How to Use Space Bunny Alpha for Coding: Setup, Tests, and Free Limits

Related integration page and current specifications: BeatAPI

To learn how to use Space Bunny Alpha for coding, choose a hosted API or a client such as OpenCode, then test one small repair. It is currently available as a free-preview coding model. Choose the access route first: BeatAPI uses space-bunny-alpha, OpenRouter uses stealth/space-bunny-alpha, and OpenCode Zen lists space-bunny-free. A key, model ID, and base URL from different services will not form a valid configuration.

This guide takes you from model selection to a small, verifiable code-repair task. It also explains slow or verbose output, rate limits, capacity failures, and what to do if the preview disappears. Documentation was checked on September 30, 2026. The API and client examples are documentation-based; we have not executed authenticated model calls for this guide.

• Free currently means zero model token price, not guaranteed permanent access or unlimited capacity.
• Start with a small task and an explicit test; avoid judging the model by a long explanation.
• On BeatAPI, reasoning_effort defaults to max. Evaluate low for a simple repair.
• Handle 429 and temporary 503 separately, and cap retries.
• Keep a named fallback and require approval before a free workflow incurs paid usage.

How to use Space Bunny Alpha: choose one route

Route	Model ID	API base URL	What to verify
BeatAPI	space-bunny-alpha	https://api.beatapi.io/v1	Free-model request limits and current account availability.
OpenRouter	stealth/space-bunny-alpha	https://openrouter.ai/api/v1	Account limits, preview terms, and route-specific data policy.
OpenCode Zen	space-bunny-free	https://opencode.ai/zen/v1	Current model listing, signup conditions, and limited-time access.

Sources: BeatAPI's model documentation, OpenRouter's listing, and OpenCode Zen documentation. Do not transfer a parameter name, quota, or privacy promise from one route to another without checking it.

The model's maker remains officially unidentified in the listing. Its advertised 1M context and multimodal input do not establish that it is a particular announced model or that it produces images or video. For the background and identity evidence, read What Is Space Bunny?; this article focuses on completing a coding task.

Start in OpenCode

If you already use OpenCode, open it in a small test repository. Run /connect, choose OpenCode Zen, and follow its account connection steps. Then run /models and choose Space Bunny Free. The route's model ID is space-bunny-free; within OpenCode's provider/model syntax the selection is:

opencode -m opencode/space-bunny-free

If the model is missing, update OpenCode and refresh the model list before changing your credentials or inventing an alias:

opencode upgrade
opencode models --refresh

These commands and provider/model conventions follow the CLI reference and model configuration guide. Availability can change during the preview, so a missing listing may be real rather than a local cache problem.

For OpenRouter inside OpenCode, connect to OpenRouter using its key and choose the corresponding listing instead. The model selection is openrouter/stealth/space-bunny-alpha. That is an OpenCode selection string; the direct OpenRouter API request still uses stealth/space-bunny-alpha.

Free token pricing does not establish that every account can be opened without funding or that auxiliary models used by a coding client are also free. Inspect signup conditions, title-generation models, and automatic top-ups separately before running unattended work.

Call the BeatAPI endpoint directly

For a minimal Python example, install the OpenAI SDK and set BEATAPI_API_KEY in your environment. The key is sent only to BeatAPI's endpoint.

python -m pip install --upgrade openai

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["BEATAPI_API_KEY"],
    base_url="https://api.beatapi.io/v1",
    timeout=180.0,
    max_retries=0,
)
completion = client.chat.completions.create(
    model="space-bunny-alpha",
    reasoning_effort="low",
    max_tokens=8192,
    messages=[{
        role: "user",
        content: (
            "Review this function for a missing final chunk:\n"
            "def chunk(items, size):\n"
            "    return [items[i:i+size] "
            "for i in range(0, len(items)-size, size)]\n"
            "Assume size must be a positive integer. "
            "Return the corrected function and three tests. "
            "Keep the explanation under 100 words."
        ),
    }],
)
choice = completion.choices[0]
print("finish_reason:", choice.finish_reason)
print(choice.message.content)
if completion.usage is not None:
    print(completion.usage.model_dump())

The model ID, endpoint, reasoning setting, and rate-limit behavior follow BeatAPI's public contract. The SDK's retries are disabled here so that a test does not silently multiply requests; your application can add a bounded policy after inspecting actual errors. If finish_reason indicates truncation, do not treat the partial function as finished.

Use the Space Bunny Alpha integration page for the current setup and limits. The request asks for code as text; it does not grant access to your repository or run tests automatically.

