Fugu Ultra 1.1 vs MiMo-V2.6 Pro

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 Ultra 1.1 and MiMo-V2.6 Pro, side by side, on 24 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 Ultra 1.1 · Benched on GoldieBench via Sakana's Responses API (fugu-ultra-v1.1, xhigh reasoning). Game tasks use the skill-infused threejs-game-director prompt plus a controls+graphics fix loop with an anti-regression clamp, judged on a real mid-play frame by the same Opus judge as the field.

MiMo-V2.6 Pro · Benched on all 50 GoldieBench tasks through OpenRouter at the model's default reasoning effort: one-shot build, real rendered poster, Opus 4.8 vision judge, game tasks skill-infused. No retries, no hand fixes; the broken builds are scored as they shipped.

Where Fugu Ultra 1.1 beat MiMo-V2.6 Pro

The tasks where I gave Fugu Ultra 1.1 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where MiMo-V2.6 Pro beat Fugu Ultra 1.1

The tasks where I gave MiMo-V2.6 Pro 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 23 scored shared tasks, Fugu Ultra 1.1 averaged 6.94/10, beating MiMo-V2.6 Pro's 5.42/10 by 1.52 points. Pick Fugu Ultra 1.1 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 Ultra 1.1 and MiMo-V2.6 Pro both into the Agent Operating System and dispatch each from the kanban by task type — hard, high-stakes coding and reasoning where answer quality beats latency → Fugu Ultra 1.1, simulations, shaders and visual scenes in one shot, at a fraction of frontier prices → MiMo-V2.6 Pro. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Fugu Ultra 1.1 vs MiMo-V2.6 Pro

Which is better, Fugu Ultra 1.1 or MiMo-V2.6 Pro?

On Goldie Bench, Fugu Ultra 1.1 averages 6.94/10 across the shared tasks, with 0 gold, 1 silver, 1 bronze overall. MiMo-V2.6 Pro averages 5.42/10, with 5 gold, 8 silver, 4 bronze. Fugu Ultra 1.1 wins the head-to-head 13–8.

How much does Fugu Ultra 1.1 cost vs MiMo-V2.6 Pro?

Fugu Ultra 1.1: Sakana's Fugu Ultra v1.1 — a multi-agent system served as a model: an orchestrator routes each request across one to three expert agents and synthesises the answer. Reported (v1.0): SWE-Bench Pro 73.7, LiveCodeBench 93.2, GPQA Diamond 95.5. NOTE: Sakana geo-blocks the EU/EEA/UK/Switzerland pending GDPR compliance — benched from an allowed region. MiMo-V2.6 Pro: Xiaomi's September 2026 open-weight flagship (MIT licence, 1.02T total / 42B active parameters). $0.435 per million input tokens and $0.87 per million output on OpenRouter, with cache hits at a fraction of a cent, which is roughly a quarter of Grok 4.7 and a twentieth of the closed frontier models it scores level with on agent benchmarks.

What's the context window for Fugu Ultra 1.1 vs MiMo-V2.6 Pro?

Fugu Ultra 1.1 has a 1,000,000-token context window context window. MiMo-V2.6 Pro has a 1,000,000 tokens context window.

When should I pick Fugu Ultra 1.1 over MiMo-V2.6 Pro?

Pick Fugu Ultra 1.1 for: Hard, high-stakes coding and reasoning where answer quality beats latency; Agentic workflows in Codex / Claude Code via the drop-in provider config; One-shot builds you want a panel of experts on, not a single model. The trade-off is the weaknesses we logged on the bench: Benched as a partial run until the full 50-task batch completes; Region-locked: unavailable across the EU/EEA/UK/CH — access depends on where you are.

When should I pick MiMo-V2.6 Pro over Fugu Ultra 1.1?

Pick MiMo-V2.6 Pro for: Simulations, shaders and visual scenes in one shot, at a fraction of frontier prices; High-volume agent work where an open, MIT-licensed model matters; Pair it with a self-fix loop for games: the failures are single broken tokens, not missing ideas. The trade-off is the weaknesses we logged on the bench: 18 of 50 builds scored under 5: long game files shipped with garbled tokens (a stray 'martin' or 'martial' identifier breaks the whole script), uninitialised references and bad canvas values, so the HUD paints but the 3D scene stays black; Two hard crashes: the RPG threw an engine fault on load and the solar system rendered nothing at all; It reasons for a long time at default effort: builds took 5 to 60 minutes each through OpenRouter.

How does Goldie Bench score Fugu Ultra 1.1 vs MiMo-V2.6 Pro?

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 Ultra 1.1 · MiMo-V2.6 Pro · back to the leaderboard