Real head-to-head · same prompt, one shot

Fugu Mini vs Hy3

Fugu's fast mini variant — single model, no panel, ~3 min per build. vs Tencent's open-weights coder — Apache-2.0, cheap, beats GLM-5.1 on frontend in Tencent's blind eval.

Head-to-head verdict: Fugu Mini wins 2–0.

Fugu Mini · contextSakana subscription · same key as Ultra
Hy3 · context262K tokens
Fugu Mini · priceSame Sakana subscription pool as Fugu Ultra
Hy3 · price$0.14 / 1M input · $0.58 / 1M output
Fugu Mini · vendorSakana AI
Hy3 · vendorTencent Hunyuan

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 Hy3, side by side, on 2 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.

Hy3 · Wired into the Agent OS as the 'Hy3 Coder' tab (chat + live preview + workspace) via OpenRouter. Bench built one-shot on the same prompts as the field; weak builds iterated by Hy3 itself (the model fixes its own builds).

Side-by-side on 42 shared tasks

Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).

Task ↓
Fugu Mini
Hy3
Game
Fugu Mini on Doom
Hy3 on Doom
Fugu Mini on Dragonrealm
Hy3 on Dragonrealm
Game
🥈Fugu Mini on Arcade
— not attempted —
Game
Fugu Mini on Dogfight
— not attempted —
Fugu Mini on Dragonflight
— not attempted —
Game
— not attempted —
🥈Hy3 on Flightsim
Game
🥇Fugu Mini on Game
— not attempted —
Game
— not attempted —
Hy3 on Gtadrive
Game
— not attempted —
Hy3 on Gtafoot
Game
🥈Fugu Mini on Neoncity
— not attempted —
Game
Fugu Mini on Neonracer
— not attempted —
Fugu Mini on Nordiccrypt
— not attempted —
Game
🥉Fugu Mini on Outrun
— not attempted —
Game
— not attempted —
Hy3 on Parachute
Game
Fugu Mini on Racing
— not attempted —
Game
Fugu Mini on Raycaster
— not attempted —
Game
Fugu Mini on Rpg
— not attempted —
Game
Fugu Mini on Skyrim
— not attempted —
Page
— not attempted —
Hy3 on Aipbpromo
Page
Fugu Mini on Landing
— not attempted —
Page
Fugu Mini on Webos
— not attempted —
Sim
Fugu Mini on Blackhole
— not attempted —
Sim
Fugu Mini on Boids
— not attempted —
Sim
Fugu Mini on Cloth
— not attempted —

Where Fugu Mini beat Hy3

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

Doom Game
Fugu Mini 8.0 · Hy3 5.5 (+2.5)

What I saw: Doom-style raycaster FPS with sprite enemies. Smoke-test PASS (pixel change after click+keys).

Fugu Mini 8.0 · Hy3 7.2 (+0.8)

What I saw: Skyrim-style frozen open world with HUD. Smoke-test PASS.

Strengths & weaknesses I logged

Fugu Mini

Strengths

  • Zero panel orchestration — much lower latency than Ultra
  • Same Sakana subscription, no extra cost
  • Doesn't time out on heavy game/3D prompts where Ultra stalls

Trade-offs

  • Single model only — no ensemble verdict
  • Newer than Ultra — less calibration / verification

Hy3

Strengths

  • Apache-2.0 open weights — self-host free, no lock-in
  • Tencent's 270-expert blind eval: 2.67/4 vs GLM-5.1's 2.51, strongest on frontend / data / CI-CD
  • Hallucination rate cut 12.5% → 5.4%; stable tool-calls across scaffoldings (<4% SWE-Bench variance)

Trade-offs

  • Slow upstream on OpenRouter (30-90s per build) — fine for one-shots, sluggish for tight loops
  • One-shot game builds can under-render (flat raycaster walls, unlit 3D) without an iterate pass

Pricing & context — the spec sheet

Spec Fugu Mini Hy3
VendorSakana AITencent Hunyuan
Context windowSingle-model variant of Sakana's Fugu — no panel orchestration. Same API endpoint, much faster per call.262,144-token context window. Open weights (Apache-2.0) on HuggingFace / ModelScope / GitHub; benched here via OpenRouter.
PriceSame Sakana subscription pool as Fugu Ultra$0.14 / 1M input · $0.58 / 1M output
Pricing detailThe 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.Tencent Hunyuan 3 — open-weights under Apache-2.0, so free to self-host. On OpenRouter it is one of the cheapest capable coders: ~$0.14/M in, $0.58/M out (1 RMB / 4 RMB). Upstream can be slow (30-90s to first token), but per-token cost is negligible.
Release2026-06-152026-07-06
Bench coverage36/37 scored · avg 7.75/107/7 scored · avg 7.13/10

The verdict — which should you pick?

Across 2 scored shared tasks, Fugu Mini averaged 8.00/10, beating Hy3's 6.35/10 by 1.65 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 Hy3 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, cost-sensitive coding + frontend design where open weights matter → Hy3. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Fugu Mini vs Hy3

Which is better, Fugu Mini or Hy3?

On Goldie Bench, Fugu Mini averages 8.00/10 across the shared tasks, with 2 gold, 4 silver, 2 bronze overall. Hy3 averages 6.35/10, with 0 gold, 1 silver, 0 bronze. Fugu Mini wins the head-to-head 2–0.

How much does Fugu Mini cost vs Hy3?

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. Hy3: Tencent Hunyuan 3 — open-weights under Apache-2.0, so free to self-host. On OpenRouter it is one of the cheapest capable coders: ~$0.14/M in, $0.58/M out (1 RMB / 4 RMB). Upstream can be slow (30-90s to first token), but per-token cost is negligible.

What's the context window for Fugu Mini vs Hy3?

Fugu Mini has a Single-model variant of Sakana's Fugu — no panel orchestration. Same API endpoint, much faster per call. context window. Hy3 has a 262,144-token context window. Open weights (Apache-2.0) on HuggingFace / ModelScope / GitHub; benched here via OpenRouter. context window.

When should I pick Fugu Mini over Hy3?

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 Hy3 over Fugu Mini?

Pick Hy3 for: Cost-sensitive coding + frontend design where open weights matter; Self-hosters who want an Apache-2.0 model they fully own; Anyone wiring a cheap capable coder into a live build panel (Agent OS Hy3 Coder tab). The trade-off is the weaknesses we logged on the bench: Slow upstream on OpenRouter (30-90s per build) — fine for one-shots, sluggish for tight loops; One-shot game builds can under-render (flat raycaster walls, unlit 3D) without an iterate pass.

How does Goldie Bench score Fugu Mini vs Hy3?

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.

The same stack Julian uses

Run this stack yourself.

Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.

3,600+founders
258documented wins
38countries
$59/momonthly