Benchmarking 23 Models for Agents: GPT 5.6 Wins Big, Slashing Inference Costs
NextgenAITrading · reddit · 2026-08-12
An independent developer shared insights from rebuilding the model routing layer of their AI trading platform. They built five evaluation harnesses covering planning, code execution, and SQL generation to benchmark mainstream models on OpenRouter.
GPT 5.6 Luna emerged as the clear winner, taking four out of five categories. For execution tasks, it was the only model that outperformed the previous default across score, cost, latency, and schema validity simultaneously. It boosted the executor score from 75.3 to 89.2 at a cost of $1.67 per 1,000 decisions. Gemini 3.6 Flash retained the text-to-SQL task.
Following these results, the developer routed the entire agent loop through Luna. This switch caused Google's share of their inference bill to plummet from 84% to 4%, while significantly lowering total costs. Consequently, the author closed their GOOGL options position, arguing the specific product edge they underwrote had narrowed, but remains a long-term holder of the stock.
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