--- title: "Rent RTX PRO 6000 Max-Q — $0.980/hr Cloud GPU Pricing (2026) | PowerGPU" description: "Rent the RTX PRO 6000 Max-Q (96 GB GDDR7) from $0.490/hr interruptible or $0.980/hr on-demand — fixed, ≥30% below market. 74 GPUs in 6 regions, per-second billing." url: https://powergpu.ai/gpu/rtx-pro-6000-max-q last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Workstation · Blackwell · launched 2025 · prices checked 2026-09-14 # Rent NVIDIA RTX PRO 6000 Max-Q — 96 GB, $0.980/hr on-demand - VRAM 96 GB GDDR7 - FP16 tensor 420 TFLOPS - PowerScore 296 RTX 3090 = 100 - Configs 1–8× PCIe 5.0 - Online now 74 6 regions [On-demand (guaranteed) $0.980 /GPU-hr ≈ $715/mo · market ~~$1.40~~ (−30%)](https://cloud.powergpu.ai/?gpu=rtx-pro-6000-max-q) [Interruptible $0.490 /GPU-hr flat −50% · pausable, disk kept](https://cloud.powergpu.ai/?gpu=rtx-pro-6000-max-q&type=spot) [Reserved 3 mo $0.637 /GPU-hr −35% · capacity held for you](https://powergpu.ai/products/reserved) Billed per second, price locked at deploy. Storage $0.08/GB/mo · bandwidth $0.01/GB — [the whole fee schedule](https://powergpu.ai/pricing). Next weekly market re-check: 2026-09-21. Workstation · Blackwell architecture The RTX PRO 6000 Max-Q is the 300 W variant of the Blackwell workstation flagship: the same 96 GB of GDDR7 at roughly half the power, so hosts pack more of them per chassis. Slightly lower clocks, noticeably lower price — the efficient way to rent 96 GB. Workstation silicon with ECC memory and studio-certified drivers. Renderers (Blender, Octane, Redshift), CAD and simulation get the large VRAM they want without paying datacenter-flagship rates — and per-second billing suits render queues perfectly. ## NVIDIA RTX PRO 6000 Max-Q specs: VRAM, TFLOPS, bandwidth - **GPU model**: NVIDIA RTX PRO 6000 Max-Q · **Architecture**: Blackwell (2025) - **VRAM**: 96 GB GDDR7 · **Memory bandwidth**: 1,792 GB/s - **FP16 tensor perf.**: 420 TFLOPS · **FP32 perf.**: — - **CUDA cores**: 24,064 · **TDP**: 300 W - **PowerScore ((RTX 3090 = 100))**: 296 · **PCIe generation**: Gen 5.0 - **Multi-GPU**: 1× – 8× · **Max instance storage**: 8,000 GB NVMe - **Network up to**: 10,000 Mbps · **CUDA**: 12.4 – 13.0 Bandwidth, CUDA cores, TDP and FP32 are public NVIDIA figures; FP16 tensor is the dense (non-sparsity) number. Machine-level values come from live inventory. ## RTX PRO 6000 Max-Q price per hour: on-demand, interruptible, reserved One public rule sets every price on this page: the marketplace median for the RTX PRO 6000 Max-Q ($1.40/hr, snapshot 2026-09-14) × 0.70, rounded down — so on-demand is $0.980, **30% below market**. Interruptible halves it; a 3-month reservation takes another 35% off. | Mode | Per GPU-hour | Per day (24 h) | Per month (730 h) | What you get | | --- | --- | --- | --- | --- | | **On-demand** | $0.980 | $23.52 | $715 | Guaranteed capacity, price locked at deploy, stop anytime | | **Interruptible** | $0.490 | $11.76 | $358 | Flat −50%; may pause under capacity pressure, disk kept, auto-requeue | | **Reserved (3 months)** | $0.637 | $15.29 | $465 | −35% on on-demand, rate locked for the term, capacity held | Per GPU: an 8× machine costs exactly 8× — no multi-GPU premium. Estimate a full month with storage and bandwidth in the [GPU cost calculator](https://powergpu.ai/calculator). ## What you can run