Fusion vs Kilo Code
Multi-model panel — Fable 5 + GPT-5.5, ensembled. Beats Fable 5 at half the price. vs Fable 5-class intelligence at ~59% less. The split-the-cost play.
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 Kilo Code, side by side, on 0 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.
Kilo Code · Used inside Agent OS as a routing layer: Fable 5 generates the plan, cheaper models execute. Bench scoring pending a head-to-head comparison.
Side-by-side on 0 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 = 🥉).
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
Kilo Code
Strengths
- Kilo's own rubric: Fable 5 plan = 9.1/10, GPT-5.5 plan = 8.3/10 — Kilo isolates where the intelligence actually lives
- Plan quality stays high while execution cost drops
- Drop-in for Agent OS — Kilo Split framework already wired
Trade-offs
- Adds routing complexity — two model providers in one workflow
- No per-task goldiebench head-to-heads yet
Pricing & context — the spec sheet
| Spec | Fusion | Kilo Code |
|---|---|---|
| Vendor | OpenRouter | Kilo |
| Context window | Varies — depends on which panel models are dispatched | Varies — Kilo splits planning from execution across multiple models |
| Price | OpenRouter Fusion API pricing | ~59% less than Fable 5 solo |
| Pricing detail | 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. | Kilo Code is a routing layer that splits planning (heavy model) from execution (cheaper model) so you get Fable-5-class plans driving GPT-5.5-class builds. Total spend lands at ~59% less than running Fable 5 end-to-end. |
| Release | 2026-06-14 | 2026-06-16 |
| Bench coverage | 0/0 scored · avg — | 0/0 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 Kilo Code 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, cost-conscious operators who run high-volume agent loops → Kilo Code. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.
FAQ — Fusion vs Kilo Code
Which is better, Fusion or Kilo Code?
On Goldie Bench, Fusion averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. Kilo Code 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 Kilo Code?
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. Kilo Code: Kilo Code is a routing layer that splits planning (heavy model) from execution (cheaper model) so you get Fable-5-class plans driving GPT-5.5-class builds. Total spend lands at ~59% less than running Fable 5 end-to-end.
What's the context window for Fusion vs Kilo Code?
Fusion has a Varies — depends on which panel models are dispatched context window. Kilo Code has a Varies — Kilo splits planning from execution across multiple models context window.
When should I pick Fusion over Kilo Code?
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 Kilo Code over Fusion?
Pick Kilo Code for: Cost-conscious operators who run high-volume agent loops; Multi-step workflows where the plan is the expensive part; Teams already paying for Fable 5 who want to keep the plan but drop the execution bill. The trade-off is the weaknesses we logged on the bench: Adds routing complexity — two model providers in one workflow; No per-task goldiebench head-to-heads yet.
How does Goldie Bench score Fusion vs Kilo Code?
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:
Fusion vs Opus 4.8 Kilo Code vs Opus 4.8 Fusion vs GLM-5.2 Kilo Code vs GLM-5.2 Fusion vs Grok Kilo Code vs Grok Fusion vs Qwen 3.7 Kilo Code vs Qwen 3.7Full model pages: Fusion · Kilo Code · back to the leaderboard
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.