DeepSeek v4 works fine, but it’s not the frontier-pressing moment we saw with Kimi 2.6. On Notion eval data, it’s similar performance to GPT 5.2, with understandable failings. Most interesting — it doesn’t scale well. It’s ridiculously slow. On multiple major, trusted, and performant US inference providers we see it 15x slower than GPT 5.2 and 2x slower than Opus 4.7, a problem Kimi never had. Curious if it’s a fundamental issue in architecture, or a matter of time til inference providers make it work. Doesn’t seem urgent either way, if Kimi can outperform. Cheaper maybe, but not groundbreaking.

AI Gateway lets you route to any model. On May 13 in SF, we're hosting a builder night powered by those models. Pick one, build, demo. Audience votes on best build. With @AnthropicAI, @MiniMax_AI, & @Kimi_Moonshot Sign up ↓ https://t.co/LUvzv22uoQ

Results on the remainder of our benchmarks are in for Kimi K2.6, the new #1# open-weight model on the Vals Index (#8# overall) Kimi K2.6 is competitive with many closed-weight models, at a fraction of their price. https://t.co/UiCtzM7phM

🎁 Here's a new limited-time top-up reward. Grab bonus vouchers and keep exploring Kimi K2.6. 🔹20% bonus for $100 – $299 🔹25% bonus for $300 – $999 🔹30% bonus for $1,000+ Ends May 3. 🔗Details:https://t.co/HLRaFecpoN https://t.co/TVo1yL7TQ2

Meet Kimi K2.6 Agent Swarm 👋 Highlights： 🔹 Swarms, elevated - 300 parallel sub-agents × 4,000 steps per run (up from 100 / 1,500 in K2.5). 🔹 Outputs are real files, not chat - one run delivers 100+ files, 100,000-word literature reviews, or 20,000-row datasets. 🔹Heterogeneous skills - search, analysis, coding, long-form writing, and visual generation all running in parallel 🔗Try it at: https://t.co/2Tu8McUaUa

Kimi K2.6 is free on Nous Portal for the next 24 hours Made possible by @vercel's AI Gateway & @Kimi_Moonshot Run 'hermes update', then 'hermes model' and select Kimi K2.6 to try out one of the most impressive open model releases ever https://t.co/iAsfm7qhTs

We are entering an extremely exciting era for open-weight models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via @FireworksAI_HQ fast inference APIs. Kimi K2.6 has impressive agentic capabilities, design skills, and the ability to synthesize large amounts of information. I built a little Skill that produces survey papers on any AI research topic you want. (see example in the clip) You can use the skill to tell your agent to generate a survey on whatever topic and watch it go to work. The artifact was fully generated by @Kimi_Moonshot's Kimi K2.6. It's cheap and fast. Next step for me is to explore ways to continue integrating the capabilities of these models on use cases like automating my LLM knowledge bases and augmenting my agent memory capabilities. Stay tuned for more.

ICYMI: Kimi K2.6 is now in Notion. It’s the first open-weight model that plays like other top-tier models. It’s strong at tool use and carrying out tasks no matter how meticulous or ambiguous. Give it a spin and tell us what you think. https://t.co/K7Vs2dYgDC

We're open-sourcing FlashKDA — our high-performance CUTLASS-based implementation of Kimi Delta Attention kernels. Achieves 1.72×–2.22× prefill speedup over the flash-linear-attention baseline on H20, and works as a drop-in backend for flash-linear-attention. Explore on github: https://t.co/sf4UohXDWY

Kimi K2.6 autonomously overhauled exchange-core, an 8-year-old open-source financial matching engine. Over a 13-hour execution, the model iterated through 12 optimization strategies, initiating over 1,000 tool calls to precisely modify more than 4,000 lines of code. Acting as an expert systems architect, Kimi K2.6 analyzed CPU and allocation flame graphs to pinpoint hidden bottlenecks and boldly reconfigured the core thread topology (from 4ME+2RE to 2ME+1RE). Despite the engine already operating near its performance limits, Kimi K2.6 extracted a 185% medium throughput leap (from 0.43 to 1.24 MT/s) and a 133% performance throughput gain (soaring from 1.23 to 2.86 MT/s).