The best inclusionAI model for instruction following is Ling-2.6-flash, satisfying 57.4% of IFBench's verifiable prompt constraints. Ling-2.6-1T (56.9%) and Ring-2.6-1T (44.6%) round out the top three.
AI models ranked by IFBench — how reliably a model obeys explicit, verifiable constraints in the prompt (format, length, inclusion and exclusion rules). High scores mean fewer retries and less prompt-wrangling in production, which often matters more than raw intelligence for pipelines.
The best inclusionAI model for instruction following is Ling-2.6-flash, satisfying 57.4% of IFBench's verifiable prompt constraints. Ling-2.6-1T (56.9%) and Ring-2.6-1T (44.6%) round out the top three.
Ling-2.6-1T (56.9%) is the closest alternative on this metric, followed by Ring-2.6-1T (44.6%). See the full ranking above for the tradeoffs.
modelgrep tracks 4 inclusionAI models with live benchmarks, speed, latency and per-provider pricing, led on intelligence by Ring-2.6-1T. 3 of them qualify for this ranking.