Run popular AI models with one simple API.
Chat, text-to-speech and transcription on one OpenAI-compatible endpoint — GPT-OSS 120B, DeepSeek V4 Flash, Kokoro, Whisper and more. Pay per request, no tiers, no daily caps.
Fast to integrate
Familiar chat completions format. Send a request with cURL, Python or JavaScript in minutes.
Pay as you go
Prepaid credits with no subscription or minimums. Every new account starts with free credit.
Zero data retention
US-hosted. Prompts and outputs are not kept by us or by the GPU providers, and nothing trains a model. How models are served.
Models
View allOpenAI's open-weight 120B reasoning model. Strong at coding, tool use and agentic tasks; the drop-in replacement Groq recommends for Llama 3.3 70B.
DeepSeek's fast, inexpensive V4 model with a 1M-token context. Strong general assistant and coding model at the lowest price per token here.
The newest DeepSeek Flash model: much quicker to answer than V4 Flash in our measurements, with a 1M-token context.
Z.ai's fast GLM 5.3 model with tool calling, JSON mode and a 1M-token context, at a low per-token price.
Meta's instruction-tuned 70B model. Still served here after its retirement on Groq — the same llama-3.3-70b-versatile id works unchanged.
Z.ai's full-size GLM 5.3 model: tool calling, JSON-schema output and a 1M-token context, for coding agents and long tasks.
DeepSeek's largest V4 model (0813 release) with a 1M-token context, hosted in the United States.
MiniMax's M3 model: tool calling and a 512K-token context at a price close to the Flash tier.
Moonshot AI's coding-tuned Kimi model with a 262K-token context, for coding agents and IDE assistants.
The small GPT-OSS model: fast and inexpensive for lightweight assistants and classification.
Alibaba's large vision-language model: send images in a chat request for OCR, document extraction and screenshot reasoning.
Fast, natural open-weight text-to-speech with 54 voices across 8 languages, on the OpenAI /v1/audio/speech endpoint.
Expressive Llama-based text-to-speech with emotive tags and eight English voices.
OpenAI's multilingual speech recognition model on the standard /v1/audio/transcriptions endpoint — same request shape as OpenAI and Groq.
NVIDIA's very fast English-first transcription model with accurate timestamps; ideal for long recordings and batch jobs.
Mistral's 24B speech model as a transcription endpoint: eight languages with automatic detection, strong on accented and noisy audio.
Mistral's small Voxtral model: the lowest price per minute here, eight languages with automatic detection.
BAAI's multilingual embedding model: 1,024-dimension vectors, 8K-token inputs, on the OpenAI /v1/embeddings endpoint.
Qwen's 8B embedding model: up to 4,096 dimensions with adjustable size, 32K-token inputs, multilingual.
Qwen's 8B reranker: scores passages against a query so RAG pipelines keep the right context.
Parse screenshots into structured, labeled UI elements for computer-use agents.
Quickstart
Sign up for free. Your key is ready immediately on the API Keys page.
curl https://api.inferenceapis.com/v1/chat/completions \
-H "Authorization: Bearer $INFERENCE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-oss-120b",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello! What can you do?"}
]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.inferenceapis.com/v1",
api_key=os.environ["INFERENCE_API_KEY"],
)
response = client.chat.completions.create(
model="openai/gpt-oss-120b",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello! What can you do?"},
],
)
print(response.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.inferenceapis.com/v1",
apiKey: process.env.INFERENCE_API_KEY,
});
const response = await client.chat.completions.create({
model: "openai/gpt-oss-120b",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Hello! What can you do?" },
],
});
console.log(response.choices[0].message.content);Tune prompts in the playground, browse the model catalog, or read the API reference.