Author @adxtyahq claims you only need a $35,000/month GPU budget or a one-time…

Brief

Kimi.ai announced Kimi K3 on 2026-07-27: a 2.8T MoE model with native visual inputs and a 1M-token context window, claiming a 2.5× intelligence-per-compute improvement. They released model weights, a technical report, and supporting infrastructure (attention kernels, MoE comms library, agent-scale runtime) to Hugging Face/GitHub, while @adxtyahq framed cost trade-offs: $35k/month GPUs or $500k one-time versus a $99/month subscription.

Key details

Kimi.ai (posted 2026-07-27) released Kimi K3: a 2.8T-parameter Mixture-of-Experts (MoE) model with native visual understanding and a 1,000,000-token context window.

Kimi.ai asserts a new architecture delivering 2.5x the intelligence per unit of compute and published model weights and stack components — attention kernels, an MoE communication library, and agent-run infrastructure — to Hugging Face/GitHub and a technical blog.

Reminder: you only need a $35,000/month GPU budget, or a one-time $500,000 investment, to avoid a $99/month Kimi K3 subscription.

Kimi.ai (@Kimi_Moonshot)

Releasing the model weights and technical report of Kimi K3.

Kimi K3 is our most capable model: a 2.8T MoE model with native visual understanding and a 1M-token context window.

New model architecture: 2.5x the intelligence per unit of compute, not just more params.

Alongside Kimi K3, we're opening up more of the stack behind it — high-performance attention kernels, MoE communication library, and infrastructure for running agent environments at scale.

Model weights: huggingface.co/moonshotai/Ki…
Tech report: github.com/MoonshotAI/Kimi-K…
Tech blog: kimi.com/blog/kimi-k3

— https://nitter.net/Kimi_Moonshot/status/2081760186235289764#m

Brief

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