Flux.1 has quickly become the model people reach for when SDXL’s output quality is not quite enough. The problem is that Black Forest Labs’ architecture demands substantially more VRAM than Stable Diffusion. On the RTX 5060 with 8 GB, that means quantisation and tight memory management. We benchmarked the trade-offs on GigaGPU dedicated hardware.
Generation Performance
| Metric | Value |
|---|---|
| Iterations/sec | 0.35 it/s |
| Seconds per image | 57.14 sec (20 steps) |
| Images per minute | 1.05 |
| Resolution | 1024×1024 |
| Sampler | Euler a / DPM++ 2M Karras |
| Performance rating | Acceptable |
20-step generation at 1024×1024, FP16/FP8, batch size 1. About one image per minute. That is a 2.3x improvement over the 3050 and just barely fast enough for interactive creative work where you generate one image, review it, adjust, and generate again.
The VRAM Constraint
| Component | VRAM |
|---|---|
| Model weights | 7.7 GB |
| Sampling buffer | ~1.5 GB |
| Total RTX 5060 VRAM | 8 GB |
| Free headroom | ~0.3 GB |
Flux.1 at FP8 quantisation fills almost the entire 8 GB. The 300 MB of remaining headroom means resolution is locked to 1024×1024 or below, batch size must stay at 1, and ComfyUI will need its memory-efficient attention mode enabled. Any LoRA or ControlNet adapter on top will likely push the card past its limits.
Cost Perspective
| Cost Metric | Value |
|---|---|
| Server cost | £0.35/hr (£99/mo) |
| Cost per 1K images | £5.56 |
| Images per £1 | 180 |
£5.56/K is reasonable for a model of this quality, but the throughput cap of roughly 1,500 images per day limits what you can achieve. SDXL on the same card generates at 2.8 images/min — nearly 3x faster — so the question becomes whether Flux.1’s quality advantage justifies the speed penalty for your specific use case. Our GPU comparison for image generation helps you weigh that decision.
Practical Guidance
The RTX 5060 works for Flux.1 when you need affordable access to the model’s superior prompt adherence and coherent compositions. It is best suited for development, small creative projects, and evaluating whether Flux.1 is the right model before investing in a bigger GPU. For production volumes, start at the 5060 Ti where 16 GB VRAM eliminates the worst memory bottlenecks.
Launch:
docker run --gpus all -p 8188:8188 ghcr.io/ai-dock/comfyui:latestResources: Flux.1 hosting guide, SDXL hosting, benchmark library, benchmark tool.
Flux.1 on the RTX 5060 — Affordable Quality
Black Forest Labs quality at £99/mo. UK datacentre, root access, flat rate.
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