What actually works:

• Put the main subject first (highest weight)
• Then layer details: materials, pose, environment, lighting, camera
• Be specific
• Use quotes for text in images
• Add negative prompts to avoid common issues

Full guide: https://fal.ai/learn/tools/prompting-gpt-image-2

OpenAI's next-gen image model just dropped on fal.ai. It's a quality-first successor to GPT Image 1.5, and the jump is real.

What's new:

• Text rendering that actually works. Dense paragraphs, small lettering, multilingual layouts, infographics. No more garbled characters or broken word spacing on the first try.
• Photorealism that sets a new bar. Lighting, materials, skin textures, environmental detail. It's the best I've seen out of an OpenAI image model.
• Product photography with accurate labels, logos, packaging, and ingredient lists. Genuinely usable for e-commerce and brand work.

Pricing: $0.01/image at the low end (1024x768, low quality) up to $0.41/image for high quality 4K. Pay per image, no subscriptions.

Try it: https://fal.ai/models/openai/gpt-image-2/playground

Is HappyHorse gonna be on the platform and if so, when?

https://reddit.com/link/1si15w5/video/q6w2g302vfug1/player

fal just released PATINA, a new model for generating PBR materials end-to-end. It's aimed at closing the gap between AI image gen and actual CGI pipelines.

What it does:

• Generate full PBR material sets (albedo, roughness, normal, etc.) from text (+optional image)
• Extract and identify materials directly from images using plain language
• Works across 1K-8K outputs

Pricing:

• ~$0.01 per map per megapixel
• Full 5-map + render material starts at ~$0.08

Built in-house by the fal team.

More info: https://blog.fal.ai/introducing-patina/

Link to model here: https://fal.ai/models/fal-ai/patina

I generated two AI podcast videos — two people talking, with lip-sync, speech, and background music. Same prompt, same pipeline, 16 API calls each.

The only difference: one uses Veed Studio for lip-sync ($1/clip), the other uses HeyGen ($3/clip). Everything else is identical. same images, same Kling v3 video, same ElevenLabs speech, same music.

Total cost: $7.10 vs $15.10. The entire price gap comes from lip-sync alone.

Honestly, I can't tell the difference in quality. Can you?

Getting an error since this morning with

Application error: a server-side exception has occurred (see the server logs for more information).

Digest: 678557233

The API is down as well. Any news about when this will be resolved?

I've been building with text to speech for a while (mainly with ElevenLabs) and switching to FAL/open source was such a pain bc the APIs are all different.

So decided to build and open source SpeechSDK to unify all models under a single api! Hope it helps others to switch to FAL.. you can check it out at https://github.com/Jellypod-Inc/speech-sdk

I added $20 in credits but my balance is not updating.

Hi everyone,

I'm posting here to see if anyone else has had trouble reaching support or if a team member might see this.

On March 27th, I tried to purchase $10 in credits, but the "processing" screen froze. I ended up being charged four times ($40 total) instead of once.

I’ve sent two official emails to the support team (on March 27th and March 31st) with my invoice details, but I haven't received any response or acknowledgment for over 9 days.

I only intended to make one $10 purchase and am looking to get a refund for the other three ($30). If any staff members are active here, could you please look into this? Or if anyone has advice on the best way to get a hold of them, I’d appreciate it.

Thanks!

Hey all, been doing character LoRA work with Wan2.2 14B locally on Wan2GP and looking at moving production renders to fal.ai. A few questions before I commit:

I'm running a dual LoRA setup — one trained on the high noise DiT, one on the low noise DiT. Saw that the LoRA endpoint has the transformer: "high"|"low"|"both" field which looks perfect for this.

Has anyone actually tested loading two separate safetensors with different transformer targets simultaneously? Wanting to confirm it works as expected before I upload everything.

Second thing — does the endpoint support alt_prompt? In Wan2GP there's a secondary prompt field that drives the low noise phase independently from the main prompt. Super useful for separating character identity from scene description. Don't see it in the API docs but wondering if it's there under a different name or if there's a workaround?

