GPT-5 vs Claude 4.6 — the full picture
GPT-5 and Claude 4.6 sit at the top of the 2026 frontier-model market but optimise for different buyers. GPT-5 (OpenAI) lists at $2.50 per 1M input tokens with a curated quality score of 9.2/10. Claude 4.6 (Anthropic) lists at $3.00 per 1M with a quality score of 9.4/10. The headline gap looks small — but at scale, the price multiple is 1.2x and the V-Index gap is 0.55 points, which compounds fast across a typical 10M-token monthly workload.
The cost math at scale
At 10M input tokens per month — a realistic mid-market workload — GPT-5 costs $25 and Claude 4.6 costs $30. The annualised difference is $60. Whether that gap is worth paying depends entirely on whether the higher-priced model reduces downstream review time enough to cover it. Our auditor measures this directly on your real prompt.
- →when budget is the binding constraint — GPT-5 is both cheaper and higher V-Index
- →for the highest-stakes work where raw quality matters more than cost — Claude 4.6 edges out on the overall quality score
Frequently asked questions
- Is GPT-5 better than Claude 4.6?
- Neither is universally better. Claude 4.6 has the higher curated quality score (9.4 vs 9.2), but GPT-5 has the higher V-Index (3.68 vs 3.13). The right choice depends on whether your workload is quality-bound or cost-bound — run a real prompt through the auditor to see which one wins for your specific use case.
- What is V-Index?
- V-Index is quality (1–10) divided by input price per 1M tokens (USD). It is a single number that captures value-per-dollar — higher is better. GPT-5 scores 3.68 on V-Index; Claude 4.6 scores 3.13.
- Which model hallucinates less?
- Both GPT-5 and Claude 4.6 hallucinate at non-zero rates in 2026, but the rate is highly task-dependent. Factual retrieval and citation tasks are the highest-risk categories on either model. The auditor on aiprompt.fyi flags hallucination risk per task type, per model, on your real prompt.
- Can I switch between GPT-5 and Claude 4.6 based on the prompt?
- Yes — and you should. Frontier-model routing (picking the right model per request based on task type and cost) typically cuts spend 30-50% versus defaulting to one model. The auditor produces a per-task recommendation you can wire directly into a router.
- Where does the pricing come from?
- Pricing is the public list price per 1M input tokens as of the most recent vendor update. Enterprise contracts often discount 20-40% off list. Quality scores are curated based on published benchmarks and our own task-specific testing — they are not vendor-supplied.