AI Image Generation

AI Image Generation

Generate and edit images with 11+ AI models via the RunComfy CLI — text-to-image and image-to-image, one auth, one command. This skill picks the right model for the user's intent and ships the documented prompt patterns + the exact runcomfy run invoke for each.

runcomfy.com · Browse all models · CLI docs

Powered by the RunComfy CLI

# 1. Install (one of — see runcomfy-cli skill for details)
npm i -g @runcomfy/cli                              # global install
npx -y @runcomfy/cli --version                      # zero-install

# 2. Sign in (interactive — opens browser)
runcomfy login
# or in CI / containers:
export RUNCOMFY_TOKEN=

# 3. Generate
runcomfy run // \
  --input '{"prompt": "..."}' \
  --output-dir ./out

CLI docs: Install · Quickstart · Commands · Auth · Troubleshooting

Install this skill

npx skills add agentspace-so/runcomfy-agent-skills --skill ai-image-generation -g

---

Pick the right model for the user's intent

Text-to-image (t2i) — newest first

FLUX 2 Klein 9B — blackforestlabs/flux-2-klein/9b/text-to-image (default) > Step-distilled, 4–25 steps, native multi-reference conditioning, strong photoreal + illustration all-rounder. > Pick for: intent unclear, fast iteration, multi-ref styling, general-purpose. > Avoid for: in-image text — use GPT Image 2.

FLUX 2 Klein 4B — blackforestlabs/flux-2-klein/4b/text-to-image > Sub-second variant of Klein 9B, same field set. > Pick for: storyboard, moodboard, batch concepting at speed. > Avoid for: final delivery — slight quality drop vs 9B.

FLUX 2 Pro / Dev / Flash / Turbo / Max — blackforestlabs/flux-2/max, flux-2-dev, flux-2-flash, flux-2-turbo > Higher-fidelity tiers of the FLUX 2 base. Cinematic + brand work, hero shots. > Pick for: production polish, brand campaigns. > Avoid for: sub-second speed — use Klein 4B.

Nano Banana Pro — google/nano-banana-pro/text-to-image > Highest-quality Nano Banana tier. Gemini-grounded, optional web search for real-world references (products, landmarks). > Pick for: NB-style instruction-following at higher fidelity. > Avoid for: cost-sensitive iteration — drop to Nano Banana 2.

Nano Banana 2 — google/nano-banana-2/text-to-image > Flash-tier latency, predictable framing, enable_web_search flag for real-product / real-person grounding. > Pick for: speed iteration, 4-up batch, real-world grounded prompts. > Avoid for: long compositional instructions — use GPT Image 2.

GPT Image 2 — openai/gpt-image-2/text-to-image > Best-in-class in-image text rendering (Japanese kana, Cyrillic, Arabic). Layout-precise instruction following. > Pick for: posters, ads, multi-line copy, multilingual creatives, exact-text headlines. > Avoid for: photoreal portraits — Seedream 5 wins on skin tones and lighting.

Seedream 5 Lite — bytedance/seedream-5/lite/text-to-image > Latest ByteDance Seedream tier. Photoreal skin tones, natural lighting, strong East Asian aesthetic. > Pick for: photoreal portraits, product shots, fashion / lifestyle. > Avoid for: typography precision — use GPT Image 2.

Seedream 4-5 — bytedance/seedream-4-5/text-to-image > Previous Seedream flagship, still strong on photoreal. > Pick for: identity-stable batches between Seedream-5 generations; cheaper Seedream tier. > Avoid for: new work — prefer Seedream 5 Lite.

Dreamina 4-0 — bytedance/dreamina-4-0/text-to-image > ByteDance illustration / concept-art lean, stylized characters. > Pick for: concept art, illustrated heroes, painterly assets. > Avoid for: photoreal — use Seedream.

Qwen Image 2512 — qwen/qwen-image/qwen-image-2512 > Alibaba Qwen latest, open-weights, LoRA-compatible (/lora variant). > Pick for: open-weights workflow, Qwen-aligned LoRA chains. > Avoid for: closed-weights polish — use FLUX 2 or GPT Image 2.

Wan 2-7 — wan-ai/wan-2-7/text-to-image, wan-ai/wan-2-7/pro/text-to-image > Open-weights, pairs natively with Wan 2-7 video models for unified-stack workflows. > Pick for: Wan-stack pipelines (image + video same brand), open-weights requirement. > Avoid for: top-tier image-only quality.

Z-Image Turbo — tongyi-mai/z-image/turbo > Sub-second open-weights, native LoRA /lora variant. > Pick for: LoRA-customized open-weights workflow at speed. > Avoid for: closed-weights polish.

Image-to-image / edit (i2i) — newest first

Nano Banana Pro Edit — google/nano-banana-pro/edit > Highest-quality Nano Banana edit tier. Identity-preserving, multi-ref. > Pick for: premium NB edit work, identity-locked variants. > Avoid for: cost-sensitive iteration — drop to Nano Banana 2 Edit.

