T4 or A100?
The A100 has more than 6x the memory bandwidth of the T4, 2,039 GB/s of HBM2e against the T4's "320+ GB/s" of GDDR6 (NVIDIA product pages, Aug 2026), and adds BF16 tensor cores the T4 doesn't have, so this is a training/serving-scale card against a low-cost inference card, not two peers. Pick the A100 when you're training, fine-tuning, or serving anything beyond light, low-batch inference; pick the T4 when you're running light inference on a small model and want the lowest possible hourly cost. On price the T4 undercuts the A100 by 79% at the entry rate ($0.158 vs $0.735/GPU/hr). Worth weighing if the deciding factor above isn't a hard requirement for your job.
Decision criteria
Pick the A100 when
- You're training, fine-tuning, or serving at meaningful scale
- Your model needs BF16 or more than 16GB of VRAM
- You're bandwidth-bound at any real batch size
Pick the T4 when
- You're running light inference on a small model
- You want the lowest possible hourly cost for a dev/test box
- 16GB of VRAM comfortably fits your model
Price-performance
At list rates, 1,000 GPU-hours costs $158 on the T4 against $735 on the A100. Neither NVIDIA nor Aquanode publishes a workload-normalized $/token or $/epoch figure for this pair, so $/GPU-hour below is the only apples-to-apples number. A faster card can still cost less per finished job even at a higher hourly rate.
A100 vs T4: common questions
Is the A100 or the T4 cheaper to rent?
On Aquanode's live marketplace the A100 starts at $0.735/GPU/hr (median $1.59/GPU/hr across 7 providers) and the T4 starts at $0.158/GPU/hr (median $0.158/GPU/hr across 1 provider). The T4 is the cheaper of the two at the entry rate, by 79%.
What is the difference between the A100 and the T4?
The A100 has 80 GB of VRAM against the T4's 16 GB; the A100 is an Ampere part and the T4 is Turing (compute capability 8.0 vs 7.5); only the A100 supports BF16 compute. On price, the A100 lists from $0.735/GPU/hr and the T4 from $0.158/GPU/hr.
Which cloud providers offer the A100 and the T4?
7 providers list the A100 (Vast.ai, RunPod, Verda, Massed Compute, HyperStack, Jarvislabs and Akash) and 1 list the T4 (Akash), across 7 and 1 region respectively. Both are available from Akash.
How much does 1,000 GPU-hours cost on the A100 vs the T4?
At the lowest rates listed today, 1,000 GPU-hours costs $735 on the A100 and $158 on the T4, a difference of $577 for the same runtime. Rates are per GPU per hour and update hourly.
Is the T4 good enough for LLM inference?
Only for small models. 16GB of VRAM and no BF16 support (NVIDIA, Aug 2026) limits it to lighter inference workloads or INT4-quantized serving. The T4 lists from $0.158/GPU/hr against the A100's $0.735/GPU/hr on Aquanode, so it's the right call when cost matters more than headroom, not when it doesn't.
How this comparison is calculated
Every price is normalized to a per-GPU hourly rate using the same pipeline as every other pricing surface on Aquanode, and only the cheapest qualifying offer per provider is shown. A dash means that provider does not currently list that GPU.
Architecture, compute capability and supported precisions come from each vendor's published datasheet for that generation, not from the marketplace feed. This page regenerates at most once per hour.
