Fugu Mini vs Inkling

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 Inkling, side by side, on 37 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.

Inkling · Benched on GoldieBench one-shot through Tinker's OpenAI-compatible endpoint at medium reasoning effort, then headless-playtested on the same rubric as the whole field. In the Agent OS it's wired into the opencode tab on your own Tinker key — the Ink Machine.

Where Fugu Mini beat Inkling

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

Where Inkling beat Fugu Mini

The tasks where I gave Inkling 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 36 scored shared tasks, Fugu Mini averaged 7.75/10, beating Inkling's 6.04/10 by 1.71 points. Pick Fugu Mini 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 Fugu Mini and Inkling 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, owning a frontier model instead of renting one — on your own key, pennies per build → Inkling. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Fugu Mini vs Inkling

Which is better, Fugu Mini or Inkling?

On Goldie Bench, Fugu Mini averages 7.75/10 across the shared tasks, with 2 gold, 2 silver, 2 bronze overall. Inkling averages 6.04/10, with 0 gold, 3 silver, 1 bronze. Fugu Mini wins the head-to-head 30–6.

How much does Fugu Mini cost vs Inkling?

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. Inkling: Inkling is open-weights — a 975B-parameter (41B active) Mixture-of-Experts model whose full weights are public on Hugging Face. You run it on your own key through Tinker's OpenAI-compatible endpoint (usage-based, ~$0.33/M sampling, 50% off at launch), or via Together / Fireworks / Modal / Databricks / Baseten. Benched here one-shot at medium reasoning effort via Tinker.

What's the context window for Fugu Mini vs Inkling?

Fugu Mini has a Single-model variant of Sakana's Fugu — no panel orchestration. Same API endpoint, much faster per call. context window. Inkling has a 1,000,000 tokens context window.

When should I pick Fugu Mini over Inkling?

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 Inkling over Fugu Mini?

Pick Inkling for: Owning a frontier model instead of renting one — on your own key, pennies per build; Generative visuals, data-viz and single-file web builds you want one-shot; A customizable open base you can fine-tune on Tinker for your own domain. The trade-off is the weaknesses we logged on the bench: One-shot 3D games are weak — three.js dungeons/racers render a title screen but no playable scene, like most open models (crypt 2.5); Physics and particle sims are hit-or-miss — black-hole, plasma and cloth one-shots often render dark or static (2.3–3.5); Not the strongest overall — the closed frontier (Fable 5) still tops the raw benchmarks; Inkling trades peak for ownership.

How does Goldie Bench score Fugu Mini vs Inkling?

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 · Inkling · back to the leaderboard