
Drop your photo into one of the viral "Ghibli" generators and you get back a pretty character of someone else. Different face, different pose, often behind a subscription or a watermark.
Flux Kontext does the opposite: it repaints your photo instead of inventing a new one – face, pose and composition stay. But here's the catch almost every guide skips: the prompt "Studio Ghibli" alone gives only generic anime – glossy round eyes, no real Ghibli handwriting. The real look comes only with a small, free Kontext LoRA.
This guide shows both – the quick prompt route and the step to real Ghibli. Tested locally on an RTX 3060 with 12 GB of VRAM, free, no cloud required.
Updated: July 2026 · ComfyUI (current) · Flux.1 Kontext Dev as GGUF · LoRA
Kontext-Style/Ghibli_lora
What you'll get:
- Why Kontext keeps your subject – and why the prompt alone still isn't enough
- The free Ghibli LoRA for Kontext – and exactly where the file goes
- The full ComfyUI workflow – with the GGUF trick for 12 GB cards
- The right prompt + the tested settings (LoRA strength, guidance)
- Fine-tuning and fixes when the look drifts
Why Kontext keeps your subject
The key term is image conditioning. Kontext gets your original image not as a vague description but as a fixed reference point (the ReferenceLatent node). It applies the style change to your image – instead of rolling a brand-new picture from a text prompt.
In practice:
- Same face, same pose, same framing – only the painting style changes.
- Not a random anime character, but recognizably you (or your subject).
- You can apply the same look consistently across a whole photo series.
That's half the battle. The other half is the style itself – and that's where it gets interesting.
Why the prompt alone isn't enough
The Flux Kontext base model barely knows "Ghibli" – the studio name is trademark-thin in the training data. Ask it for "Studio Ghibli style" via prompt and you get generic anime: big glossy eyes, garish colors, but not the soft, hand-painted Ghibli handwriting.

The fix is a LoRA – a small add-on file (~350 MB) that teaches the model a specific style. That's exactly what the Kontext-Style project is: a Ghibli LoRA trained specifically for Flux Kontext on paired image data. Free, local, one download – and the look lands.
🔑 Remember: Kontext provides the fidelity (your subject stays), the LoRA provides the real style. Only both together give real Ghibli instead of run-of-the-mill anime.
Requirements
| What | Recommendation |
|---|---|
| Graphics card | NVIDIA with ≥ 8 GB VRAM (tested on RTX 3060/12 GB) |
| Software | ComfyUI (current version) |
| Custom node | ComfyUI-GGUF (for the GGUF loader) |
| Storage | ~ 12 GB (base models) + ~ 350 MB (LoRA) |
💡 Tip: We use the GGUF variant of Flux Kontext (Q4_K_M, ~6.8 GB). GGUF is a compressed format – so a 12-billion-parameter model runs smoothly on a 12 GB card, where the full fp16 version (~24 GB) would be far too large.
⚠️ Warning: ComfyUI Desktop and the portable version do not share models. Put the files in the models folder of the version you actually launch.
Keine starke Grafikkarte? Führe ComfyUI in der Cloud aus.
Flux & SDXL sind speicherhungrig. Statt ~1.800 € für eine eigene Karte mietest du bei RunPod eine 24-GB-GPU ab ca. 0,50 €/Stunde – und zahlst nur, was du nutzt.
Step 1: Install the custom node "ComfyUI-GGUF"
The GGUF loader isn't a default node – it comes via the Manager:
- Start ComfyUI → click Manager on the right.
- Open Custom Nodes Manager → search for
ComfyUI-GGUF→ Install. - Fully restart ComfyUI.
Without this step, the "Unet Loader (GGUF)" node is missing later and the workflow stays red.
Step 2: Place the models and the Ghibli LoRA
Flux Kontext has four parts (main model, two text encoders, VAE). On top comes the Ghibli LoRA – that's the part that makes the real style.
| File | Source | Folder |
|---|---|---|
flux1-kontext-dev-Q4_K_M.gguf | 🤗 QuantStack/FLUX.1-Kontext-dev-GGUF | models/unet/ |
t5xxl_fp8_e4m3fn.safetensors | 🤗 comfyanonymous/flux_text_encoders | models/text_encoders/ |
clip_l.safetensors | 🤗 comfyanonymous/flux_text_encoders | models/clip/ |
ae.safetensors | 🤗 black-forest-labs/FLUX.1-schnell (VAE) | models/vae/ |
Ghibli_lora_weights.safetensors | 🤗 Kontext-Style/Ghibli_lora | models/loras/ |
The folder structure then looks like this:
📁 ComfyUI/
└── 📁 models/
├── 📁 unet/
│ └── flux1-kontext-dev-Q4_K_M.gguf
├── 📁 text_encoders/
│ └── t5xxl_fp8_e4m3fn.safetensors
├── 📁 clip/
│ └── clip_l.safetensors
├── 📁 vae/
│ └── ae.safetensors
└── 📁 loras/
└── Ghibli_lora_weights.safetensors
📌 Note: After copying, restart ComfyUI once, otherwise the models and LoRA won't show up in the dropdowns.
