NVIDIA A100 vs. RTX 4090: Which GPU Offers Better Value for Fine-Tuning?

Quick answer: If your model fits in 24 GB and you already own a desktop, a 4090 is great. The moment you need more memory, multi-GPU scale-out, or you’d rather avoid a $2 K+ hardware bill, rent an A100 (40 GB at $0.57/hr or 80 GB at $0.78/hr on Thunder Compute) and get to work immediately.

Spec sheet at a glance

Why VRAM rules fine-tuning

Fine-tuning GPT-style models is mostly a memory problem. A single 30 B-parameter model needs ~ 60–65 GB just to load with 8-bit weights; mixed precision or LoRA adapters push that higher. The A100 80 GB handles this on one card, or you can shard across multiple A100s via NVLink. With only 24 GB, a 4090 forces heavy checkpointing, CPU off-load, or model downsizing; slowing iteration and complicating your codebase.

Raw speed vs. usable speed

Benchmarks that include I/O and optimizer states show full fine-tunes running 3–4× faster on an A100 than a 4090 once the model actually fits. When the 4090 is faster (e.g., CNNs that fit comfortably in 24 GB), the gap is often < 20 %. For LLMs, memory bottlenecks dominate.

Cost math: buy vs. rent

• Buying a 4090:
  Cash outlay ≈ $2 – 3 K up-front; resale uncertain.

• Buying an A100:
  $7 – 12 K per card; and you still need a dual-socket server plus datacenter-grade power/cooling.

• Renting an A100 on Thunder:
  40 GB = $0.57/hr, 80 GB = $0.78/hr. At ~ 350 GPU-hours per month you still spend under the retail price of one 4090—and you can burst to eight A100s when needed, then spin them down.

Use our transparent pricing page (/pricing) to see the exact hourly cost in your region and estimate your break-even point.

When to choose each GPU

Try it yourself: $20 on us

Ready to see how much larger a model you can fine-tune with an A100? Spin up a GPU in 60 seconds and get $20 of free credit at www.thundercompute.com. No commitments—just cheap, on-demand horsepower for your next experiment.

FAQ

Is the 4090 “overkill” for most AI tasks?
Not if your model fits in 24 GB. But if you need more VRAM sometimes, renting an A100 when you need it is cheaper than owning both.

How many A100s can I chain together on Thunder?
Up to eight in a single node with NVLink, or scale horizontally with our high-bandwidth fabric.

Can I start small and scale?
Yes! Begin with one A100 40 GB, snapshot your disk, then relaunch on a larger multi-GPU node when your project grows.

Still choosing? Test-drive an A100 today and keep your experiments flowing—without melting your credit card.