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Step 5 Preview: Advancing the Pareto Frontier

45 pointsby 3h agostepfun.com
12 comments
2h agoHN ↗

I regularly hit 200-300M cached reads every day on some of the models I use. It has exceeded 7-800M on a couple of occasions. At $0.04/M, that is $8-12 per day only for cached reads.

54m agoHN ↗

At $0.04/M

Unless you meant step-3.7-flash, the input cache hits are $0.05 per mil for step-5-preview.

$8-12 per day only for cached reads

Pretty decent "API" rates for ~500M+ tokens on Step Fun 5, a Kimi K3 / GLM 5.3 level model?

Their "Step Plan" is ridiculous, by comparison: ~$60 usage on $6.99/mo; ~$220 on $9.99/mo. https://platform.stepfun.ai/docs/en/step-plan/overview

1h agoHN ↗

Sometimes 4 is skipped due to being considered unlucky.

1h agoHN ↗

In China and in places influenced by Chinese culture, due to homonymy between "4" and death.

1h agoHN ↗

Without any Pokémon-specific optimization, Step 5 Preview has so far sustained progress for more than 3,000 turns and 6 million tokens of interaction. By turn 3,082, it had unlocked Cut, earned three Gym Badges, and defeated Lt. Surge. The run is now roughly one-third of the way through the main story.

Finally FireRed is being used as a benchmark again! I believe Astra can beat it in 18 hours. Not sure how that compares.

1h agoHN ↗

  > Built on a sparse Mixture-of-Experts architecture, Step 5 Preview has 600B total parameters, with 27B active per token, and supports a 1M-token context window and vision input.

  > Step 5 Preview scores 44 on the Artificial Analysis Intelligence Index.

  > The model will be released with open weights on October 15.

I guess being Chinese company they decided to skip version 4, while also giving impression to be on the similar iteration with leading companies (claude opus 5). I wonder if other Chinese labs like Kimi/Moonshot will follow suit.

26m agoHN ↗

Moonshot has already teased K3.1 so not likely

20m agoHN ↗

K3.1 would likely be a deeper/longer post-train from K3, so that’d make sense.

It’s all marketing anyways, but that’s at least how a lot of labs have been naming things (sometimes).

1h agoHN ↗

Their posisitoning is nice. Instead of saying they are cheaper and a bit less performant (in terms of intelligence), they say they are best among the cheaper and a bit less performant ones.