Step 3: Load the workflow – GGUF trick + hook in the LoRA
You build nothing by hand. ComfyUI ships the base workflow as a template:
- Click Workflow → Browse Templates → category Flux → "Flux.1 Kontext Dev (Basic)". The full graph loads automatically.
- GGUF trick for 12 GB cards: delete the "Load Diffusion Model" node. Right-click → Add Node → bootleg → Unet Loader (GGUF) → select
flux1-kontext-dev-Q4_K_M.gguf. - Hook in the LoRA: right-click → Add Node → loaders → LoraLoaderModelOnly. Plug the GGUF loader's MODEL output into the LoRA node, choose
Ghibli_lora_weights.safetensorsthere and setstrength_modelto 1.0. Route the LoRA node's MODEL output on to the KSampler.
Quickly check the remaining loaders:
- DualCLIPLoader →
t5xxl_fp8_e4m3fn+clip_l,type: flux - VAELoader →
ae.safetensors

🔑 Remember: The chain is GGUF loader → LoRA loader → KSampler. The LoRA sits between model and sampler – that's the only way the Ghibli style activates.
Step 4: Load photo, write the prompt, generate
1. Load photo. Upload your source photo in the Load Image node. A clear portrait with good lighting works best.
2. Write the prompt. With the LoRA you need no prompt acrobatics – the recommended sentence is enough:
Turn this image into the Ghibli style.3. Set the parameters. The tested values:
| Parameter | Value | Why |
|---|---|---|
| Sampler | euler | stable for Flux |
| Scheduler | simple | standard for Kontext |
| Steps | 20 | clean look; 8 for a quick preview run |
| Guidance | 2.5 | Kontext standard – the LoRA does the style work |
| CFG | 1.0 | fixed for Flux |
| LoRA strength | 1.0 | full Ghibli look |
4. Generate. Click Queue Prompt.
🧪 Try it: The first run takes ~2–3 minutes because both the model and the LoRA load into VRAM. Every further conversion runs at ~30–60 seconds on the RTX 3060.
Result: your photo becomes a hand-painted Ghibli character – face, pose and clothes stay, the painting style is real Ghibli.
Fine-tuning: LoRA strength controls the look
The one dial that makes the difference is strength_model on the LoRA node:
| Strength | Effect |
|---|---|
| 1.0 | Full Ghibli look – hand-painted, soft eyes, film feel |
| 0.7–0.8 | Keeps more of the photo's realism (photo ↔ Ghibli blend) |
| 0.5 | Just a light coat – clearly a photo, with a Ghibli tone |
💡 Tip: The Kontext-Style project has not only Ghibli but a whole set of style LoRAs for Kontext (watercolor, cartoon, line-art and more). Same workflow, you just swap the LoRA file – so you build a whole style palette from one photo.
Doesn't look like Ghibli? Quick fixes
| Problem | Cause | Fix |
|---|---|---|
| Models/LoRA not in dropdown | ComfyUI not restarted | restart ComfyUI |
| "Unet Loader (GGUF)" node missing | ComfyUI-GGUF not installed | Manager → install ComfyUI-GGUF |
| Result = generic anime | LoRA not active / strength 0 | check the chain GGUF → LoRA → KSampler, set strength_model to 1.0 |
| Look too weak | LoRA strength too low | raise strength_model toward 1.0 |
| Face becomes unrecognizable | LoRA strength too high for your subject | lower to 0.8 |
| Red nodes / errors | file in the wrong folder | check folders per the table above |
No 12 GB card? Use the cloud
If your GPU won't keep up or lacks VRAM: run the exact same workflow (LoRA included) on a cloud GPU – an RTX 4090 (24 GB) from ~$0.59/h renders Kontext in seconds and with no quant compromise. The full setup is in our hub:
👉 Set up ComfyUI on RunPod (Network Volume)
Keine starke Grafikkarte? Führe ComfyUI in der Cloud aus.
Flux & SDXL sind speicherhungrig. Statt ~1.800 € für eine eigene Karte mietest du bei RunPod eine 24-GB-GPU ab ca. 0,50 €/Stunde – und zahlst nur, was du nutzt.
Conclusion & next steps
Real Ghibli needs no subscription and no ChatGPT – just Flux Kontext plus a free LoRA. Kontext locks your subject in place, the LoRA brings the real style. The prompt alone only makes generic anime – the LoRA is the difference.
- 📥 Download: Get the Ghibli workflow as JSON – load it in ComfyUI via Workflow → Open, the LoRA is already wired in, drop in your photo, generate.
- 🎨 The LoRA itself: Kontext-Style/Ghibli_lora on HuggingFace (free).
- 🔗 Missing the basics? → Install Flux.1 Dev with ComfyUI
- ⏮️ From the series: Flux Kontext: Change Clothes in ComfyUI
- ⏭️ Up next: "Flux Kontext: Swap the Background" and "Flux Kontext: Change Hairstyle".
One photo, one LoRA, one sentence – and your snapshot becomes a scene that looks straight out of your favorite film.