Nano Banana 2 Edit — google/nano-banana-2/edit (default i2i) > 1–20 input images per call, identity-preserving by default, spatial-language honored (upper-right, the left object). > Pick for: default i2i, batch identity-preserving, background swap, directional object remove/add. > Avoid for: precise mask region — use the image-edit skill (Z-Image Inpaint).

GPT Image 2 Edit — openai/gpt-image-2/edit > Up to 10 reference images, multilingual in-image text rewrite, layout-precise repositioning. > Pick for: multilingual headline swap, multi-ref composition, layout repositioning, brand-locked identity across translations. > Avoid for: mask-driven inpainting — use image-edit skill.

Seedream 5 Lite Edit — bytedance/seedream-5/lite/edit > Latest Seedream edit tier, photoreal preservation. > Pick for: photoreal edits that started from a Seedream t2i (identity holds across the pair). > Avoid for: multilingual text rewrite.

Seedream 4-5 Edit — bytedance/seedream-4-5/edit > Previous Seedream edit. > Pick for: identity-stable batches between 4-5 generations. > Avoid for: new work — prefer Seedream 5 Lite Edit.

Dreamina 4-0 Edit — bytedance/dreamina-4-0/edit > ByteDance illustration edit. > Pick for: editing a Dreamina-generated illustration. > Avoid for: photoreal subjects.

Qwen Image Edit 2511 — qwen/qwen-image/qwen-image-edit-2511 > Alibaba open-weights edit. > Pick for: open-weights edit pipeline. > Avoid for: closed-weights polish.

Wan 2.6 i2i — wan-ai/wan-v2.6/image-to-image > Wan ecosystem image-to-image. > Pick for: Wan-stack pipeline integration. > Avoid for: new work — older generation; prefer NB or GPT Image 2.

FLUX Kontext Pro — blackforestlabs/flux-1-kontext/pro/edit > Single-ref single-instruction, highest preservation fidelity (keep everything except X). > Pick for: single-image precise local edit (change only her umbrella to orange). > Avoid for: batch work, multi-ref composition, mask-driven inpainting.

> Need mask-driven inpainting, controlled outpainting, or the full edit treatment? → use the image-edit skill.

---

t2i Route 1: FLUX 2 Klein — default

Models: blackforestlabs/flux-2-klein/9b/text-to-image (default), blackforestlabs/flux-2-klein/4b/text-to-image (sub-second) Catalog: 9B · 4B

Schema (both variants)

Field	Type	Required	Default	Notes
prompt	string	yes	—	Up to ~512 tokens; longer degrades. Subject-first declarative
steps	int	no	25 (9B) / 4 (4B)	Step-distilled; 4–8 enough for ideation, ~25 for polish, >25 buys little
width	int	no	1024	512–1536 typical, max ~2K total. Aspect cap 16:9
height	int	no	1024	Match width's aspect intent

Up to 4 reference images supported on the same endpoint for style transfer / guided composition. Field name documented on the model page.

Invoke

Polish / final (9B):

runcomfy run blackforestlabs/flux-2-klein/9b/text-to-image \
  --input '{
    "prompt": "A small purple cat sitting on a moss-covered stone, golden hour rim light, shallow depth of field, photoreal",
    "steps": 25,
    "width": 1536,
    "height": 864
  }' \
  --output-dir ./out

Sub-second concepting (4B):

runcomfy run blackforestlabs/flux-2-klein/4b/text-to-image \
  --input '{"prompt": "A small purple cat at sunset, photoreal"}' \
  --output-dir ./out

Prompting tips

• Subject first, scene second, modifiers last. A small purple cat … on a moss stone … golden hour, shallow DoF.
• Step strategy: 4–8 for ideation, ~25 for polish. Don't crank past 28 — diminishing returns.
• 9B vs 4B: default 9B; drop to 4B only when you need sub-second batch concepting.
• Multi-ref: 1–4 reference URLs; describe roles in prompt ("subject from ref 1, palette from ref 2").

---

t2i Route 2: GPT Image 2 — typography & in-image text

Model: openai/gpt-image-2/text-to-image Catalog: runcomfy.com/models/openai/gpt-image-2

Schema

Field	Type	Required	Default	Notes
prompt	string	yes	—	Quote in-image text exactly with "…"
size	enum	no	1024_1024	1024_1024 (1:1), 1024_1536 (2:3 portrait), 1536_1024 (3:2 landscape) — only these three

Invoke

Logo / poster with exact headline:

runcomfy run openai/gpt-image-2/text-to-image \
  --input '{
    "prompt": "Minimal product poster. Centered bold headline reads exactly \"AURORA — Spring 2026\" in clean white sans-serif on a deep navy background. Below the headline a small line in monospace reads \"runs on water\". 3:2 layout.",
    "size": "1536_1024"
  }' \
  --output-dir ./out

