Best inclusionAI Models for RAG

Match · Updated July 2026

The best inclusionAI model for RAG is Ring-2.6-1T — 30.6 intelligence with 262K tokens of context for retrieved passages. Ling-2.6-1T (26.1) and Ling-2.6-flash (14.1) round out the top three.

30.6Intelligence

$0.075Input /M

262KContext

The best AI models for retrieval-augmented generation, ranked by intelligence among models with at least 128K tokens of context — enough to hold retrieved passages plus conversation. RAG pipelines run at volume, so weigh the price and speed columns as hard as the score.

Frequently asked

What is the best inclusionAI model for RAG?

The best inclusionAI model for RAG is Ring-2.6-1T — 30.6 intelligence with 262K tokens of context for retrieved passages. Ling-2.6-1T (26.1) and Ling-2.6-flash (14.1) round out the top three.

What's a good alternative to Ring-2.6-1T?

Ling-2.6-1T (26.1) is the closest alternative on this metric, followed by Ling-2.6-flash (14.1). See the full ranking above for the tradeoffs.

How many inclusionAI models are there?

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.

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