The RTX 6000 Ada rents for 60% less per hour today — $0.82 against $2.05 — with 48 GB against 96 GB of memory.
Prices collected 2026-09-18 · 9 providers price both
Index median per GPU-hour, on-demand, per snapshot.
| RTX PRO 6000 Blackwell | RTX 6000 Ada | |
|---|---|---|
| Median rental, per GPU-hour | $2.05 | $0.82 |
| Cheapest listing | $0.80 | $0.63 |
| Per month at 720 h | $1,472 | $587 |
| Providers pricing it | 24 | 10 |
| Memory | 96 GB GDDR7 | 48 GB GDDR6 |
| Memory bandwidth | 1,792 GB/s | 960 GB/s |
| GB of memory per $/hr | 46.9 | 58.9 |
| Architecture | Blackwell | Ada Lovelace |
| Class | Workstation | Workstation |
| Released | 2025-04 | 2022-12 |
The cleanest comparison: 9 providers price both cards, so the difference is the GPU and nothing else. The RTX PRO 6000 Blackwell is cheaper at 0 of them.
| Provider | RTX PRO 6000 Blackwell | RTX 6000 Ada | RTX 6000 Ada premium |
|---|---|---|---|
| $1.47 | $0.70 | -53% | |
| $1.69 | $0.74 | -56% | |
| $1.84 | $0.65 | -65% | |
| $1.90 | $1.10 | -42% | |
| $2.14 | $0.84 | -61% | |
| $2.19 | $0.79 | -64% | |
| $2.24 | $1.02 | -54% | |
| $2.27 | $0.78 | -66% | |
| $2.41 | $1.07 | -56% |
Weights + KV cache at 8K context + overhead against 90% of each card's memory. Where a model needs more than one card the cell says how many and prices the set at today's median. $/M tokens is the hourly median divided by estimated single-stream output, from memory bandwidth — an estimate for ranking, not a benchmark.
| Model | Bits | RTX PRO 6000 Blackwell | RTX 6000 Ada |
|---|---|---|---|
| Kimi K3 | 4-bit | 19× GPU$38.85/hr | 37× GPU$30.15/hr |
| Kimi K3 | 16-bit | 65× GPU$132.92/hr | 130× GPU$105.95/hr |
| DeepSeek V4.1-Flash | 4-bit | 4× GPU$8.18/hr | 8× GPU$6.52/hr |
| DeepSeek V4.1-Flash | 16-bit | 13× GPU$26.59/hr | 26× GPU$21.19/hr |
| Llama 4 Maverick | 4-bit | 3× GPU$6.14/hr | 6× GPU$4.89/hr |
| Llama 4 Maverick | 16-bit | 10× GPU$20.45/hr | 19× GPU$15.49/hr |
| gpt-oss-120b | 4-bit | ✓ 67.9 GB~500 tok/s · $1.14/M | 2× GPU$1.63/hr |
| gpt-oss-120b | 16-bit | 3× GPU$6.14/hr | 6× GPU$4.89/hr |
| Llama 3.1 70B | 4-bit | ✓ 44.5 GB~36 tok/s · $15.78/M | 2× GPU$1.63/hr |
| Llama 3.1 70B | 16-bit | 2× GPU$4.09/hr | 4× GPU$3.26/hr |
| Gemma 4 31B | 4-bit | ✓ 21.2 GB~82 tok/s · $6.93/M | ✓ 21.2 GB~44 tok/s · $5.15/M |
| Gemma 4 31B | 16-bit | ✓ 65.7 GB~23 tok/s · $24.7/M | 2× GPU$1.63/hr |
| Qwen3 Coder 30B-A3B | 4-bit | ✓ 19 GB~772 tok/s · $0.74/M | ✓ 19 GB~414 tok/s · $0.55/M |
| Qwen3 Coder 30B-A3B | 16-bit | ✓ 62.9 GB~217 tok/s · $2.62/M | 2× GPU$1.63/hr |
| Qwen3.8 27B | 4-bit | ✓ 18.7 GB~94 tok/s · $6.04/M | ✓ 18.7 GB~51 tok/s · $4.44/M |
| Qwen3.8 27B | 16-bit | ✓ 57.6 GB~27 tok/s · $21.04/M | 2× GPU$1.63/hr |
| gpt-oss-20b | 4-bit | ✓ 13.7 GB~708 tok/s · $0.8/M | ✓ 13.7 GB~379 tok/s · $0.6/M |
| gpt-oss-20b | 16-bit | ✓ 43.9 GB~199 tok/s · $2.85/M | 2× GPU$1.63/hr |
| Llama 3.1 8B | 4-bit | ✓ 6.9 GB~319 tok/s · $1.78/M | ✓ 6.9 GB~171 tok/s · $1.32/M |
| Llama 3.1 8B | 16-bit | ✓ 18.4 GB~90 tok/s · $6.31/M | ✓ 18.4 GB~48 tok/s · $4.72/M |
Hours of renting at today's median that add up to the card's approximate list price. List prices are typical quoted figures, not tracked, and do not include the server, power or the person to run it — so the break-even is a floor, not a verdict.
On 2026-09-18 the RTX PRO 6000 Blackwell has a market median of $2.04 per GPU-hour across 24 providers and the RTX 6000 Ada $0.81 across 10, so the RTX 6000 Ada is 60% cheaper per hour. Among the 9 providers that price both, the RTX PRO 6000 Blackwell is cheaper at 0 and the RTX 6000 Ada at 9. Per hour is only half the answer — the table below prices a whole model on each.
At 4-bit, Llama 3.1 70B needs about 44.5 GB. On the RTX PRO 6000 Blackwell that is one card at $2.05/hr; on the RTX 6000 Ada 2 cards at $1.63/hr.
96 GB GDDR7 at 1,792 GB/s (Blackwell) against 48 GB GDDR6 at 960 GB/s (Ada Lovelace). Memory decides what fits; bandwidth decides how fast it generates, because each token streams the active weights once. Compute matters for prompt processing and training, not for how fast text appears.