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

Opus 4.8 vs Kilo Code

The reasoning king — deepest thinking, premium price. vs Fable 5-class intelligence at ~59% less. The split-the-cost play.

Opus 4.8 · context200K tokens
Kilo Code · contextVaries (Kilo dispatches across models)
Opus 4.8 · price$15 / $75 per M tokens
Kilo Code · price~59% less than Fable 5 solo
Opus 4.8 · vendorAnthropic
Kilo Code · vendorKilo

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 Opus 4.8 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.

Opus 4.8 · The default when the build has to ship on the first prompt — Opus is the safety net inside Agent OS for hard one-shots.

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 17 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 ↓
Opus 4.8
Kilo Code
Game
🥇Opus 4.8 on Arcade
— not attempted —
Game
🥇Opus 4.8 on Doom
— not attempted —
Game
🥈Opus 4.8 on Neoncity
— not attempted —
Game
🥇Opus 4.8 on Outrun
— not attempted —
Game
🥈Opus 4.8 on Raycaster
— not attempted —
Page
🥇Opus 4.8 on Landing
— not attempted —
Sim
🥇Opus 4.8 on Blackhole
— not attempted —
Sim
Opus 4.8 on Cloth
— not attempted —
Sim
🥉Opus 4.8 on Fluid
— not attempted —
Sim
🥈Opus 4.8 on Fractal
— not attempted —
Sim
🥇Opus 4.8 on Galaxy
— not attempted —
Sim
🥇Opus 4.8 on Orbit
— not attempted —
Opus 4.8 on Pathtracer
— not attempted —
Opus 4.8 on Reactiondiff
— not attempted —
Sim
🥇Opus 4.8 on Solar
— not attempted —
Visual
Opus 4.8 on Terrain
— not attempted —
Visual
🥈Opus 4.8 on Voxel
— not attempted —

Strengths & weaknesses I logged

Opus 4.8

Strengths

  • Most consistent across the Goldie Bench bench — no weak build, 8.46/10 average
  • Deepest one-shot reasoning, especially on game-feel and physics
  • Extended thinking mode handles up to 1M tokens of context

Trade-offs

  • 5–10× the per-token cost of every other model on the bench
  • Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments

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 Opus 4.8 Kilo Code
VendorAnthropicKilo
Context window200,000 tokens (1M with extended thinking)Varies — Kilo splits planning from execution across multiple models
Price$15 / $75 per M tokens~59% less than Fable 5 solo
Pricing detailPremium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency.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.
Release2026-052026-06-16
Bench coverage13/17 scored · avg 8.46/100/0 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 Opus 4.8 and Kilo Code both into the Agent Operating System and dispatch each from the kanban by task type — mission-critical one-shot builds where 'has to work the first time' matters → Opus 4.8, 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 — Opus 4.8 vs Kilo Code

Which is better, Opus 4.8 or Kilo Code?

On Goldie Bench, Opus 4.8 averages no scored verdicts yet across the shared tasks, with 8 gold, 4 silver, 1 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 Opus 4.8 cost vs Kilo Code?

Opus 4.8: Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. 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 Opus 4.8 vs Kilo Code?

Opus 4.8 has a 200,000 tokens (1M with extended thinking) context window. Kilo Code has a Varies — Kilo splits planning from execution across multiple models context window.

When should I pick Opus 4.8 over Kilo Code?

Pick Opus 4.8 for: Mission-critical one-shot builds where 'has to work the first time' matters; Hard reasoning tasks (planning, multi-step) where you'll pay for the depth; Anything where vendor reliability beats the per-token bill. The trade-off is the weaknesses we logged on the bench: 5–10× the per-token cost of every other model on the bench; Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments.

When should I pick Kilo Code over Opus 4.8?

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 Opus 4.8 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.

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