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

Fusion vs Kimi K2.7 · Fast

Multi-model panel — Fable 5 + GPT-5.5, ensembled. Beats Fable 5 at half the price. vs Fast mode — top speed, minimal thinking.

Fusion · contextVaries (per-panel)
Kimi K2.7 · Fast · context256K tokens
Fusion · priceOpenRouter Fusion API pricing
Kimi K2.7 · Fast · priceFlat plan (no per-token bill)
Fusion · vendorOpenRouter
Kimi K2.7 · Fast · vendorMoonshot AI

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 Fusion and Kimi K2.7 · Fast, side by side, on 3 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.

Fusion · Dispatched from Agent OS for research-heavy prompts where ensemble accuracy outweighs single-model speed.

Kimi K2.7 · Fast · Wired into Agent OS as the snappy default — first-pass attempts, agent chatter, live demos.

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 ↓
Fusion
Kimi K2.7 · Fast
Game
🥈Fusion on Game
Kimi K2.7 · Fast on Game
Sim
🥇Fusion on Galaxy
Kimi K2.7 · Fast on Galaxy
Sim
🥇Fusion on Solar
Kimi K2.7 · Fast on Solar
Game
🥇Fusion on Arcade
— not attempted —
Game
🥇Fusion on Crypt
— not attempted —
Game
🥉Fusion on Dogfight
— not attempted —
Game
🥇Fusion on Doom
— not attempted —
🥉Fusion on Dragonflight
— not attempted —
🥇Fusion on Dragonrealm
— not attempted —
Fusion on Neonblaster
— not attempted —
Game
🥈Fusion on Neoncity
— not attempted —
Game
🥇Fusion on Neonracer
— not attempted —
🥈Fusion on Nordiccrypt
— not attempted —
Game
🥉Fusion on Outrun
— not attempted —
Game
🥇Fusion on Pool
— not attempted —
Game
🥉Fusion on Racing
— not attempted —
Game
🥇Fusion on Raycaster
— not attempted —
Game
🥈Fusion on Rpg
— not attempted —
Game
🥈Fusion on Skyrim
— not attempted —
Fusion on Twilightvale
— not attempted —
Game
🥇Fusion on Voxelcraft
— not attempted —
Page
🥇Fusion on Landing
— not attempted —
Page
🥇Fusion on Webos
— not attempted —
Sim
🥇Fusion on Blackhole
— not attempted —

Strengths & weaknesses I logged

Fusion

Strengths

  • Premium Fusion panel scored 69.0% on DRACO deep-research benchmark — beats solo Fable 5 by +3.7 points
  • Budget panel ties Fable 5 at ~64.7% for roughly half the cost
  • Vendor-agnostic — model panel can swap as new frontier releases land

Trade-offs

  • Ensemble latency higher than any single model (panel calls run in parallel but the slowest still gates the response)
  • No per-task goldiebench scoring yet — bench rank pending

Kimi K2.7 · Fast

Strengths

  • Lowest latency of the three Kimi modes for short builds
  • Same 256K context as Quality mode
  • Best when you need agent-loop responsiveness over polish

Trade-offs

  • Skips deeper reasoning passes — bronze-tier on tasks needing planning
  • Julian explicitly does not assign scores to Kimi modes on the standalone bench

Pricing & context — the spec sheet

Spec Fusion Kimi K2.7 · Fast
VendorOpenRouterMoonshot AI
Context windowVaries — depends on which panel models are dispatched256,000 tokens
PriceOpenRouter Fusion API pricingFlat plan (no per-token bill)
Pricing detailOpenRouter's Fusion API dispatches a single prompt to multiple frontier models and ensembles the answers. Premium panel: Fable 5 + GPT-5.5. Budget panel: cheaper open-weights models. Roughly half the per-token cost of a Fable 5 solo call.Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model.
Release2026-06-142026-06
Bench coverage42/42 scored · avg 8.00/100/3 scored · avg —

The verdict — which should you pick?

Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.

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 Fusion and Kimi K2.7 · Fast both into the Agent Operating System and dispatch each from the kanban by task type — deep-research workflows where panel consensus beats single-model answers → Fusion, snappy iteration inside agent loops → Kimi K2.7 · Fast. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Fusion vs Kimi K2.7 · Fast

Which is better, Fusion or Kimi K2.7 · Fast?

On Goldie Bench, Fusion averages no scored verdicts yet across the shared tasks, with 27 gold, 8 silver, 4 bronze overall. Kimi K2.7 · Fast averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.

How much does Fusion cost vs Kimi K2.7 · Fast?

Fusion: OpenRouter's Fusion API dispatches a single prompt to multiple frontier models and ensembles the answers. Premium panel: Fable 5 + GPT-5.5. Budget panel: cheaper open-weights models. Roughly half the per-token cost of a Fable 5 solo call. Kimi K2.7 · Fast: Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model.

What's the context window for Fusion vs Kimi K2.7 · Fast?

Fusion has a Varies — depends on which panel models are dispatched context window. Kimi K2.7 · Fast has a 256,000 tokens context window.

When should I pick Fusion over Kimi K2.7 · Fast?

Pick Fusion for: Deep-research workflows where panel consensus beats single-model answers; Cost-sensitive operators who want Fable-5-class output at ~half the bill; Production agents that benefit from vendor-redundancy on every call. The trade-off is the weaknesses we logged on the bench: Ensemble latency higher than any single model (panel calls run in parallel but the slowest still gates the response); No per-task goldiebench scoring yet — bench rank pending.

When should I pick Kimi K2.7 · Fast over Fusion?

Pick Kimi K2.7 · Fast for: Snappy iteration inside agent loops; Short prompts where Quality mode would over-think; Live demos where latency matters more than the last 5% of polish. The trade-off is the weaknesses we logged on the bench: Skips deeper reasoning passes — bronze-tier on tasks needing planning; Julian explicitly does not assign scores to Kimi modes on the standalone bench.

How does Goldie Bench score Fusion vs Kimi K2.7 · Fast?

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
$100k+/mocommunity MRR