Sixteen gigabytes of VRAM is the threshold where Flux.1 stops fighting its hardware and starts performing as intended. The RTX 4060 Ti is the first card in the GigaGPU range that loads the full Flux.1 model without resorting to aggressive quantisation or CPU offloading, and the difference in stability and usability is substantial. We tested it on a GigaGPU dedicated server.
Benchmark Data
| Metric | Value |
|---|---|
| Iterations/sec | 0.48 it/s |
| Seconds per image | 41.67 sec (20 steps) |
| Images per minute | 1.44 |
| Resolution | 1024×1024 |
| Sampler | Euler a / DPM++ 2M Karras |
| Performance rating | Acceptable |
20-step, 1024×1024, FP16, batch size 1. Roughly 42 seconds per image — not fast, but meaningfully quicker than the 4060 (57s) and far more stable. The consistent timing matters for automated pipelines where predictable throughput is essential.
VRAM: Finally Enough
| Component | VRAM |
|---|---|
| Model weights | 12.0 GB |
| Sampling buffer | ~2.4 GB |
| Total RTX 4060 Ti VRAM | 16 GB |
| Free headroom | ~4.0 GB |
Four gigabytes of free headroom changes the experience. You can load a ControlNet adapter alongside the base model, experiment with basic LoRA modifications, and generate at slightly above standard resolution without immediately hitting OOM. This is the entry point for Flux.1 as a practical creative tool rather than a technical experiment.
What It Costs
| Cost Metric | Value |
|---|---|
| Server cost | £0.50/hr (£99/mo) |
| Cost per 1K images | £5.79 |
| Images per £1 | 173 |
£5.79 per thousand images with full model quality (no quantisation-induced artefacts). The 4060 (£5.56/K) is nominally cheaper per image, but it runs a degraded FP8 version that misses some of Flux.1’s quality advantage. When you factor in the reliability and wider workflow support the 4060 Ti provides, the extra £30/mo is an easy justification. For high-throughput scenarios, our GPU comparison for image gen shows where the bigger cards pull ahead.
Our Verdict
The RTX 4060 Ti is the minimum-viable Flux.1 card for serious work. It runs the model at full precision with enough headroom for basic ComfyUI pipelines, ControlNet workflows, and LoRA experimentation. Production-scale Flux.1 — multiple images per minute, batch processing, high-res outputs — requires stepping up to the RTX 3090 or higher. But for small teams, freelance creatives, and product developers validating Flux.1 integration, the 4060 Ti delivers.
Get going:
docker run --gpus all -p 8188:8188 ghcr.io/ai-dock/comfyui:latestDeep dive: Flux.1 hosting guide. More: SDXL hosting, best GPU for image gen, all benchmarks.
Flux.1 Without Compromises — RTX 4060 Ti
Full FP16, 4 GB headroom, £99/mo. UK datacentre with root access.
Order 4060 Ti Server
