How to use the Space Bunny API
Space Bunny Alpha is served through a hosted, OpenAI Chat Completions-compatible API. If you already have code that talks to OpenAI, you only need to change two things — the base URL and your API key — and set the model to space-bunny-alpha.
Get a key
Create a free key to start. New accounts get roughly $1 of credit on signup; after that you top up with credit packs. Keys look like sb_live_... and are sent in the Authorization: Bearer header.
Endpoint
The API is a drop-in OpenAI Chat Completions endpoint. Base URL: https://spacebunnymodel.com/api/v1. Send requests to POST /api/v1/chat/completions with the model set to space-bunny-alpha.
curl
The raw HTTP request — useful for a quick smoke test.
curl https://spacebunnymodel.com/api/v1/chat/completions \
-H "Authorization: Bearer sb_live_..." \
-H "Content-Type: application/json" \
-d '{
"model": "space-bunny-alpha",
"messages": [
{ "role": "user", "content": "In one sentence, what is a space bunny?" }
],
"max_tokens": 4096
}'Python (openai SDK)
Install with pip install openai, then point the client at our base URL.
from openai import OpenAI
client = OpenAI(
base_url="https://spacebunnymodel.com/api/v1",
api_key="sb_live_...",
)
resp = client.chat.completions.create(
model="space-bunny-alpha",
messages=[
{"role": "user", "content": "In one sentence, what is a space bunny?"},
],
# Reasoning model: it thinks before answering, so give it room.
max_tokens=4096,
)
print(resp.choices[0].message.content)JavaScript / TypeScript (openai npm)
Install with npm install openai. The official OpenAI package works unchanged once you set baseURL and apiKey.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://spacebunnymodel.com/api/v1",
apiKey: "sb_live_...",
});
const resp = await client.chat.completions.create({
model: "space-bunny-alpha",
messages: [
{ role: "user", content: "In one sentence, what is a space bunny?" },
],
// Reasoning model: it thinks before answering, so give it room.
max_tokens: 4096,
});
console.log(resp.choices[0].message.content);Streaming
Pass stream: true to receive tokens as they are produced. This works exactly like OpenAI streaming.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://spacebunnymodel.com/api/v1",
apiKey: "sb_live_...",
});
const stream = await client.chat.completions.create({
model: "space-bunny-alpha",
messages: [
{ role: "user", content: "Write a short poem about a rabbit in orbit." },
],
max_tokens: 4096,
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}Using it in opencode
Because the endpoint is OpenAI-compatible, you can wire Space Bunny Alpha into opencode as a custom provider — set the base URL to https://spacebunnymodel.com/api/v1, your sb_live_ key, and the model space-bunny-alpha. See the step-by-step guide at /integrations/opencode.
Notes
- It is a reasoning model. Space Bunny Alpha spends output tokens thinking before it answers, so set a generous
max_tokens(4096+). A low limit can truncate the reply before the final answer is written. - 1M token context. You can pass very large prompts — long documents, full codebases, extended chat history.
- Multimodal input. The model accepts image content in messages alongside text, using the standard OpenAI content-parts format.
- Credits and rate limits. Usage is billed from your prepaid balance; requests are rate limited per key. This is a free upstream preview, so availability and limits may change.
- Prefer no account setup? Space Bunny Alpha is also on OpenRouter as
stealth/space-bunny-alpha. Our hosted endpoint just gives you one stable key and model name without an OpenRouter account.