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Compare two AI models

Pick two models and see what each costs, how well it works and what it's actually for. The scores are my own judgment on a 1–5 scale from using these — not vendor claims and not benchmark results. Your picks stay in the address bar, so you can send the comparison to someone else.

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Coding assistants

Kilo

Visit

Free value

4/5

Performance

4/5

Range of uses

4/5

Free tool, but you pay for whichever model you plug into it.

Published benchmark scores: KiloBench (Terminal-Bench 2.0, run in Kilo's harness)76.2% at $87.41 per attempt — 1st
share of real command-line tasks completed unaided, with the API cost of trying · tested: GPT-5.6 Sol driven by Kilo
Kilo's own KiloBench board · checked September 2026 · maker's own figures
KiloBench (Terminal-Bench 2.0, run in Kilo's harness)75.3% at $112.27 per attempt — 3rd
share of real command-line tasks completed unaided, with the API cost of trying · tested: Gemini 3.8 Flash driven by Kilo
Kilo's own KiloBench board · checked September 2026 · maker's own figures
KiloBench (Terminal-Bench 2.0, run in Kilo's harness)73.0% at $33.83 per attempt — 5th
share of real command-line tasks completed unaided, with the API cost of trying · tested: Grok 4.6 driven by Kilo
Kilo's own KiloBench board · checked September 2026 · maker's own figures
Worth reading next to the row above: three points behind the leader for a third of the money.
Kilo now publishes its own board — KiloBench — which runs Terminal-Bench 2.0 through Kilo's actual agent harness and reports the cost of each attempt alongside the pass rate. These are Kilo's own figures, not an independent leaderboard, and each one belongs to the model plugged in rather than to Kilo itself. The 88% SWE-bench figure floating around one comparison blog still has no primary source, so it stays out.
Figures copied from the sources above, checked 17 September 2026.
Cost: Free for individuals; teams $15 per user/month.
Performance: As good as whichever model you plug into it. Works in VS Code, JetBrains, the terminal and the cloud.
Use it for: Editing a project without paying a subscription
Keeping code private by running a local model