Charitably, you could read this as "its overall intelligence [is in a class that] ranks second only to [that of]..."

Yeah, bad wording it seems. Though a charitable interpretation is that Fable 5 and GPT 5.6 Sol are joint 1st place in the measurement.

While you are technically correct, in English it’s perfectly fine to say it this way as well.

“Second only” here has meaning “next after”, not “number two”.

Not if the others tie for first place.

Which is still great because it means neither of the two best financed labs in the world manage to produce even two models themselves that would beat Kimi K3.

Sonnet 5 does beat Opus 4.8 on several benchmarks. It just costs more and takes longer.

(On several other benchmarks, it costs more, takes longer, and does worse.)

Possible, but pay-as-you-go Hy3 / DeepSeek v4 Pro / MiMo v2.5 Pro (from respective vendors) are genuinely good enough as daily drivers, given the costs (especially, low prices for input cache, which usually makes up 70%+ of total input for agentic workflows). I put in $10 in DeepSeek & Xiaomi MiMo, and I've barely used $1 each, in a week of coding work.

Coding Plans by MiniMax ($20/mo for 1.7b tokens) and Z.ai (~$30/week use for $17/mo) are also tremendous value for money.

i’ll never really understand this comment. why would labs do this if they know private benchmark evals will come out in the next week?

It was also disruptive because it was open weight, meaning anyone and their dog could theoretically compete with the frontier labs for their inference revenue.

The frontier labs need to recoup a huge amount of cash to cover their model development costs, and justify their valuations. That’s plausible when they’re only ones capable of selling inference on these models, it a lot less plausible when models themselves become cheap commodities, and you’re just competing on your ability to provide compute. Anthropic and OpenAI can’t compete with people like AWS on that front.

cost has nothing to do with why deepseek was disruptive, the fact that it means there is zero moat around anthropic or openai is what's disruptive about it. it means in the mid-term LLMs will be commoditized and customers will flock to the cheapest inference wherever they can find it. there's no reason to stick to the "frontier" labs

DeepSeek didn’t really change any trends though, unless you count the stock market.

It was impressive work, but models were commoditizing and inference costs were dropping rapidly already. They were neither the first nor the last 10x optimization, from what I’ve seen.

It was on the page linked in the top comment, but it's been removed.

I copied that from https://platform.kimi.ai/docs/guide/kimi-k3-quickstart but it seems they updated the page to remove the benchmark score now.