Synexa AI

Platform Overview

Synexa AI describes itself as a generative media platform designed for developers, offering high-performance AI model inference and training capabilities. The documentation states that the platform specializes in running diffusion models with production-ready APIs and interactive UI playgrounds. [3]

The documented key features include ready-to-use AI inference APIs optimized for speed and scalability, serverless deployment options for custom AI models, interactive UI playgrounds for model experimentation, and enterprise features such as private models and preference fine-tuning capabilities. [3]

The homepage presents the service around a one-line deployment pattern, showing a curl request to the predictions endpoint that passes an API key header, a model identifier, and an input prompt. [1]

Documented Features

The homepage states that the platform provides access to 100+ production-ready AI models, including FLUX Pro, Ideogram v2, and Hunyuan Video, with new models added weekly and zero setup required. [1]

The model gallery lists specific entries such as nano-banana-pro for image generation and editing, hunyuan3d-2 for generating high-resolution textured 3D assets, veo3.1 for video with context-aware audio and reference image support, and z-image-turbo as a fast text-to-image model. [1]

• Generate images, videos, and speech, restore and caption images, and fine-tune models [1]

• Available model categories include image generation, video generation, speech-to-text, and text generation [4]

Getting Started Workflow

The quickstart guide instructs users to create an API key before proceeding, since the key authenticates requests to the Synexa AI API. Python users install the synexa client and can supply the key through an environment variable or direct initialization; Node.js users install the synexa package and initialize it with an API token. [4]

A first API call runs a model by name, such as black-forest-labs/flux-schnell, with an input prompt. The Python example writes each returned image to a webp file, while the Node.js example reads the output URL or retrieves the file data as a blob. [4]

For each model, the documentation and example code are available in the API tab of the model's page, and the guides cover generating images, generating videos, speech to text, and using LLMs. [4]

• Install the Python client with pip install synexa [4]

• Install the Node.js client with npm install synexa [4]

• Call models through the REST API as an alternative to the SDKs [1]

Pricing and Billing

The pricing page states that Synexa adapts to usage so customers pay only for the computing power they consume, with billing based on model output. Published model prices include FLUX.1 [dev] at 0.0125 per image, FLUX.1 [schnell] at 0.0015 per image, FLUX.1 [pro] at 0.02 per image, Stable Diffusion XL at 0.002 per image, Wan 2.1 Video at 0.2 per video, and Hunyuan 3D at 0.025 per 3D model. [2]

Hardware is billed by the second, and the page states that when nothing is running it scales to zero and no charge applies. Listed GPU rates include the Nvidia H100 at $0.00083 per second, the A100 80GB at $0.00069 per second, the A6000 at $0.000414 per second, the RTX 4090 at $0.000192 per second, and the RTX 3090 at $0.000119 per second. [2]

The pricing page presents these rates alongside comparison figures from other providers, describing savings such as 50% on FLUX.1 [schnell] and 60% on FLUX.1 [pro]. These comparisons are vendor-published statements rather than independently measured results. [2]

Developer Experience and Scaling

The homepage describes integration through intuitive SDKs and API documentation, with support for Python, JavaScript, and REST API. It also states that GPU infrastructure with A100s and H100s spans three continents and that smart routing provides sub-100ms latency with a 99.9% uptime guarantee; these are vendor performance claims. [1]

Automatic scaling is described as handling traffic spikes instantly, paying only for what is used, scaling to zero when idle, and scaling up when busy. [1]

The homepage states that the optimized inference engine delivers up to 4x faster performance on diffusion models and sub-second generation times with FLUX and other popular models, which is a publisher claim rather than an independent measurement. [1]

Sources

• 1. Synexa AI: Deploy AI Models in One Line of Code

• 2. Synexa Pricing - Affordable AI Computing Solutions

• 3. Introduction - Synexa AI

• 4. Quickstart with Synexa AI - Synexa AI

Sources checked October 19, 2026 (UTC).