Daily Ranking Compares Coding AI Models by Cost-Effectiveness
The October 11, 2026 AI Weather Report ranks 60 AI coding models by a value score that combines benchmark capability with blended API cost. Mistral-Nemo took first place with a capability rating of 62 and a cost of $0.0297 per million tokens, yielding a value score of 2084.0. The scoring uses SWE-bench, HumanEval, and LiveCodeBench, weighting input at 25% and output at 75% for coding workloads.
The October 11, 2026 report ranks 60 coding models and highlights a top 10. Its value score divides a capability rating by blended API cost per million tokens, using SWE-bench, HumanEval, and LiveCodeBench. Coding workloads are weighted 25% for input and 75% for output.
Mistral-Nemo leads with a 62/100 capability rating and $0.0297 cost, producing 2084.0. By contrast, gpt-oss-120b scores 93/100 but ranks seventh at 680.1 because its cost is $0.1368. The list also includes providers such as MistralAI, OpenAI, Google, Meta, Qwen, and others.
Rankings like this could influence how developers and small teams choose coding assistants, potentially steering spending toward lower-cost models. If value scores shape procurement, providers may face pressure to improve benchmark performance or cut API prices. However, because the score emphasizes cost and selected benchmarks, it may not capture real-world reliability, security, or maintainability, so its societal effects on access and productivity remain uncertain.