Multilingual:

runcomfy run openai/gpt-image-2/text-to-image \
  --input '{
    "prompt": "Japanese magazine cover. Vertical headline reads exactly \"今日のおすすめ\" in bold Japanese kana, right-edge alignment, photoreal portrait of a woman in a kimono.",
    "size": "1024_1536"
  }' \
  --output-dir ./out

Prompting tips

• Quote in-image text exactly. "the sign reads exactly 'CLOSED'" — without the literal quote the model paraphrases.
• Name the script for non-Latin text: "Japanese kana", "Cyrillic", "Arabic right-to-left". Without this it falls back to romanization.
• Layout language honored: "top-left", "centered", "two-line stacked", "baseline aligned".
• Only 3 sizes. Don't pass arbitrary widths.

---

t2i Route 3: Nano Banana 2 — speed iteration

Model: google/nano-banana-2/text-to-image Catalog: runcomfy.com/models/google/nano-banana-2 · nano-banana collection

Schema

Field	Type	Required	Default	Notes
prompt	string	yes	—	Subject-first description
num_images	int	no	1	1–4. Use 4 for ideation rounds
seed	int	no	0	Reuse for reproducibility
aspect_ratio	enum	no	auto	auto, 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16
resolution	enum	no	1K	0.5K (drafts), 1K (default), 2K (final), 4K (max)
output_format	enum	no	png	png, jpeg, webp
safety_tolerance	int	no	4	1 (strict) – 6 (permissive)
enable_web_search	bool	no	false	Adds web grounding (extra cost + latency)

Invoke

Default draft:

runcomfy run google/nano-banana-2/text-to-image \
  --input '{"prompt": "A coffee mug on marble counter, top-down warm morning light"}' \
  --output-dir ./out

4-up batch for ideation:

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "Three product photos of a ceramic coffee mug on a marble counter, warm morning light, top-down angle, minimal styling",
    "num_images": 4,
    "aspect_ratio": "1:1",
    "resolution": "0.5K"
  }' \
  --output-dir ./out

Prompting tips

• Subject-first declarative. A coffee mug on marble beats Generate a creative shot of a mug.
• enable_web_search: true when the prompt names a real product, place, or person whose appearance must match reality (logos, landmarks).
• Drop to 0.5K for ideation, jump to 2K+ only for finals — 4K ~16× the cost of 0.5K.

---

t2i Route 4: Seedream 5 / 4-5 — photoreal flagship

Models: bytedance/seedream-5/lite/text-to-image · bytedance/seedream-4-5/text-to-image Collection: seedream

Invoke

runcomfy run bytedance/seedream-5/lite/text-to-image \
  --input '{"prompt": "85mm portrait of a woman by a window, soft natural light, shallow depth of field, photoreal"}' \
  --output-dir ./out

Field schema is on the model page — pass through the CLI verbatim.

When to pick Seedream

• Photoreal portraits / product — realistic skin tones and natural lighting
• East Asian aesthetic / fashion — strong on these subject categories
• Cinematic frames — picks up lens and lighting language well
• vs FLUX 2: Seedream skews more photoreal; FLUX skews more design/illustration

---

t2i Route 5: Open-weights & specialty models

For workflows that want open-weights / LoRA support, or alternative aesthetics:

Model	Endpoint	When
wan-ai/wan-2-7/text-to-image	wan-ai/wan-2-7/text-to-image	Wan ecosystem; pair with Wan 2-7 video models
wan-ai/wan-2-7/pro/text-to-image	wan-ai/wan-2-7/pro/text-to-image	Wan Pro tier
tongyi-mai/z-image/turbo	tongyi-mai/z-image/turbo	Sub-second, supports LoRA via /lora endpoint
qwen/qwen-image/qwen-image-2512	qwen/qwen-image/qwen-image-2512	Qwen Image, open-weights, also has /lora variant
bytedance/dreamina-4-0/text-to-image	bytedance/dreamina-4-0/text-to-image	Illustration / concept art lean

Schemas live on each model page — pass field set through the CLI verbatim.

---

i2i — image-to-image / edit (compact)

For one-shot edits, this skill ships three core routes; for the full edit treatment (mask-driven inpainting, batch-edit, all the side schemas), use the dedicated image-edit skill.

i2i Route A: Nano Banana 2 Edit — default

runcomfy run google/nano-banana-2/edit \
  --input '{
    "prompt": "Keep the subject identity, pose, and clothing unchanged. Convert the background into a rainy neon cyberpunk street.",
    "image_urls": ["https://.../portrait.jpg"]
  }' \
  --output-dir ./out

Schema: prompt, image_urls (1–20), number_of_images (1–4), aspect_ratio (auto default), resolution, output_format, seed, enable_web_search. Lead the prompt with preservation goals, end with the chan