
Kilo Code vs Grok 4.5
Fable 5-class intelligence at ~59% less. The split-the-cost play. vs xAI's Grok 4.5 — the coding/agentic model, default in Grok Build. Tops SWE Marathon, ~4x more token-efficient than Opus 4.8, ~80 TPS.
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 Grok 4.5, 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.
Grok 4.5 · Benched one-shot on the same GoldieBench game prompts as the field, with the threejs-game-director patterns baked into each prompt; weak builds iterated by Grok 4.5 itself (the model authors every fix, never hand-patched). Wired into the Agent OS as the newest engine.
Side-by-side on 48 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
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
Grok 4.5
Strengths
- SWE Marathon resolution #1: 29.0% (Opus 4.8 26.0, Fable 24.0)
- ~4.2x more token-efficient than Opus 4.8 on SWE-Bench Pro (15,954 vs 67,020 avg output tokens); ~80 TPS
- Strong one-shot game builds: gorgeous multi-part heroes + layered worlds + cohesive HUDs first try (dragonrealm, crypt, skyrim)
Trade-offs
- Raycaster/FPS (doom) under-renders + walks out of bounds one-shot; needed multiple self-fix passes
- Occasional TDZ/init bug blanks a build to black (racing) — recovered by the model itself in one pass
- Not available in the EU until mid-July 2026
Pricing & context — the spec sheet
| Spec | Kilo Code | Grok 4.5 |
|---|---|---|
| Vendor | Kilo | xAI · Grok Build |
| Context window | Varies — Kilo splits planning from execution across multiple models | xAI's smartest model, built for coding + agentic tasks; trained alongside Cursor. Default model in Grok Build. Benched here via OpenRouter (x-ai/grok-4.5). |
| Price | ~59% less than Fable 5 solo | $2 / 1M input · $6 / 1M output |
| Pricing detail | 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. | ~4.2x fewer output tokens than Opus 4.8 on SWE-Bench Pro (15,954 vs 67,020 avg) and served at ~80 TPS, so real cost/latency is well below the sticker. Free for a limited time in Grok Build + Cursor. |
| Release | 2026-06-16 | 2026-07-08 |
| Bench coverage | 0/0 scored · avg — | 48/50 scored · avg 7.60/10 |
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 Grok 4.5 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, one-shot end-to-end app + game builds from a single prompt → Grok 4.5. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Kilo Code vs Grok 4.5
Which is better, Kilo Code or Grok 4.5?
On Goldie Bench, Kilo Code averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. Grok 4.5 averages no scored verdicts yet, with 12 gold, 34 silver, 2 bronze. Not enough scored shared tasks yet to call a winner.
How much does Kilo Code cost vs Grok 4.5?
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. Grok 4.5: ~4.2x fewer output tokens than Opus 4.8 on SWE-Bench Pro (15,954 vs 67,020 avg) and served at ~80 TPS, so real cost/latency is well below the sticker. Free for a limited time in Grok Build + Cursor.
What's the context window for Kilo Code vs Grok 4.5?
Kilo Code has a Varies — Kilo splits planning from execution across multiple models context window. Grok 4.5 has a xAI's smartest model, built for coding + agentic tasks; trained alongside Cursor. Default model in Grok Build. Benched here via OpenRouter (x-ai/grok-4.5). context window.
When should I pick Kilo Code over Grok 4.5?
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.
When should I pick Grok 4.5 over Kilo Code?
Pick Grok 4.5 for: One-shot end-to-end app + game builds from a single prompt; Cost/latency-sensitive agentic coding loops (token-efficient + fast); Office-work automation (Excel/PowerPoint/Word via Grok Build). The trade-off is the weaknesses we logged on the bench: Raycaster/FPS (doom) under-renders + walks out of bounds one-shot; needed multiple self-fix passes; Occasional TDZ/init bug blanks a build to black (racing) — recovered by the model itself in one pass; Not available in the EU until mid-July 2026.
How does Goldie Bench score Kilo Code vs Grok 4.5?
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:
Kilo Code vs Fusion Grok 4.5 vs Fusion Kilo Code vs Hermes MoA Grok 4.5 vs Hermes MoA Kilo Code vs Claude Fable 5 Grok 4.5 vs Claude Fable 5 Kilo Code vs Grok (X real-time) Grok 4.5 vs Grok (X real-time)Full model pages: Kilo Code · Grok 4.5 · 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 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.






















