pvakati-tech.ai

// head_to_head

Gemini 3.8 Flash vs Space Bunny Alpha

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Space Bunny Alpha is the cheaper of the two; neither can be ranked on quality here.

Space Bunny Alpha does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

google

Gemini 3.8 Flash

Blended / 1M
$1.50
Context
1.0M
Released
Sep 2, 2026
Overall score
75.8
reasoningtool callingimage inputvideo inputfile inputaudio inputprompt caching

stealth

Space Bunny Alpha

Blended / 1M
Free
Context
1M
Released
Sep 23, 2026
Overall score
Not evaluated
reasoningtool callingimage inputvideo input

Specs and pricing

MetricGemini 3.8 FlashSpace Bunny Alpha
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

75.8
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.1750
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$1.50Freewin
Input price / 1M$0.750Freewin
Output price / 1M$3.75Freewin
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.075
Context window1.0M1M
Max output tokens66K524Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Gemini 3.8 Flash on top, Space Bunny Alpha below, both out of 100.

Agentic coding
54.2
Coding
72.5
Reasoning
89.3
Mathematics
91.6
Data analysis
54.0
Language
87.8
Instruction following
81.4

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadGemini 3.8 FlashSpace Bunny Alpha
Support chatbot

1.2K in / 400 out × 200K requests

$431.40/mo$0/mo
RAG assistant

8K in / 600 out × 100K requests

$555.00/mo$0/mo
Coding agent

40K in / 4K out × 20K requests

$522.00/mo$0/mo
Document extraction

20K in / 1.5K out × 50K requests

$997.50/mo$0/mo
Bulk classification

500 in / 20 out × 5M requests

$1,912/mo$0/mo
Run these two through the cost calculator

Which should you pick?

You are cost-constrained

Space Bunny Alpha

Cheaper on blended list price at Free per million tokens.

Gemini 3.8 Flash vs Space Bunny Alpha FAQ

Which is better, Gemini 3.8 Flash or Space Bunny Alpha?

Space Bunny Alpha is the cheaper of the two; neither can be ranked on quality here. Space Bunny Alpha does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

Is Gemini 3.8 Flash cheaper than Space Bunny Alpha?

Space Bunny Alpha is cheaper. On a 3:1 input:output blend, Gemini 3.8 Flash lists at $1.50 per million tokens and Space Bunny Alpha at Free. Input and output are priced separately — Gemini 3.8 Flash charges $0.750 in and $3.75 out, Space Bunny Alpha charges Free and Free — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Gemini 3.8 Flash or Space Bunny Alpha have a bigger context window?

They are effectively the same — 1.0M for Gemini 3.8 Flash and 1M for Space Bunny Alpha.

Do Gemini 3.8 Flash and Space Bunny Alpha support prompt caching?

Gemini 3.8 Flash publishes a cached-input rate of $0.075 per million tokens against a full input rate of $0.750. The catalogue lists no separate cached rate for Space Bunny Alpha, which means the provider does not price it separately here — not that caching is unavailable.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • ScoresLiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.