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GPU comparison · Blackwell vs Ada Lovelace
NVIDIA RTX PRO 6000 vs L40S.
Two PCIe data-center cards with ECC, a generation apart. The RTX PRO 6000 Server Edition (Blackwell) has twice the memory (96 GB of GDDR7 against 48 GB of GDDR6), 1.8× the bandwidth and FP4 tensor cores, for only $170 more per GPU per month: it costs less per GB. The L40S (Ada Lovelace) is the lower monthly price for models that fit in 48 GB.
- 96 vs 48 GBGPU memory
- 1.6 vs 0.86 TB/smemory bandwidth
- $959 vs $789per GPU, per month
RTX PRO 6000 vs L40S: which one to rent.
Choose the RTX PRO 6000 if
- Your model needs more than 48 GB per GPU: 96 GB holds about 73B parameters in FP8, so a 70B model fits on one card.
- Token generation speed matters: 1.6 TB/s of memory bandwidth against 864 GB/s.
- You want FP4 inference or the most memory per dollar: $9.99 per GB a month against $16.44.
Choose the L40S if
- Your models fit in 48 GB: about 36B parameters in FP8 or 67B in 4-bit per card.
- You want the lowest monthly price for a data-center card with ECC: $789 against $959.
- You run many replicas of a small model, where the price per card counts more than the memory per card.
RTX PRO 6000 vs L40S specs, side by side.
Figures from NVIDIA’s published specifications, per GPU. Tensor figures are peak dense throughput.
| Per GPU | NVIDIA RTX PRO 6000 | NVIDIA L40S | L40S / RTX PRO 6000 |
|---|---|---|---|
| Architecture | Blackwell | Ada Lovelace | — |
| Form factor | Server Edition, passive PCIe card | Dual-slot PCIe card, passive | — |
| GPU memory | 96 GB GDDR7 with ECC, 512-bit | 48 GB GDDR6 with ECC | 0.5× |
| Memory bandwidth | 1,597 GB/s | 864 GB/s | 0.54× |
| GPU-to-GPU link | None (PCIe 5.0 x16) | None (PCIe Gen4 x16) | — |
| FP4 tensor (dense) | 4.0 PFLOPS | Not supported | — |
| FP8 tensor (dense) | 2,000 TFLOPS | 733 TFLOPS | 0.37× |
| FP16 / BF16 tensor (dense) | 1,000 TFLOPS | 362 TFLOPS | 0.36× |
| FP64 | — | — | — |
| Max power | Up to 600 W, configurable | 350 W | — |
| GPUs per server | 1, 2, 4, 8 | 1, 2, 4, 8 | — |
| Per GPU in our servers | 24 vCPU · 180 GB RAM · 1.92 TB | 12 vCPU · 96 GB RAM · 1 TB | — |
NVIDIA does not say whether its RTX PRO 6000 Server Edition tensor figures use sparsity. Sources: NVIDIA RTX PRO 6000 Server Edition · NVIDIA L40S. Full sheets: RTX PRO 6000 · L40S
RTX PRO 6000 vs L40S rental price.
At CryptGPU, the RTX PRO 6000 rents for $959 and the L40S for $789 per GPU per month, 30% below the market median of public on-demand prices, paid in crypto with no KYC. Hourly figures are the monthly price divided by 730 hours.
| CryptGPU | NVIDIA RTX PRO 6000 | NVIDIA L40S | L40S / RTX PRO 6000 |
|---|---|---|---|
| Price per GPU, per month | $959 | $789 | 0.82× |
| Equivalent per GPU-hour | $1.31 | $1.08 | — |
| Per GB of GPU memory, per month | $9.99 | $16.44 | 1.65× |
| Per PFLOPS of dense FP8, per month | $480 | $1,076 | 2.2× |
| Largest server | 8× · $7,672/mo | 8× · $6,312/mo | — |
| Market median, per GPU | $1,380 | $1,139 | — |
| Below the median | −31% | −31% | — |
Same price per GPU at every server size, no hourly metering. How we compare prices · Configure an RTX PRO 6000 server · Configure a L40S server
Which models fit on each.
Smallest server that holds each model, by precision. Rule of thumb with headroom for the KV cache, 92% of GPU memory usable.
| Model (total parameters) | RTX PRO 6000 · FP8 | L40S · FP8 | RTX PRO 6000 · 4-bit | L40S · 4-bit |
|---|---|---|---|---|
| Qwen3.5-9B | 1× | 1× | 1× | 1× |
| Gemma 4 31B | 1× | 1× | 1× | 1× |
| Llama 3.3 70B | 1× | 2× | 1× | 2× |
| gpt-oss-120b | 2× | 4× | 1× | 2× |
| DeepSeek-V4-Flash | 4× | 8× | 4× | 8× |
| Qwen3.5-397B-A17B | 8× | — | 4× | 8× |
| DeepSeek-R1 (671B) | — | — | 8× | — |
| Kimi K2.6 (1T) | — | — | 8× | — |
FP8 ≈ 1.2 bytes and 4-bit ≈ 0.65 bytes per parameter. — = larger than the biggest server of that GPU. Size another model · How much VRAM does an LLM need?
RTX PRO 6000 vs L40S FAQ.
More on each GPU: NVIDIA RTX PRO 6000 · NVIDIA L40S.
Which is faster for LLM inference?
On paper the RTX PRO 6000: 1.8× the memory bandwidth for token generation and more tensor throughput, although NVIDIA does not say whether its RTX PRO 6000 Server Edition tensor figures use sparsity. Real speed depends on the model and the engine; we do not publish benchmarks.
Which is cheaper per GB of GPU memory?
The RTX PRO 6000: $9.99 per GB per month against $16.44 for the L40S.
Can a 70B model run on one card?
On one RTX PRO 6000, yes in FP8: about 84 GB of the 88 GB usable by our rule. On one L40S, no: even in 4-bit it needs about 46 GB, more than the 44 GB usable; two L40S hold it.
Other GPU comparisons.
- Blackwell vs Blackwell RTX PRO 6000 vs RTX 5090 96 vs 32 GB · 1.6 TB/s vs 1.8 TB/s $959 vs $329/mo per GPU
- Blackwell vs Hopper RTX PRO 6000 vs H100 96 vs 80 GB · 1.6 TB/s vs 3.35 TB/s $959 vs $1,779/mo per GPU
- Ada Lovelace vs Hopper L40S vs H100 48 vs 80 GB · 864 GB/s vs 3.35 TB/s $789 vs $1,779/mo per GPU
Rent the RTX PRO 6000 or the L40S.
Dedicated servers with 1 to 8 GPUs, one monthly price, paid in crypto. Online in under 10 minutes, no KYC.