on a RTX PRO 6000 Max-Q (96 GB VRAM) With 96 GB of GDDR7, a single card holds a **~32B-parameter LLM in FP16** or up to **~141B parameters quantized to 4-bit**, with room for KV-cache at practical context lengths. Scale to 8× GPUs on one machine for bigger models or bigger batches — the per-GPU price stays $0.980. - One-click template: [Linux Desktop on a RTX PRO 6000 Max-Q](https://powergpu.ai/templates/linux-desktop) - One-click template: [ComfyUI on a RTX PRO 6000 Max-Q](https://powergpu.ai/templates/comfyui) - One-click template: [Ubuntu Desktop VM on a RTX PRO 6000 Max-Q](https://powergpu.ai/templates/ubuntu-desktop-vm) - Sizing help: [LLM VRAM requirements guide](https://powergpu.ai/guides/llm-vram-requirements) ## RTX PRO 6000 Max-Q availability by region 74 × RTX PRO 6000 Max-Q across 7 machines, live from inventory: - Chicago, IL - Seattle, WA - Singapore - Mumbai - Stockholm - Santiago ## RTX PRO 6000 Max-Q vs alternatives: price per TFLOP | GPU | VRAM | FP16 | On-demand | $ / TFLOP-hr | | --- | --- | --- | --- | --- | | **RTX PRO 6000 Max-Q** (this card) | 96 GB | 420 | $0.980 | $2.33‰ | | [RTX PRO 6000 WS](https://powergpu.ai/gpu/rtx-pro-6000-ws) | 96 GB | 505 | $1.040 | $2.06‰ | | [RTX PRO 6000 S](https://powergpu.ai/gpu/rtx-pro-6000-s) | 48 GB | 450 | $1.073 | $2.38‰ | | [RTX PRO 5000](https://powergpu.ai/gpu/rtx-pro-5000) | 32 GB | 280 | $0.560 | $2.00‰ | | [RTX 6000Ada](https://powergpu.ai/gpu/rtx-6000ada) | 48 GB | 364 | $0.467 | $1.28‰ | ‰ = dollars per 1,000 TFLOP-hours of FP16 — a rough value-for-compute yardstick across cards. ## Renting a RTX PRO 6000 Max-Q: frequently asked questions **How much does it cost to rent an NVIDIA RTX PRO 6000 Max-Q per hour?** $0.980 per GPU-hour on-demand — a fixed price set at least 30% below the current market median of $1.40. Interruptible capacity costs $0.490/hr and a 3-month reservation $0.637/hr. Around $715/month if you keep one running non-stop, billed per second. **What can a RTX PRO 6000 Max-Q with 96 GB VRAM run?** In LLM terms, roughly a 32B-parameter model in FP16 or up to ~141B parameters 4-bit quantized on a single card, with context headroom. Multi-GPU instances (up to 8× on current inventory) multiply that; diffusion and rendering workloads fit comfortably at this VRAM class. **Is the RTX PRO 6000 Max-Q available to rent right now?** Yes — 74 GPUs across 7 machines in 6 regions are listed as we render this page. Configurations go from 1× to 8×. Deploy from the console and it is running in about 30 seconds. **How do I deploy a RTX PRO 6000 Max-Q?** Create an account (email + password, no card, no KYC), top up in crypto, open the console, filter by RTX PRO 6000 Max-Q, pick a machine and a template such as PyTorch, vLLM or ComfyUI. The same deploy is one command with the CLI: powergpu launch --gpu rtx-pro-6000-max-q --template pytorch. **Why is the RTX PRO 6000 Max-Q cheaper here than on GPU marketplaces?** We price from the public marketplace median and fix our on-demand rate at least 30% below it, rounded down. The price is re-checked weekly (next check 2026-09-21) and published — no auctions, no per-host roulette, no bidding. --- *About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API. Source: https://powergpu.ai/gpu/rtx-pro-6000-max-q · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt