Kimi K2.7 vs Fugu Mini

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 Kimi K2.7 and Fugu Mini, side by side, on 26 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.

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.

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

Where Kimi K2.7 beat Fugu Mini

The tasks where I gave Kimi K2.7 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 2 scored shared tasks, Kimi K2.7 averaged 7.00/10, beating Fugu Mini's 5.50/10 by 1.50 points. Pick Kimi K2.7 when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.

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 Kimi K2.7 and Fugu Mini both into the Agent Operating System and dispatch each from the kanban by task type — interactive game prototypes you want shippable on the first prompt → Kimi K2.7, agent loops where latency matters more than panel consensus → Fugu Mini. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Kimi K2.7 vs Fugu Mini

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

On Goldie Bench, Kimi K2.7 averages 7.00/10 across the shared tasks, with 3 gold, 2 silver, 2 bronze overall. Fugu Mini averages 5.50/10, with 0 gold, 0 silver, 0 bronze. Kimi K2.7 wins the head-to-head 1–0.

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

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). 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.

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

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

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.

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.

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

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