--- title: "Rent RTX A6000 — $0.281/hr Cloud GPU Pricing (2026) | PowerGPU" description: "Rent the RTX A6000 (48 GB GDDR6) from $0.140/hr interruptible or $0.281/hr on-demand — fixed, ≥30% below market. 12 GPUs in 5 regions, per-second billing." url: https://powergpu.ai/gpu/rtx-a6000 last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Workstation · Ampere · launched 2020 · prices checked 2026-09-14 # Rent NVIDIA RTX A6000 — 48 GB, $0.281/hr on-demand - VRAM 48 GB GDDR6 - FP16 tensor 155 TFLOPS - PowerScore 109 RTX 3090 = 100 - Configs 1–4× PCIe 4.0 - Online now 12 5 regions [On-demand (guaranteed) $0.281 /GPU-hr ≈ $205/mo · market ~~$0.40~~ (−30%)](https://cloud.powergpu.ai/?gpu=rtx-a6000) [Interruptible $0.140 /GPU-hr flat −50% · pausable, disk kept](https://cloud.powergpu.ai/?gpu=rtx-a6000&type=spot) [Reserved 3 mo $0.182 /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 · Ampere architecture The RTX A6000 is the Ampere workstation flagship: 48 GB GDDR6 with ECC, 10,752 CUDA cores, NVLink bridge support, 300 W. It is the cheapest 48 GB card on the sheet — ideal for 32B-class inference, LoRA training and render jobs that outgrow 24 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 A6000 specs: VRAM, TFLOPS, bandwidth - **GPU model**: NVIDIA RTX A6000 · **Architecture**: Ampere (2020) - **VRAM**: 48 GB GDDR6 · **Memory bandwidth**: 768 GB/s - **FP16 tensor perf.**: 155 TFLOPS · **FP32 perf.**: 38.7 TFLOPS - **CUDA cores**: 10,752 · **TDP**: 300 W - **PowerScore ((RTX 3090 = 100))**: 109 · **PCIe generation**: Gen 4.0 - **Multi-GPU**: 1× – 4× · **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 A6000 price per hour: on-demand, interruptible, reserved One public rule sets every price on this page: the marketplace median for the RTX A6000 ($0.40/hr, snapshot 2026-09-14) × 0.70, rounded down — so on-demand is $0.281, **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** | $0.281 | $6.74 | $205 | Guaranteed capacity, price locked at deploy, stop anytime | | **Interruptible** | $0.140 | $3.36 | $102 | Flat −50%; may pause under capacity pressure, disk kept, auto-requeue | | **Reserved (3 months)** | $0.182 | $4.37 | $133 | −35% on on-demand, rate locked for the term, capacity held | Per GPU: an 4× machine costs exactly 4× — 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 A6000 (48 GB VRAM) With 48 GB of GDDR6, a single card holds a **~14B-parameter LLM in FP16** or up to **~72B parameters quantized to 4-bit**, with room for KV-cache at practical context lengths. Scale to 4× GPUs on one machine for bigger models or bigger batches — the per-GPU price stays $0.281. - One-click template: [Linux Desktop on a RTX A6000](https://powergpu.ai/templates/linux-desktop) - One-click template: [ComfyUI on a RTX A6000](https://powergpu.ai/templates/comfyui) - One-click template: [Ubuntu Desktop VM on a RTX A6000](https://powergpu.ai/templates/ubuntu-desktop-vm) - Sizing help: [LLM VRAM requirements guide](https://powergpu.ai/guides/llm-vram-requirements) ## RTX A6000 availability by region 12 × RTX A6000 across 5 machines, live from inventory: - Miami, FL - Chicago, IL - Osaka - New York, NY - Ashburn, VA ## RTX A6000 vs alternatives: price per TFLOP | GPU | VRAM | FP16 | On-demand | $ / TFLOP-hr | | --- | --- | --- | --- | --- | | **RTX A6000** (this card) | 48 GB | 155 | $0.281 | $1.81‰ | | [RTX 4500Ada](https://powergpu.ai/gpu/rtx-4500ada) | 24 GB | 72 | $0.280 | $3.89‰ | | [RTX PRO 4500](https://powergpu.ai/gpu/rtx-pro-4500) | 24 GB | 200 | $0.273 | $1.37‰ | | [RTX 5000Ada](https://powergpu.ai/gpu/rtx-5000ada) | 32 GB | 190 | $0.369 | $1.94‰ | | [RTX PRO 4000](https://powergpu.ai/gpu/rtx-pro-4000) | 20 GB | 150 | $0.183 | $1.22‰ | ‰ = dollars per 1,000 TFLOP-hours of FP16 — a rough value-for-compute yardstick across cards. - [RTX 6000Ada vs RTX A6000](https://powergpu.ai/compare/rtx-6000ada-vs-rtx-a6000) — specs, price per hour, which to rent - [RTX A6000 vs RTX 4090](https://powergpu.ai/compare/rtx-a6000-vs-rtx-4090) — specs, price per hour, which to rent - [All GPU comparisons](https://powergpu.ai/compare) ## Renting a RTX A6000: frequently asked questions **How much does it cost to rent an NVIDIA RTX A6000 per hour?** $0.281 per GPU-hour on-demand — a fixed price set at least 30% below the current market median of $0.40. Interruptible capacity costs $0.140/hr and a 3-month reservation $0.182/hr. Around $205/month if you keep one running non-stop, billed per second. **What can a RTX A6000 with 48 GB VRAM run?** In LLM terms, roughly a 14B-parameter model in FP16 or up to ~72B parameters 4-bit quantized on a single card, with context headroom. Multi-GPU instances (up to 4× on current inventory) multiply that; diffusion and rendering workloads fit comfortably at this VRAM class. **Is the RTX A6000 available to rent right now?** Yes — 12 GPUs across 5 machines in 5 regions are listed as we render this page. Configurations go from 1× to 4×. Deploy from the console and it is running in about 30 seconds. **How do I deploy a RTX A6000?** Create an account (email + password, no card, no KYC), top up in crypto, open the console, filter by RTX A6000, 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-a6000 --template pytorch. **Why is the RTX A6000 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-a6000 · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt