
Real head-to-head · same prompt, one shot
Fugu Ultra vs MiMo-V2.6 Pro
Sakana's multi-agent answer to Fusion — frontier ensemble without single-vendor risk. vs Open weights that score level with Opus 5 on agents, for cents.
Head-to-head verdict: MiMo-V2.6 Pro wins 22–20.
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 and MiMo-V2.6 Pro, side by side, on 42 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 · Dispatched from Agent OS as the panel-ensemble alternative to OpenRouter Fusion. Bench scored by Claude judge against the same 42 prompts as every other model.
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.
Side-by-side on 50 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 Ultra
MiMo-V2.6 Pro
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Page
Page
Sim
Sim
Sim
Where Fugu Ultra beat MiMo-V2.6 Pro
The tasks where I gave Fugu Ultra a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
Solar
Sim
Fugu Ultra 9.0
·
MiMo-V2.6 Pro 1.5
(+7.5)
· winner · panel polish
What I saw: Fugu Ultra v2 rebuild — 55.7KB solar system, the densest solar attempt on the bench. Full </html>, animation loop, Saturn rings, drag-to-orbit + scroll-to-zoom. Smoke-test PASS (3.6% pixel diff after drag, zero console errors). The panel ensemble produces a markedly richer build …
Rpg
Game
Fugu Ultra 8.0
·
MiMo-V2.6 Pro 1.5
(+6.5)
What I saw: Ultra v2 (gap-fill) — top-down RPG with tilemap + NPCs. Smoke-test PASS (1.1% diff).
Twilightvale
Game
Fugu Ultra 9.0
·
MiMo-V2.6 Pro 3.0
(+6.0)
· winner · open-world depth
What I saw: Ultra v2 — 61.8KB open-world RPG (village, NPCs, weather, day/night). Smoke-test PASS. Densest Ultra build on the bench.
Nordiccrypt
Game
Fugu Ultra 9.0
·
MiMo-V2.6 Pro 3.2
(+5.8)
· winner · dungeon depth
What I saw: Ultra v2 (gap-fill) — 61.5KB Nordic dungeon crawler with bloom + boss room. Smoke-test PASS with 22.8% pixel diff — highly reactive.
Pathtracer
Sim
Fugu Ultra 8.5
·
MiMo-V2.6 Pro 3.0
(+5.5)
What I saw: Ultra v2 — WebGL path tracer with sample accumulation. Smoke-test PASS (4.1% pixel diff).
Where MiMo-V2.6 Pro beat Fugu Ultra
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.
Neonblaster
Game
MiMo-V2.6 Pro 8.7
·
Fugu Ultra 6.5
(+2.2)
· 3D neon top-shooter
What I saw: Renders a gorgeous 3D synthwave arena with detailed ship, glowing perspective grid, floating debris, and a fully polished HUD (hull/shield/boost meters, radar, boss bar, combo) backed by scheduled synth music and juicy SFX. Strong on-brief execution that rivals the field best; on…
Lavalamp
Visual
MiMo-V2.6 Pro 8.7
·
Fugu Ultra 7.0
(+1.7)
· raymarched lava lamp
What I saw: Gorgeous raymarched metaball lava lamp with a proper glass vessel, cap, base, warm bulb glow and molten blobs at varied heights — clearly reads as an authentic lava lamp; the classic silhouette, glass refraction and polished typography make this a top-tier entry.
Webos
Page
MiMo-V2.6 Pro 8.7
·
Fugu Ultra 7.0
(+1.7)
· Polished nebula desktop
What I saw: Strikingly polished render with layered windows (Notes/Terminal/Paint), a full paint toolbar with working color/brush controls and beautiful sample strokes, animated 3D-object wallpaper, top menubar, dock, live clock and system-monitor widgets — clearly on-brief and top-tier; onl…
Arcade
Game
MiMo-V2.6 Pro 8.6
·
Fugu Ultra 7.0
(+1.6)
· 3D neon snake
What I saw: Stunning 3D reinterpretation of Snake as a WebGL arena viper — polished lighting, segmented tail, working minimap, pickups, and clean neon HUD all render crisply. Strong on-brief execution that clearly outclasses the flat 2D field; only slight risk is that the elaborate combat fr…
Dogfight
Game
MiMo-V2.6 Pro 8.6
·
Fugu Ultra 7.0
(+1.6)
· polished 3D dogfight
What I saw: Renders a gorgeous low-poly 3D world with detailed player jet, chase cam, floating clouds, terrain props, an enemy bogey in view, and a fully realized HUD (radar, throttle, afterburner, hull). Cohesive military-flight aesthetic and rich mechanics make this a task-topper; only min…
Strengths & weaknesses I logged
Fugu Ultra
Strengths
- SWE Bench Pro 73.7 · GPQA-D 95.5 · MRCRv2 93.6 — Sakana's published frontier-tier benchmark scores
- Vendor-agnostic ensemble — opt out of specific providers for compliance / export-control
- OpenAI-compatible API at api.sakana.ai — drop-in for existing tooling
Trade-offs
- Panel orchestration adds latency — even a 'pong' burns ~2k orchestration tokens
- Newer than Fusion; less community calibration on long-tail prompts
MiMo-V2.6 Pro
Strengths
- Simulations and visual pieces are top-tier one-shots: the black hole lensing scored 9.0 and the matrix rain, lava lamp, ocean waves, web desktop, boids and galaxy all landed 8.6 or higher
- Strong flight and driving output when the build holds together: a polished 3D dogfight (8.6), a flight sim (8.4) and the synthwave outrun (8.4)
- Big, complete files: builds ran 30 to 70 KB with full HUDs, control hints and settings panels
- The weights are MIT and on Hugging Face, so the same model can run on your own hardware
Trade-offs
- 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
Pricing & context — the spec sheet
| Spec | Fugu Ultra | MiMo-V2.6 Pro |
|---|---|---|
| Vendor | Sakana AI | Xiaomi |
| Context window | 272,000 tokens with the standard rate. Calls exceeding 272K context are billed at the higher 'long-context' rates. | 1,000,000 tokens |
| Price | $5 / 1M input · $30 / 1M output (Fugu Ultra) | $0.435 in / $0.87 out per M tokens |
| Pricing detail | Sakana's multi-agent orchestration: a single API call internally dispatches to multiple frontier models and synthesises the answer. Subscription plans run $20-$200/mo (Standard / Pro / Max); PAYG is $5/M input + $30/M output for Fugu Ultra. Direct competitor to OpenRouter Fusion's panel approach. | 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. |
| Release | 2026-06-15 | 2026-09 |
| Bench coverage | 42/42 scored · avg 7.94/10 | 50/50 scored · avg 6.35/10 |
The verdict — which should you pick?
Across 42 scored shared tasks, Fugu Ultra averaged 7.94/10, beating MiMo-V2.6 Pro's 6.50/10 by 1.45 points. Pick Fugu Ultra 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 and MiMo-V2.6 Pro both into the Agent Operating System and dispatch each from the kanban by task type — teams that want fusion-class quality but need a different vendor risk profile → Fugu Ultra, 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 vs MiMo-V2.6 Pro
Which is better, Fugu Ultra or MiMo-V2.6 Pro?
On Goldie Bench, Fugu Ultra averages 7.94/10 across the shared tasks, with 5 gold, 2 silver, 2 bronze overall. MiMo-V2.6 Pro averages 6.50/10, with 5 gold, 8 silver, 4 bronze. MiMo-V2.6 Pro wins the head-to-head 22–20.
How much does Fugu Ultra cost vs MiMo-V2.6 Pro?
Fugu Ultra: Sakana's multi-agent orchestration: a single API call internally dispatches to multiple frontier models and synthesises the answer. Subscription plans run $20-$200/mo (Standard / Pro / Max); PAYG is $5/M input + $30/M output for Fugu Ultra. Direct competitor to OpenRouter Fusion's panel approach. 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 vs MiMo-V2.6 Pro?
Fugu Ultra has a 272,000 tokens with the standard rate. Calls exceeding 272K context are billed at the higher 'long-context' rates. context window. MiMo-V2.6 Pro has a 1,000,000 tokens context window.
When should I pick Fugu Ultra over MiMo-V2.6 Pro?
Pick Fugu Ultra for: Teams that want Fusion-class quality but need a different vendor risk profile; Operators avoiding export-controlled providers (Sakana emphasises this in their pitch); Deep-research workflows where ensemble verdicts beat single-model answers. The trade-off is the weaknesses we logged on the bench: Panel orchestration adds latency — even a 'pong' burns ~2k orchestration tokens; Newer than Fusion; less community calibration on long-tail prompts.
When should I pick MiMo-V2.6 Pro over Fugu Ultra?
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 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:
Fugu Ultra vs Fusion MiMo-V2.6 Pro vs Fusion Fugu Ultra vs Claude Opus 5 MiMo-V2.6 Pro vs Claude Opus 5 Fugu Ultra vs Hermes MoA MiMo-V2.6 Pro vs Hermes MoA Fugu Ultra vs GPT-5.6 Sol MiMo-V2.6 Pro vs GPT-5.6 SolFull model pages: Fugu Ultra · MiMo-V2.6 Pro · back to the leaderboard
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 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.
4,000+founders
258documented wins
38countries
$59/momonthly














































