Skill-Details
model-routing
Wählt Standard-fal.ai-Endpoint-IDs für genmedia-Produktions-Skills aus, einschließlich Videogenerierung, Bildgenerierung und Bearbeitung.
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SKILL.md
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---
name: model-routing
description: >
Choose default fal.ai endpoint IDs for genmedia production skills. Use this
with commercial, marketing, ugc, character-design, cinematography,
storytelling, and workflow when the user has not named a specific model.
---
# Genmedia model routing
Use these endpoint defaults when a domain skill needs a model. These choices
come from project-specific guidance. Still run `genmedia schema <endpoint_id>
--json` before execution and `genmedia pricing <endpoint_id> --json` when cost
matters.
Endpoint-first rule:
1. Pick the endpoint ID from this skill.
2. Verify it with `genmedia models --endpoint_id <endpoint_id> --json`.
3. Inspect it with `genmedia schema <endpoint_id> --json`.
4. Check `genmedia pricing <endpoint_id> --json` when cost matters.
5. Use text search only if the routed endpoint is missing, deprecated,
rejected, or the task needs a model role not covered here.
Do not invent endpoint IDs.
## Image generation
### Text-heavy image work
Use for infographics, UI mockups, posters, product labels, packaging text,
readable signs, book covers, educational diagrams, and any output where text
inside the image must be accurate.
1. `openai/gpt-image-2`
- Use `quality=high`.
- Prefer 2K or 4K custom `image_size` when the final must be detailed.
- Treat as expensive. Do not use it for cheap drafts.
2. `fal-ai/nano-banana-pro`
- Use as the second choice when text is important but GPT Image 2 is not
available or the user accepts a lower ceiling.
Cheap and simple models are not acceptable for text-heavy production.
### Premium still images
Use for commercial stills, realistic product scenes, editorial photography,
cinematic keyframes, and high-quality visual concepts.
- More realistic output: `openai/gpt-image-2`.
- High-quality styled output: `openai/gpt-image-2`.
- One step down: `fal-ai/nano-banana-pro`.
- Strong cheaper alternative: `fal-ai/nano-banana-2`.
### Fast draft images
Use for quick concepts, mood options, rough composition, and cheap iteration.
- `fal-ai/flux-2/klein/9b`
Do not use fast draft output as final commercial delivery unless the user asks.
## Image editing
Use for background replacement, relighting, cleanup, object changes, product
placement, outfit changes, character edits, and multi-image composition.
1. `fal-ai/nano-banana-pro/edit`
2. `openai/gpt-image-2/edit`
3. `fal-ai/bytedance/seedream/v5/lite/edit`
For product fidelity, also consider:
- `fal-ai/nano-banana-pro`
- `fal-ai/nano-banana-2`
- `fal-ai/bytedance/seedream/v5/lite/text-to-image`
- `fal-ai/nano-banana-2/edit`
For consistent characters, use `openai/gpt-image-2` first. If editing an
existing character image, inspect `openai/gpt-image-2/edit`.
## Video generation
### Highest quality video
Use Seedance 2.0 first for final, high-quality video.
- Text to video: `bytedance/seedance-2.0/text-to-video`
- Image to video: `bytedance/seedance-2.0/image-to-video`
- Reference to video: `bytedance/seedance-2.0/reference-to-video`
Fast variants exist for lower latency:
- `bytedance/seedance-2.0/fast/text-to-video`
- `bytedance/seedance-2.0/fast/image-to-video`
- `bytedance/seedance-2.0/fast/reference-to-video`
### Fast or lower-cost video
Use Grok Imagine Video for fast, lower-cost motion previews and economical
video generation.
- Text to video: `xai/grok-imagine-video/text-to-video`
- Image to video: `xai/grok-imagine-video/image-to-video`
- Video edit: `xai/grok-imagine-video/edit-video`
### Multi-shot storytelling
Use in this order:
1. `bytedance/seedance-2.0/text-to-video`
2. `bytedance/seedance-2.0/image-to-video`
3. `bytedance/seedance-2.0/reference-to-video`
4. `fal-ai/kling-video/v3/pro/text-to-video`
5. `fal-ai/kling-video/v3/pro/image-to-video`
6. `alibaba/happy-horse/text-to-video`
7. `alibaba/happy-horse/image-to-video`
Use Kling v3 when its multi-prompt, element, or custom element controls match
the requested shot plan. Use Happy Horse after Seedance aVollständige Quelle auf GitHub lesen (öffnet externe Seite)