Fugu Mini vs Kimi K2.7

What I tested — same prompt, two models

I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Fugu Mini and Kimi K2.7, side by side, on 16 shared tasks inside the Agent Operating System.

Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.

Fugu Mini · Dispatched from Agent OS as the fast Sakana lane. Bench scored by Claude judge against the same 42 prompts.

Kimi K2.7 · Wired into the Agent OS as the heavy-lifter for game/sim prototypes and Kanban-dispatched code work. Mode toggled per task: Quality for one-shot games, Fast for short bursts.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 1 scored shared tasks, the averages are essentially tied — Fugu Mini 8.00 vs Kimi K2.7 8.00. This isn't the comparison where one wins; it's the comparison where you pick based on context, pricing, and what you're actually trying to ship.

If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Fugu Mini and Kimi K2.7 both into the Agent Operating System and dispatch each from the kanban by task type — agent loops where latency matters more than panel consensus → Fugu Mini, interactive game prototypes you want shippable on the first prompt → Kimi K2.7. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Fugu Mini vs Kimi K2.7

Which is better, Fugu Mini or Kimi K2.7?

On Goldie Bench, Fugu Mini averages 8.00/10 across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. Kimi K2.7 averages 8.00/10, with 3 gold, 2 silver, 2 bronze. It's a curated tie on the head-to-head.

How much does Fugu Mini cost vs Kimi K2.7?

Fugu Mini: The non-Ultra `fugu` model on Sakana's API. Sakana describes it as 'Fast mini model optimized for low latency yet high quality responses.' Crucially: zero orchestration tokens per call (vs Ultra's panel of thousands). Returns in ~3 min instead of 6-15 min and doesn't time out on heavy prompts. Kimi K2.7: Available on Moonshot's flat-rate subscription plan — no per-token billing for individual builders. The plan covers all three speed modes (Fast, No-Think, Quality).

What's the context window for Fugu Mini vs Kimi K2.7?

Fugu Mini has a Single-model variant of Sakana's Fugu — no panel orchestration. Same API endpoint, much faster per call. context window. Kimi K2.7 has a 256,000 tokens context window.

When should I pick Fugu Mini over Kimi K2.7?

Pick Fugu Mini for: Agent loops where latency matters more than panel consensus; Quick first-drafts you'll refine downstream; Filling out a bench when Ultra is timing out. The trade-off is the weaknesses we logged on the bench: Single model only — no ensemble verdict; Newer than Ultra — less calibration / verification.

When should I pick Kimi K2.7 over Fugu Mini?

Pick Kimi K2.7 for: Interactive game prototypes you want shippable on the first prompt; High-iteration agent loops where per-token cost would dominate; Long-context refactors using the 256K window inside Agent OS. The trade-off is the weaknesses we logged on the bench: Plays plainest on abstract visual prompts — synthwave grids, fluid sims, aurora — where GLM and Opus add more flair; Bronze average on the {{SITE_NAME}} bench despite the gold-medal games — its visual builds are accurate but understated.

How does Goldie Bench score Fugu Mini vs Kimi K2.7?

Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.

Related comparisons

Other head-to-heads using the same scoring system:

Full model pages: Fugu Mini · Kimi K2.7 · back to the leaderboard