--- title: "Cheapest cloud GPU for Stable Diffusion & Flux in 2026 ($/image)" description: "What SDXL and Flux actually need, images-per-dollar on eight rentable GPUs, and where paying more per hour costs less per image." url: https://powergpu.ai/guides/cheapest-gpu-for-stable-diffusion last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Guide · Costs & pricing # Cheapest cloud GPU for Stable Diffusion & Flux in 2026 ($/image) What SDXL and Flux actually need, images-per-dollar on eight rentable GPUs, and where paying more per hour costs less per image. 9 min read Published 2026-08-27 Updated 2026-09-03 (prices live from the sheet) TL;DR - For SDXL the RTX 4090 wins images per dollar at $0.163 interruptible, roughly 2.9 seconds per image; for Flux the RTX 5090 leads. - Rank cards by images per dollar, not hourly rate: 3,600 divided by seconds per image divided by hourly price. - Flux dev FP8 needs about 17 GB, so 24 GB cards are the practical floor and 32 GB removes the ceiling. - On PowerGPU cheap hourly cards like the RTX 3060 lose on throughput; keep checkpoints on a volume and stop idle instances. ## The answer table Eight rentable cards, live prices, images per dollar (interruptible rate — image queues pause gracefully): | GPU | $/hr int. | SDXL s/img | SDXL img/$ | Flux s/img | Flux img/$ | | --- | --- | --- | --- | --- | --- | | [RTX 3060](https://powergpu.ai/gpu/rtx-3060) (12 GB) | $0.021 | 11.0 s | **15,584** | 38 s | **4,511** | | [RTX 3090](https://powergpu.ai/gpu/rtx-3090) (24 GB) | $0.054 | 5.6 s | **11,905** | 16 s | **4,167** | | [RTX 4070](https://powergpu.ai/gpu/rtx-4070) (12 GB) | $0.037 | 6.5 s | **14,969** | 21 s | **4,633** | | [RTX 4090](https://powergpu.ai/gpu/rtx-4090) (24 GB) | $0.163 | 2.9 s | **7,616** | 7.5 s | **2,945** | | [RTX 5090](https://powergpu.ai/gpu/rtx-5090) (32 GB) | $0.219 | 2.1 s | **7,828** | 5.2 s | **3,161** | | [RTX A4000](https://powergpu.ai/gpu/rtx-a4000) (16 GB) | $0.035 | 8.9 s | **11,557** | 29 s | **3,547** | | [L40S](https://powergpu.ai/gpu/l40s) (48 GB) | $0.257 | 3.4 s | **4,120** | 9.0 s | **1,556** | | [RTX 5070 Ti](https://powergpu.ai/gpu/rtx-5070-ti) (16 GB) | $0.065 | 4.8 s | **11,538** | 15 s | **3,692** | Timings: community-typical SDXL 1024² @30 steps and Flux dev @20 steps; treat as ±20% and re-run on your workflow. Prices re-render live with every weekly sheet update. ## Method: $/image, not $/hour *the whole method* ``` images_per_dollar = 3600 / seconds_per_image / price_per_hour ``` This single division reorders the whole market. The "cheap" hourly cards at the top of the table lose to the [RTX 4090](https://powergpu.ai/gpu/rtx-4090) the moment throughput enters the equation — and the gap widens on Flux, where small cards spill to system RAM. ## SDXL economics - **Interactive sessions** — an evening of prompting (~3 h) on a 4090: $0.98 on-demand. Use on-demand for sessions: an interruption mid-flow is worth more than the 50%. - **Batches** — queue overnight on interruptible; per the table, roughly 7,616 images per dollar. - **Budget floor** — the 3090 remains the best "always cheap" card: 24 GB means no workflow ever refuses to load. ## Flux economics - **24 GB is the entry ticket** (FP8 + offloaded text encoders). Below that, generation works but throughput collapses — the img/$ column shows the 3060's honest number. - **32 GB removes the ceiling** — full-precision weights, LoRA stacks and upscalers resident: the [5090](https://powergpu.ai/gpu/rtx-5090) leads img/$ despite the highest hourly rate on the table. - **Serving users?** Concurrency changes the criteria — see [serverless endpoints](https://powergpu.ai/products/serverless) with the ComfyUI template. ## Three traps that triple bills 1. **Re-downloading models every session.** 30 GB of checkpoints at every boot is slow and silly. A 120 GB [volume](https://powergpu.ai/docs/volumes) costs $9.60/mo and mounts in seconds. 2. **Idle instances "kept for later".** Stop them — a stopped instance bills only disk. The pause button is the biggest discount on this page. 3. **Benchmarking with someone else's workflow.** Your LoRA count, resolution and sampler move s/image by 3×. Rent two candidates for one hour ($0.766 total) and measure your own pipeline. --- Put the numbers to work Every price in this guide is our live rate — fixed, ≥30% under the market median, billed per second. Deploy the exact setup above from the [console](https://cloud.powergpu.ai/) in about 30 seconds, paid in crypto, no card and no KYC. --- *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/guides/cheapest-gpu-for-stable-diffusion · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt