gpt-4o

By price, gpt-4o ranks 55th cheapest of 68 on input and 51st on output. Its quality score of 88 ranks 29th of 68, and on value (quality score ÷ output price) it ranks 50th of 68. Its blended rate sits 49% above the catalog average.

In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $500 per month on gpt-4o, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $560. Because output is priced 4.0× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.

A 128K context window holds roughly 171 pages of A4 text (at ~750 tokens per page), ranking 53rd of 68 here. That covers typical RAG and multi-turn chat, though book-length inputs still need retrieval and chunking. Output runs at about 100 tok/s (30th fastest of 68), acceptable interactively, though long responses will feel slow.

We track 11 OpenAI models, and gpt-4o's blended rate sits 14% above that provider's average. If your task tolerates a little less headroom, Hunyuan HY3 (Tencent) blends about 98% cheaper at a quality score of 87, and is worth benchmarking first. Going the other way, qwen3.5 scores 91 on quality for about 97% less.

The closest model in OpenAI's line-up is gpt-5.6-terra ($2.00 input / $12.00 output, quality 95). Against it, gpt-4o scores 7 points lower on quality, runs 10 tok/s slower (about 9%), has a 921K smaller context window, costs 3% less blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.