T4 vs A100: Specs, VRAM & Price
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.
The A100 has 80 GB of VRAM; the T4 has 16 GB.
You can rent both by the hour, no purchase required. A100 from $1.26/GPU/hr; T4 from $0.162/GPU/hr. The T4 is 87% cheaper at the entry rate.
A100
Good for training and inference on models that don't need FP8 kernels
T4
Good for inference workloads on older-generation hardware
Last updated: 2026-11-03 UTCRefreshes every 6 hours
Specs side by side
| Spec | A100 | T4 |
|---|---|---|
| VRAM | 80 GB | 16 GB |
| Memory bandwidth | 2,039 GB/s | 320+ GB/s |
| Architecture | Ampere | Turing |
| Compute capability | 8.0 | 7.5 |
| Precisions in hardware | FP32, FP16, BF16, INT4 | FP32, FP16, INT4 |
| Peak FP16/BF16 tensor TFLOPS | 312 TFLOPS | 65 TFLOPS |
| NVLink / multi-GPU interconnect | NVLink 3, 600 GB/s | – |
| Max board power (TDP) | 400W (SXM) | 70W |
| Form factor | SXM4 | PCIe |
| Regions | 5 | 1 |
On-demand price
| Rate | A100 | T4 |
|---|---|---|
| Lowest per GPU/hr | $1.49/GPU/hr | $0.162/GPU/hr (cheapest overall) |
Which is better for AI: 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 87% at the entry rate ($0.162 vs $1.26/GPU/hr). Worth weighing if the deciding factor above isn't a hard requirement for your job.
Decision criteria
| Memory bandwidth | A100 80GB SXM: 2,039 GB/s HBM2e. T4: "320+ GB/s" GDDR6 (NVIDIA product pages, Aug 2026). |
| Compute precision | A100 supports BF16; T4 (Turing) does not. T4 supports FP16 and INT4-class serving kernels but no BF16 (lib/tools/gpu-capabilities.ts). |
| VRAM | 80 GB (A100) vs 16 GB (T4). T4 ships with 16GB GDDR6 per NVIDIA's page. |
| Availability | 5 region(s) list the A100 vs 1 for the T4. |
| Entry price | $1.26/GPU/hr (A100) vs $0.162/GPU/hr (T4). |
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 $162 on the T4 against $1,264 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.
T4 vs A100: common questions
Is the A100 or the T4 better for AI?
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.
Is the A100 or the T4 cheaper to rent?
On Aquanode's live marketplace the A100 starts at $1.26/GPU/hr (median $1.52/GPU/hr) and the T4 starts at $0.162/GPU/hr (median $0.162/GPU/hr). The T4 is the cheaper of the two at the entry rate, by 87%.
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 $1.26/GPU/hr and the T4 from $0.162/GPU/hr.
How widely available are the A100 and the T4?
The A100 is listed in 5 regions and the T4 in 1 region right now.
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 $1,264 on the A100 and $162 on the T4, a difference of $1,102 for the same runtime. Rates are per GPU per hour and update hourly.
How much VRAM does the A100 have compared to the T4?
The A100 has 80 GB of VRAM; the T4 has 16 GB.
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 $0.162/GPU/hr against the A100's $1.26/GPU/hr on Aquanode, so it's the right call when cost matters more than headroom, not when it doesn't.
Does the A100 or the T4 support NVLink?
The A100 supports NVLink 3, 600 GB/s; the T4 has no dedicated GPU-to-GPU interconnect.
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.
Memory bandwidth, tensor TFLOPS, NVLink/interconnect and max board power are the same verified-from-datasheet figures shown on each model's own A100 page and T4 page, which link the primary vendor source for that model. A dash here means Aquanode hasn't verified that figure from a primary source yet, never a guess.
Go further
Check what fits in each card's memory with the A100 VRAM calculator and the T4 VRAM calculator, see vendor-published throughput in the GPU benchmarks and specs table, or browse every model by generation in the GPU index.
More A100 comparisons
More T4 comparisons
Related reading: A100 pricing and specs, A100 vs H100, A100 vs V100, and The best GPUs for AI, ranked.
