Tokenizers also matter. Anthropics tokenizers will encode the same piece of text at a way higher token count than OpenAi, for example.

That said, Kimi is competing against GLM in my mind, and GLM 5.2 is less than 1/3 the price.

I feel like the quickstart is missing something. It's referring to its tech blog for actual benchmarks, but K3 isn't mentioned on there, the last thing on that blog was K2.6, 2 releases ago.

This is too expensive to be a viable model. If it were $5/1m output, it might be another story. At these prices, there's no reason to use this over GPT 5.6.

Are thinking models only the reasonable tradeoff vs using much larger non thinking ones because the cost of output tokens is below that of input tokens?

> reasoning efficiency matters directly for how expensive a model actually is in real use

I have high hopes on this topic, given token efficiency seemed to be the primary (only?) goal of the K2.7 Code release.

Excited to see the signals that come out of the big eval/benchmark sites.

Agreed re reasoning. I’ve seen this play out with 5x reasoning negating cost savings.

Will be interesting to see how it stacks up pricing wise on the various inference providers.

How do Kimi's subscriptions work? I find their price structure pretty confusing

The big danger here is the gradual increase in open-weight subscription costs. I use open weight subscriptions, with lower-cost models for 80% of my tasks and GLM-5.2, Qwen 3.7-Max, Kimi-K2.6/2.7-Code for the 20% that need the most intelligence. That lets me maximize the rate-limit the subscription gives (rate limits per model are literally a price-limit-per-token/model). When new/more expensive open weights come in, providers phase out older/cheaper models. Over time we will either have to pay more, or use our subscriptions less.

It goes without saying, but if the open weights become as expensive as SOTA models, there's no point in using open weights. If nobody pays for open weights' development, the development dies out, and we're stuck with a US-controlled duopoly again. Which may be the biggest threat the world has seen from the US since nukes.

It seems the subsidized era is nearing its end and we'll see a convergence on API pricing before a pulling of subscriptions pricing.

I eat 1M context in a local model in about 3-4 hours.

It'd need to be exceptionally smart and error free to ever make sense.

Yeah... it's as if vendors hawked cars and announced expected range on a tank of gas.

But some cars have a 15 gallon tank and others a 50 gallon tank.

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