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

Kilo Code vs N2 (Nex-N2-Pro)

Fable 5-class intelligence at ~59% less. The split-the-cost play. vs Free local frontier model — runs in Hermes for $0.

Kilo Code · contextVaries (Kilo dispatches across models)
N2 (Nex-N2-Pro) · contextTBD
Kilo Code · price~59% less than Fable 5 solo
N2 (Nex-N2-Pro) · priceFree — runs locally inside Hermes
Kilo Code · vendorKilo
N2 (Nex-N2-Pro) · vendorNex AGI

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 Kilo Code and N2 (Nex-N2-Pro), 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.

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.

N2 (Nex-N2-Pro) · Wired into Hermes as the free local frontier coder. Dispatched from Agent OS for any task where the per-token bill would dominate.

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 = 🥉).

Task ↓
Kilo Code
N2 (Nex-N2-Pro)

Strengths & weaknesses I logged

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

N2 (Nex-N2-Pro)

Strengths

  • Vendor-reported 80.8% on SWE-bench Verified — top of the free open-weights field
  • Runs locally inside Hermes — no token meter, no rate limits
  • Builds two playable 3D games in one-shot per Julian's three-dragons writeup

Trade-offs

  • Vendor-reported benchmark (not independently verified yet)
  • No goldiebench per-task scores yet

Pricing & context — the spec sheet

Spec Kilo Code N2 (Nex-N2-Pro)
VendorKiloNex AGI
Context windowVaries — Kilo splits planning from execution across multiple modelsSpecs not yet public
Price~59% less than Fable 5 soloFree — runs locally inside Hermes
Pricing detailKilo 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.Nex AGI's flagship N2 (full name Nex-N2-Pro) runs free for individuals inside Hermes on your own Mac. Vendor-reported SWE-bench Verified: 80.8% — the highest published coding score among the free dragons (Kimi K2.6 / GLM / N2).
Release2026-06-162026-06-12
Bench coverage0/0 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 Kilo Code and N2 (Nex-N2-Pro) both into the Agent Operating System and dispatch each from the kanban by task type — cost-conscious operators who run high-volume agent loops → Kilo Code, local agent loops that need a free frontier-class coder → N2 (Nex-N2-Pro). That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Kilo Code vs N2 (Nex-N2-Pro)

Which is better, Kilo Code or N2 (Nex-N2-Pro)?

On Goldie Bench, Kilo Code averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. N2 (Nex-N2-Pro) 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 Kilo Code cost vs N2 (Nex-N2-Pro)?

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. N2 (Nex-N2-Pro): Nex AGI's flagship N2 (full name Nex-N2-Pro) runs free for individuals inside Hermes on your own Mac. Vendor-reported SWE-bench Verified: 80.8% — the highest published coding score among the free dragons (Kimi K2.6 / GLM / N2).

What's the context window for Kilo Code vs N2 (Nex-N2-Pro)?

Kilo Code has a Varies — Kilo splits planning from execution across multiple models context window. N2 (Nex-N2-Pro) has a Specs not yet public context window.

When should I pick Kilo Code over N2 (Nex-N2-Pro)?

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.

When should I pick N2 (Nex-N2-Pro) over Kilo Code?

Pick N2 (Nex-N2-Pro) for: Local agent loops that need a free frontier-class coder; Privacy-sensitive workflows (no cloud round-trip); Operators experimenting with Hermes who want to compare local models against the cloud field. The trade-off is the weaknesses we logged on the bench: Vendor-reported benchmark (not independently verified yet); No goldiebench per-task scores yet.

How does Goldie Bench score Kilo Code vs N2 (Nex-N2-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.

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