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

Claude Mythos 5 vs Kilo Code

Restricted-access flagship — vetted partners only. vs Fable 5-class intelligence at ~59% less. The split-the-cost play.

Claude Mythos 5 · context200K tokens
Kilo Code · contextVaries (Kilo dispatches across models)
Claude Mythos 5 · priceRestricted access — vetted partners only
Kilo Code · price~59% less than Fable 5 solo
Claude Mythos 5 · 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 Claude Mythos 5 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.

Claude Mythos 5 · Not currently dispatched from Agent OS — no public API. Tracked for news coverage only.

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 = 🥉).

Task ↓
Claude Mythos 5
Kilo Code

Strengths & weaknesses I logged

Claude Mythos 5

Strengths

  • Highest-class Anthropic model — sits above Fable 5 in the Mythos line
  • Same Mythos-class capability profile as Fable 5 (with restrictions)

Trade-offs

  • No public API access — can't be benched against the open field
  • Restricted distribution makes it effectively unavailable to most builders

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 Claude Mythos 5 Kilo Code
VendorAnthropicKilo
Context window200,000 tokensVaries — Kilo splits planning from execution across multiple models
PriceRestricted access — vetted partners only~59% less than Fable 5 solo
Pricing detailMythos 5 is the un-released sibling of Fable 5. Same Mythos class, restricted to vetted partners. Made headlines mid-June 2026 when reports of a White-House-driven ban over China access dominated AI press.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.
Release2026-06-092026-06-16
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 Claude Mythos 5 and Kilo Code both into the Agent Operating System and dispatch each from the kanban by task type — vetted enterprise partners with mythos-class access → Claude Mythos 5, 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 — Claude Mythos 5 vs Kilo Code

Which is better, Claude Mythos 5 or Kilo Code?

On Goldie Bench, Claude Mythos 5 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 Claude Mythos 5 cost vs Kilo Code?

Claude Mythos 5: Mythos 5 is the un-released sibling of Fable 5. Same Mythos class, restricted to vetted partners. Made headlines mid-June 2026 when reports of a White-House-driven ban over China access dominated AI press. 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 Claude Mythos 5 vs Kilo Code?

Claude Mythos 5 has a 200,000 tokens context window. Kilo Code has a Varies — Kilo splits planning from execution across multiple models context window.

When should I pick Claude Mythos 5 over Kilo Code?

Pick Claude Mythos 5 for: Vetted enterprise partners with Mythos-class access; (For everyone else: read the Mythos ban coverage instead of waiting for access). The trade-off is the weaknesses we logged on the bench: No public API access — can't be benched against the open field; Restricted distribution makes it effectively unavailable to most builders.

When should I pick Kilo Code over Claude Mythos 5?

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 Claude Mythos 5 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