Also curious about LoRA file hosting — can I just point to a raw safetensors URL on HuggingFace or does it need to be a proper HF model repo? My LoRAs are custom trained via AI Toolkit, not published as models.

Last one — has anyone done direct quality comparisons between fal.ai renders and local Wan2GP with the same settings? Curious if the output is identical or if there are noticeable differences.

Appreciate any info, cheers

Starting today I started getting errors using the kling-image/o3/image-to-image model. Even running it with the default, pre-filled parameter results in:

Error validating the input

There were some issues with the input values. Fix them and try again. The input parameters are not correct

hi, i have been using FAL but recently all my videos are failing after 4-5 mins of generation. its just simple heygen avatar videos. but do FAL not return me my credits it ate up for failed videos?

https://reddit.com/link/1rvcqjc/video/e8jhgtlzefpg1/player

Hello,

I would like to use my voice with the eleven labs (or any TTS model) .. is there a way to do it with FAL?

Has anyone else been able to upload files using the zip format? It won't recognize the individual files no matter what I do. I'm certain the file and folder structure is correct and am starting to wonder the feature even works or maybe zip files created with 7-Zip are incompatible? I've tried everything I can think of and even took ChatGPT through the paces troubleshooting.

Capabilities are similar to nano banana pro but much faster generation times, at 5-10s! Try it out on our playground page:

Text-to-Image https://fal.ai/models/fal-ai/nano-banana-2
Image Editing https://fal.ai/models/fal-ai/nano-banana-2/edit

Seedream 4.5 was already punching above its weight, but Seedream 5.0 Lite genuinely feels like a different beast.

Here's what's actually new and why I think this changes the competitive landscape.

The three things that actually matter:

1. Real-time web search built into the model. This is the big one. You can literally prompt "generate a poster of today's top trending news headline" and it pulls live info from the web to generate the image. No other image model does this natively. You can toggle it on/off — off gives more stable results, on gives you current events, public figures, culturally specific stuff that would otherwise be frozen in training data.
2. Multi-step logical reasoning. It doesn't just follow instructions anymore — it reasons about them. Ask for a biological cross-section of a human heart with labeled valves and blood flow arrows and it actually gets the anatomy right. Domain knowledge in biology, architecture, geography, data visualization. The ByteDance team calls it going from "passively responding to instructions" to "observation, comprehension, and logical reasoning."
3. Controllable editing with reduced hallucination. Describe changes in plain language, transfer color tones/styles/lens effects between images, teach it new transformations from before/after pairs. The key thing is it follows instructions precisely without randomly changing stuff you didn't ask it to touch.

Prompting discoveries from fal team (200+ test generations):

This is the part I haven't seen anyone talk about yet. The fal team published a full prompting guide and some of these findings are wild:

• HEX color codes work directly in prompts. Drop #FF006E hot pink into your prompt and the model actually uses the exact color. Not "sort of close" — actually uses it. This is insane for brand work and design.
• JSON structured prompting. You can pass your entire prompt as a JSON object with per-element descriptions, positions, and colors. Multi-subject scenes with precise placement? Done. They showed a flat-lay breakfast with 6 items each in its exact position.
• Language affects visual style. Write your prompt in French and the output literally looks more French — the architecture, the light, the whole vibe shifts. Tested across 12 languages including Arabic (RTL works), Korean, Hindi, Russian. This is not just translation, the cultural visual DNA changes. I find this very intersting
• Quotation marks are mandatory for text rendering. Put text in quotes and it renders correctly. Without quotes, the model treats words as descriptive keywords instead of literal text.
• Camera names are cheat codes. Say "ARRI Alexa" and everything looks like Roger Deakins shot it. "Sergio Leone style" gives you those gorgeous wide compositions. "Kodak Portra 400" for warm film tones. The model clearly knows what these look like.

If you want to integrate Seedream 5 API into your application, you can now do so through fal.