Your coding questions are exactly where AI models disagree most

Most developers I know have a default model for coding help. One tab, one answer, ship it. Our divergence study suggests coding is one of the worst places to do that. We sent the same 24 questions, unchanged, to five models — GPT, Claude, Gemini, Grok and Llama. Six were coding approach questions. On facts, the panel was near-unanimous (0.33 material divergences per question). On coding, they averaged 2.67 divergences per question — and 5 of the 6 coding questions produced a lone model: a claim or stance exactly one model took. Three coding examples from the study: Postgres partitioning: only one model named the main design cost — retrofitting partitioning forces a schema change, because primary and unique keys must include the partition key. Every other answer discussed benefits without naming that cost. TypeScript interfaces vs types: the lone claims ran both ways. One model correctly flagged that declaration merging is double-edged — same-named interfaces merge silently — and was the only one to propose an enforcement mechanism (an ESLint rule). Another cited implements support as a reason interfaces are needed, which is wrong: classes can implement object-shaped type aliases too. Public API default: three models picked REST, one picked GraphQL as the default — a genuine lone dissent a single-model workflow would present as settled fact. That is the pattern: 14 sole-source claims across the study, hand-checked — 8 were the highest-value line in their set, 3 were wrong or invented. A lone coding claim is sometimes the detail that saves the migration and sometimes the error that breaks it, and one chat window never tells you it is alone. My practical rule now: one model is fine for a syntax lookup; for an architecture call I will live with — partitioning, API style, a type standard — I check where more than one model splits before I commit. The disagreement is the information. Full study, method and caveats (including that one judge was also a panel member, and a memory-bleed incident we found and disclosed): https://multio.ai/research/model-divergence Disclosure: I build MultiO (multio.ai) — One subscription. Every top AI model… Auto sends each message to the most cost-efficient model that can handle it. Compare asks up to three models side by side, and every message shows its exact token charge on a receipt. Free trial: 3,000,000 tokens, no card required. — @getmultio / hello@multio.ai