modelgrep

Best LLMs for Science — inclusionAI

Match · Updated August 2026

The best inclusionAI model for science is Ring-2.6-1T, scoring 85.7% on GPQA Diamond — graduate-level physics, chemistry and biology. Ling-2.6-1T (75.2%) and Ling-2.6-flash (59.3%) round out the top three.

85.7%GPQA
30.6Intelligence
60 t/sSpeed
$0.075Input /M
262KContext
  1. 1I
    ring-2.6-1t
    ReasoningToolsJSON30.6 intel · $0.075/M · 60 t/s
    85.7%
    GPQA
  2. 2I
    ling-2.6-1t
    ToolsJSON26.1 intel · $0.075/M · 36 t/s
    75.2%
    GPQA
  3. 3I
    ling-2.6-flash
    ToolsJSON14.1 intel · $0.010/M · 62 t/s
    59.3%
    GPQA

How this is ranked

AI models ranked by GPQA Diamond — graduate-level physics, chemistry and biology questions written to be un-Googleable, so the score reflects reasoning from knowledge rather than retrieval. The best large language models for scientific research and hard-science work.

Frequently asked

What is the best inclusionAI model for science?

The best inclusionAI model for science is Ring-2.6-1T, scoring 85.7% on GPQA Diamond — graduate-level physics, chemistry and biology. Ling-2.6-1T (75.2%) and Ling-2.6-flash (59.3%) round out the top three.

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

Ling-2.6-1T (75.2%) is the closest alternative on this metric, followed by Ling-2.6-flash (59.3%). 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.

More inclusionAI rankings

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