❌Won't fitfp16 · 4K ctx · batch 1
Does L40S run Llama 3.3 70B? No at fp16.
At fp16 precision, Llama 3.3 70B (70 B parameters) needs roughly 142.9 GB of VRAM. L40S only has 48 GB, short by 94.9 GB. INT4 quantization brings it down to 40.9 GB — that fits.
298%
VRAM
Won't fit
Estimated VRAM (fp16)
142.9 GB
of 48 GB on L40S· 94.9 GB short
Tok/sec
6
TFTT
4619ms
Power
270W
Rent on GPUniq marketplace
L40S
Live prices from verified providers · billed hourly, no commitment.
Memory breakdown (fp16)
Quantization comparison
Lower precision = less VRAM with a small quality trade-off. Quality order: FP16 > INT8 > INT4.
| Precision | VRAM | Utilisation | Fits on L40S? |
|---|---|---|---|
| FP16 (full precision) | 142.9 GB | 298% | ❌Won't fit |
| INT8 (8-bit) | 74.9 GB | 156% | ❌Won't fit |
| INT4 / Q4 (4-bit) | 40.9 GB | 85% | ⚠️Tight fit |
Frequently asked
- Can L40S run Llama 3.3 70B?
- Not at fp16 — Llama 3.3 70B needs about 142.9 GB while L40S has 48 GB. It fits at INT4 quantization (40.9 GB) with some accuracy trade-off.
- How much VRAM does Llama 3.3 70B use?
- About 142.9 GB at fp16, 40.9 GB at INT4 (for a 4K context, batch size 1). Longer contexts add to KV cache size; larger batches increase activations.
- What's the fastest way to run Llama 3.3 70B on L40S?
- Use a production inference engine like vLLM, SGLang, or TensorRT-LLM with paged attention — they cut KV cache 2–3× vs the naive estimate and batch multiple requests efficiently. For L40S, enable Flash Attention 2.
- Where can I rent a L40S?
- GPUniq aggregates live L40S offers from verified providers. You can deploy an instance in about a minute and pay hourly with no commitment.
Other GPUs for Llama 3.3 70B
Try it live
Chat with Llama 3.3 70B — no setup
Send a prompt and see how Llama 3.3 70B responds directly in our chat. No installation, no GPU required to test.
Want to tweak sequence length, batch size, or fine-tuning? Open the full calculator →