The small, fast inclusionAI model is Ling-2.6-flash — the efficient tier at 91 tokens/sec and $0.010 per million input tokens. It trades a few points of raw intelligence for speed and cost, the right call for high-volume, latency-sensitive work. Ring-2.6-1T (73 t/s) and Ling-2.6-1T (57 t/s) round out the top three.
Compact, efficient models — the small/mini/flash/haiku tier — ranked by output speed. These trade a little raw intelligence for low cost and high throughput, which is the right tradeoff for chat, classification, extraction and other high-volume work.
The small, fast inclusionAI model is Ling-2.6-flash — the efficient tier at 91 tokens/sec and $0.010 per million input tokens. It trades a few points of raw intelligence for speed and cost, the right call for high-volume, latency-sensitive work. Ring-2.6-1T (73 t/s) and Ling-2.6-1T (57 t/s) round out the top three.
Ring-2.6-1T (73 t/s) is the closest alternative on this metric, followed by Ling-2.6-1T (57 t/s). See the full ranking above for the tradeoffs.
modelgrep tracks 3 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.