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Kimi-K2-Instruct-0905. New not-quite-MIT licensed model from Chinese Moonshot AI, a follow-up to the highly regarded Kimi-K2 model they released in July.

This one is an incremental improvement - I've seen it referred to online as "Kimi K-2.1". It scores a little higher on a bunch of popular coding benchmarks, reflecting Moonshot's claim that it "demonstrates significant improvements in performance on public benchmarks and real-world coding agent tasks".

More importantly the context window size has been increased from 128,000 to 256,000 tokens.

Like its predecessor this is a big model - 1 trillion parameters in a mixture-of-experts configuration with 384 experts, 32B activated parameters and 8 selected experts per token.

I used Groq's playground tool to try "Generate an SVG of a pelican riding a bicycle" and got this result, at a very healthy 445 tokens/second taking just under 2 seconds total:

This one is pretty good. Bicycle is mostly the right shape, the pelican is perched quite awkwardly on the saddle, it has quite a good attempt at the chain mechanism.

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