A code-repair task with a clear acceptance check

The buggy loop stops before the final starting position. For five items and a chunk size of two, it returns only the first four items; for exactly two items and a size of two, it returns no chunks at all. A valid implementation should start slices through the full input and reject a non-positive size.

Use this as the acceptance specification, written before requesting a patch:

def verify(chunk):
    assert chunk([1, 2, 3, 4, 5], 2) == [[1, 2], [3, 4], [5]]
    assert chunk([1, 2], 2) == [[1, 2]]
    assert chunk([], 2) == []
    for size in (0, -1):
        try:
            chunk([1], size)
        except ValueError:
            pass
        else:
            raise AssertionError("non-positive size must raise ValueError")

A reference implementation for the declared positive-integer contract is:

def chunk(items, size):
    if size <= 0:
        raise ValueError("size must be positive")
    return [items[i:i + size] for i in range(0, len(items), size)]

verify(chunk)

The reference and acceptance checks were run locally. They establish the exercise's expected behavior; they are not a Space Bunny-generated result. When you run the model example, execute the tests against its returned patch and inspect the diff. If it changes the tests to hide a failure, reject that attempt.

In OpenCode, use a task prompt that includes the same criteria:

Fix only chunk.py so it preserves the final partial chunk and rejects
non-positive chunk sizes. Do not edit the tests or add dependencies.
Run the existing tests. Return the patch, the actual test result, and a
summary under 100 words. If a tool fails, report the failure instead of
claiming that the tests passed.

This exercise is deliberately small. It separates model correctness, client tool execution, and explanatory verbosity without giving an anonymous preview unrestricted production work.

Why does it think so much or answer too long?

A Kilo user report describes useful routine coding results alongside very verbose answers. That is firsthand experience, not a controlled benchmark, but it identifies a practical configuration question.

On BeatAPI, reasoning is always enabled and the documented default effort is max. For a simple repair, compare low with the default while holding the task and acceptance checks constant. Lower effort may reduce latency, but does not guarantee an equivalent result. A concise output instruction controls what you request in the answer; it does not turn internal reasoning off.

Limit the task scope, give the failing test, exclude unrelated files, and specify the final format. Record elapsed time, finish reason, tests passed, and returned token usage. A short-looking answer can still involve substantial reasoning; a long answer can still contain a wrong patch.

Free limits, errors, and fallback behavior

BeatAPI currently documents 1 successful free-model request per minute before a first top-up, and at most 10 requests per minute after any top-up, independent of the amount paid. Free calls have their own allowance. Funding the account changes that documented request limit; it does not buy a stronger Space Bunny model or establish a concurrent-request guarantee.

Symptom	Next step
401	Check which service issued the key and which endpoint you called.
Model missing or unavailable	Inspect the current account model list; verify the exact route's ID.
429 on BeatAPI	Respect Retry-After, then retry within a bounded attempt limit.
503 processing_unavailable	Temporary capacity can fail even below your request limit; wait briefly, cap retries, then surface the failure.
Truncated or empty final output	Inspect finish reason and budget before retrying the task.
Plausible patch, failing tests	Return the actual failure to the agent; stop after the turn cap.

Use GET /v1/models to check availability before depending on the preview. Do not reroute a limited free request to a paid model silently. A fallback policy should name the alternative, maximum budget, and the action requiring approval. For example: after two temporary failures, offer to run the task with a named paid model at a capped budget, or let the user wait.

Frequently asked questions

Is Space Bunny permanently free?

No permanence is promised. OpenCode calls it limited-time, and anonymous previews can be withdrawn. Build the application so the model is replaceable.

Is it MiniMax M3.1 or another named model?

Its developer is not officially identified in the listing. Similar behavior or tokenizer clues do not establish a confirmed model version.

Can I use the same ID everywhere?

No. Use the route table above. The OpenCode provider prefix is also different from a raw API model ID.

Does a top-up make it smarter?

BeatAPI's published change concerns request limits. It is not a quality upgrade to the model.

Is confidential code safe to send?

Review the exact access route's current data terms. OpenCode's model-specific zero-retention wording and OpenRouter's retention wording are different. A promise on one route does not apply to another; start the exercise with public or synthetic code.

What should I do after the first successful task?

Repeat on a few small tasks with known checks, then record correctness, retries, and latency. Use the integration guide for configuration and the model overview for current capability context before adopting it in a larger workflow.

If you decide to evaluate a paid alternative, the GPT-6.1 Sol integration guide provides a separate setup and cost worksheet.

Disclosure: We build BeatAPI. This article distinguishes documentation-based examples from tests actually executed; it does not report a model benchmark.