fal.ai

fal.ai is a fast inference platform for image generation models (FLUX, Ideogram, Recraft, Nano Banana, and more) plus LLMs via OpenRouter. Portkey routes image generation requests to fal’s native API and chat completion requests through fal’s OpenAI-compatible path.

Provider slug: fal-ai

Quick Start

from portkey_ai import Portkey

portkey = Portkey(api_key="PORTKEY_API_KEY")

image = portkey.images.generate(
    model="@fal-ai/fal-ai/flux/schnell",
    prompt="A photorealistic mountain lake at sunrise"
)

print(image.data[0].url)

import Portkey from 'portkey-ai';

const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" });

const image = await portkey.images.generate({
    model: "@fal-ai/fal-ai/flux/schnell",
    prompt: "A photorealistic mountain lake at sunrise"
});

console.log(image.data[0].url);

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL

client = OpenAI(
    api_key="PORTKEY_API_KEY",
    base_url=PORTKEY_GATEWAY_URL
)

image = client.images.generate(
    model="@fal-ai/fal-ai/flux/schnell",
    prompt="A photorealistic mountain lake at sunrise"
)

print(image.data[0].url)

import OpenAI from "openai";
import { PORTKEY_GATEWAY_URL } from "portkey-ai";

const client = new OpenAI({
    apiKey: "PORTKEY_API_KEY",
    baseURL: PORTKEY_GATEWAY_URL
});

const image = await client.images.generate({
    model: "@fal-ai/fal-ai/flux/schnell",
    prompt: "A photorealistic mountain lake at sunrise"
});

console.log(image.data[0].url);

curl https://api.portkey.ai/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -d '{
    "model": "@fal-ai/fal-ai/flux/schnell",
    "prompt": "A photorealistic mountain lake at sunrise"
  }'

The model format is @{provider-slug}/{fal-model-id}. Since fal model IDs start with fal-ai/, the full path becomes @fal-ai/fal-ai/flux/schnell.

Add Provider in Model Catalog

Go to Model Catalog → Add Provider
Select fal.ai
Enter your fal.ai API key
Name your provider (e.g., fal-ai)

Model Catalog Setup

Complete setup options and configuration

Chat Completions

fal.ai provides LLM access via an OpenAI-compatible endpoint (powered by OpenRouter). Use chat.completions.create with the same client:

from portkey_ai import Portkey

portkey = Portkey(api_key="PORTKEY_API_KEY")

response = portkey.chat.completions.create(
    model="@fal-ai/google/gemini-2.5-flash",
    messages=[{"role": "user", "content": "Explain diffusion models in one sentence."}]
)

print(response.choices[0].message.content)

import Portkey from 'portkey-ai';

const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" });

const response = await portkey.chat.completions.create({
    model: "@fal-ai/google/gemini-2.5-flash",
    messages: [{ role: "user", content: "Explain diffusion models in one sentence." }]
});

console.log(response.choices[0].message.content);

curl https://api.portkey.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -d '{
    "model": "@fal-ai/google/gemini-2.5-flash",
    "messages": [{"role": "user", "content": "Explain diffusion models in one sentence."}]
  }'

LLM model IDs follow OpenRouter’s format — e.g., google/gemini-2.5-flash, anthropic/claude-sonnet-4, meta-llama/llama-4-maverick. Browse available models at fal.ai/models.

Image Generation

Image generation requests go to POST /v1/images/generations. The model ID maps to a path on fal.run — for example, model="fal-ai/flux/dev" routes to https://fal.run/fal-ai/flux/dev.

from portkey_ai import Portkey

portkey = Portkey(api_key="PORTKEY_API_KEY", provider="@fal-ai")

image = portkey.images.generate(
    model="fal-ai/flux-pro/v1.1",
    prompt="A futuristic city at night, neon lights reflecting on wet streets",
    n=2,
    size="1024x1024"
)

for img in image.data:
    print(img.url)

import Portkey from 'portkey-ai';

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",
    provider: "@fal-ai"
});

const image = await portkey.images.generate({
    model: "fal-ai/flux-pro/v1.1",
    prompt: "A futuristic city at night, neon lights reflecting on wet streets",
    n: 2,
    size: "1024x1024"
});

image.data.forEach(img => console.log(img.url));

curl https://api.portkey.ai/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-provider: @fal-ai" \
  -d '{
    "model": "fal-ai/flux-pro/v1.1",
    "prompt": "A futuristic city at night, neon lights reflecting on wet streets",
    "n": 2,
    "size": "1024x1024"
  }'

Parameters

Portkey maps OpenAI-style parameters to fal’s API:

Parameter	fal parameter	Details
`prompt`	`prompt`	Required
`n`	`num_images`	1–4, default 1
`size`	`image_size`	See size mapping below
`seed`	`seed`	For reproducible outputs

Size mapping:

`size` value	fal `image_size`
`256x256`	`square_hd`
`512x512`	`square`
`1024x1024`	`square_hd`
`1024x1792`	`portrait_4_3`
`1792x1024`	`landscape_4_3`
Any other value	Passed through as-is

fal-native size strings like landscape_16_9 or portrait_16_9 can be passed directly. Responses always return image URLs. response_format: "b64_json" is not supported.

Parameters outside the table above (quality, style, guidance_scale, num_inference_steps, etc.) are not forwarded to fal.

Supported Image Models

Model ID	Description
`fal-ai/flux/schnell`	FLUX Schnell — fastest, best for rapid iteration
`fal-ai/flux/dev`	FLUX Dev — higher quality, open weights
`fal-ai/flux-pro/v1.1`	FLUX Pro 1.1 — high quality, commercial use
`fal-ai/flux-pro/v1.1-ultra`	FLUX Pro Ultra — highest resolution
`fal-ai/flux-pro/kontext`	FLUX Kontext — context-aware generation
`fal-ai/recraft-v3`	Recraft V3
`fal-ai/recraft/v4/pro/text-to-image`	Recraft V4 Pro
`fal-ai/nano-banana-2`	Nano Banana 2 — fast semantic generation
`fal-ai/nano-banana-pro`	Nano Banana Pro — highest quality
`fal-ai/ideogram/v2`	Ideogram V2
`fal-ai/ideogram/v2/turbo`	Ideogram V2 Turbo
`openai/gpt-image-2`	GPT Image 2 via fal

fal.ai hosts 1000+ models. Any model on fal.ai/models that accepts a prompt input works with Portkey’s image generation route — use its endpoint ID as the model value.

Next Steps

Configs

Add fallbacks, load balancing, and retries

Observability

Monitor usage and costs across models

Caching

Cache image generation results

Metadata

Tag requests with custom metadata

Portkey is now PRISMA AIRS AI Gateway. See it in action.

Last modified on August 21, 2026

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Quick Start

Add Provider in Model Catalog

Model Catalog Setup

Chat Completions

Image Generation

Parameters

Supported Image Models

Next Steps

Configs

Observability

Caching

Metadata

Portkey is now PRISMA AIRS AI Gateway. See it in action.

​Quick Start

​Add Provider in Model Catalog

Model Catalog Setup

​Chat Completions

​Image Generation

​Parameters

​Supported Image Models

​Next Steps

Configs

Observability

Caching

Metadata

Portkey is now PRISMA AIRS AI Gateway. See it in action.

Quick Start

Add Provider in Model Catalog

Chat Completions

Image Generation

Parameters

Supported Image Models

Next Steps