Quickstart

Get an API key

Create a key at withhopper.com/console/keys. The full sk_hopper_... key is shown once, at creation; the console keeps only the prefix. New accounts start with $5 in credits.

Make a chat completion

Any OpenAI-compatible client works. Set the base URL and pass your key.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.withhopper.com/v1",
    api_key="sk_hopper_...",
)

response = client.chat.completions.create(
    model="gemma-4-31b",
    messages=[{"role": "user", "content": "Say hello in one sentence."}],
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.withhopper.com/v1",
  apiKey: "sk_hopper_...",
});

const response = await client.chat.completions.create({
  model: "gemma-4-31b",
  messages: [{ role: "user", content: "Say hello in one sentence." }],
});
console.log(response.choices[0].message.content);

curl https://api.withhopper.com/v1/chat/completions \
  -H "Authorization: Bearer sk_hopper_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemma-4-31b",
    "messages": [{"role": "user", "content": "Say hello in one sentence."}]
  }'

The response is a standard chat completion object. Two headers report spend:

x-hopper-request-cost-usd: 0.000123
x-hopper-credits-remaining-usd: 4.999877

Stream the response

Set stream: true. Tokens arrive as SSE chunks in the OpenAI chunk format.

stream = client.chat.completions.create(
    model="gemma-4-31b",
    messages=[{"role": "user", "content": "Count to five."}],
    stream=True,
)
for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

const stream = await client.chat.completions.create({
  model: "gemma-4-31b",
  messages: [{ role: "user", content: "Count to five." }],
  stream: true,
});
for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}

curl -N https://api.withhopper.com/v1/chat/completions \
  -H "Authorization: Bearer sk_hopper_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemma-4-31b",
    "messages": [{"role": "user", "content": "Count to five."}],
    "stream": true
  }'

Streaming responses carry only x-hopper-credits-remaining-usd, set to the pre-request balance; the cost of a stream is not known until it ends. Non-streaming responses carry both headers.

For voice agents: hopper-client

hopper-client is a drop-in wrapper around the OpenAI SDK for turn-taking workloads: it holds one warm HTTP/2 connection per process with a 300 s keepalive, so the connection survives conversational gaps instead of re-handshaking on the next turn. Measurements are in the blog post.

pip install hopper-client

from hopper import AsyncHopper

# initialize once, at startup — reused for every turn
client = AsyncHopper(
    base_url="https://api.withhopper.com/v1",
    api_key="sk_hopper_...",
)

Next steps

Models — the catalog: gemma-4-31b, omnivoice, nemotron-asr
Generate speech — 24 kHz streaming TTS
Transcription — batch and streaming speech to text
Pricing — $1 per million input tokens and $3 per million output tokens for the LLM; per-character TTS and per-audio-hour STT

Get started

LLM

Text to Speech

Speech to Text

Platform