Kimi K2.8 Preview puts near-K3 coding in every membership tier

Moonshot spent the week arguing about revenue and the weekend shipping a model that undercuts its own flagship. Meanwhile the person who built Redis quietly made DeepSeek's newest MoE run on a desktop Mac.

Moonshot AI put Kimi K2.8 Preview live across Kimi Code and Kimi Work on September 11, claiming overall performance close to flagship K3 with further gains in coding and agentic work, and a 1M-token context window open to every membership tier. The pricing gap is the point: K3 needs the ¥99-per-month plan just to be selected, and its million-token window sits behind the ¥199 Allegretto tier, while K2.8 Preview is available on all five plans with the full 1M. The swap is invisible — the existing kimi-for-coding model ID now resolves to K2.8 Preview, and K3 requests with thinking disabled get routed to the preview's non-thinking variant. It carries K3's three reasoning-effort levels (low, high, max) and takes image and video input.

Why now: Moonshot's own K3 documentation concedes the flagship is fragile outside its sweet spot — sensitive to missing prior thinking context in an agent loop, and prone to over-reaching on vague tasks. A cheaper, more predictable workhorse is what high-volume code completion and everyday editing actually need. It also fits the commercial pressure: Moonshot reportedly crossed $1 billion in annualized revenue in August, up from roughly $300 million in June, and is targeting $2 billion by year-end while pursuing a Hong Kong listing at a $50 billion pre-IPO valuation — about 167 times revenue, against roughly 20 for Anthropic and 40 for OpenAI. We covered the filing last week — Moonshot AI files for Hong Kong IPO at $50B — days after Anthropic calls it out. Volume is the lever it needs: K3's series already generates around 300 billion tokens a day.

A 366 GB GGUF of DeepSeek V4.1 Flash is now on Hugging Face from Salvatore Sanfilippo, the Redis author, and it is built to run off solid-state storage rather than fit in memory. The quants back his ds4 inference engine, a from-scratch Metal, CUDA and ROCm runtime for DeepSeek's Flash and Pro models that ships an SSD-streaming mode — his own benchmark sweep runs a Q2 build on an M5 Max with 128 GB of RAM, and the docs point first-time users at a 96 or 128 GB machine. The Q2 file is up; the Q4 was still uploading as r/LocalLLaMA noticed. The relevant part for anyone running models locally is not the download size but what it implies: a frontier-class MoE whose active-parameter sparsity lets a single desktop stream expert weights from disk and still hold useful token rates. The model itself landed last week — DeepSeek V4.1 Flash ships — and retires V4 Pro on Sunday.

What to watch: whether K2.8 Preview graduates out of "Preview" with published weights, the way K3 did — Moonshot's flagship story has always leaned on open weights for distribution.

If your agent stack ran on one 128 GB desktop instead of a cloud API, what would you still pay for per token? Tell us in the comments.

Sources: antirez/ds4 (GitHub)

Akhetonics says its all-optical CPU reaches a customer in 2026

Light-based computing keeps promising more than it delivers — but one Munich startup has just put a date on its bet, and the interview laying it out is doing the rounds on Hacker News this week. Akhetonics says it will deploy its first commercial machine with a major customer by the end of 2026, with several more planned for 2027. The company, founded by Michael Kissner and Leonardo Del Bino, is building a computer where data enters as light, is switched as light, and circulates through memory

The Week in AI — October 5–11, 2026

Every big claim this week turned out to rest on fine print more interesting than the headline: revenue only the company reporting it can define, safety tests sandboxed while the product keeps the web, and a Pentagon phase-out nobody would confirm until reporters kept asking. The week's top 5 1. OpenAI's revenue was $20 billion below the numbers everyone quoted — and the gap was definitional. The Financial Times reported Thursday that OpenAI's annualized revenue runs roughly $20 billion unde

Drone strike shuts a third Yandex data center, taking YandexGPT offline

Russia's largest tech company is learning what the AI era's infrastructure war looks like from the receiving end — three data centers in four days, and with them much of the cloud layer Russian businesses run on. A Ukrainian drone strike knocked out Yandex's data center in Vladimir early Sunday morning, the third of the company's facilities hit since October 8. The site — reported at roughly 50 MW and designed for about 2,880 server racks — stopped operating completely after the attack, Yandex

Agent teams cost up to 5x more, barely score higher

The multi-agent hype train hit a benchmark this weekend — and the grid and the trucking regulators had quiet weeks of their own. Vals AI put agent teams head-to-head with single agents on its Vibe Code Bench, and the teams cost between 1.8 and 5.1 times more for almost no extra quality. The evals company ran GPT-6 Sol and Claude Opus 5.5 solo and in teams across 50 apps at two reasoning efforts; out of four comparisons, only one was statistically significant — Sol at medium effort, where the t

Read more

Akhetonics says its all-optical CPU reaches a customer in 2026

The Week in AI — October 5–11, 2026

Drone strike shuts a third Yandex data center, taking YandexGPT offline

Agent teams cost up to 5x more, barely score higher