We are really taking a long time to prove this: everyone is building big macs but we bring you a kiwi🥝 instead. You have multimodal with K2.5 everywhere: chat with visual tools, code with vision, generate aesthetic frontend with visual refs...and most basically, it is a SUPER POWERFUL VLM

actually opus-4.7 and 4.8 have stalled at the same token-accuracy pareto for osworld

Looking forward to the blog! (If you’re able to share) - do you guys use G3 or G4 offloading or just CPU?

this is literally insane that we truly see an open model thinking 200-300k for math problems…

I saw flowers and moonlight today.

Very Nice Move👍

往错误的方向行走不会到达终点。

huggingface.co/papers/2604.2… arxiv.org/abs/2604.23781 tech report release

open intelligence in duet

Kimi K2.6 is #5 on Vending-Bench 2. It's the best open model, overtaking GLM 5.1.

As long as K2.5/K2.6 is multimodal, we are also making it to use (I am really amazed by how it excels at long multi-image documents because we are not specially optimizing for them too much) However still a long way to go

I think deepseek-v4 is not over-benchmaxxing, which is good. We build these things for people to use.

The 🐳 has surfaced and it’s a powerhouse on the Vals leaderboards, dominating on coding. DeepSeek V4 just landed #2 on the Vals Index, nearly tying Kimi K2.6 (only 0.07% behind).

GPT-5.5 takes OpenAI back to the clear number one in AI. OpenAI’s new model tops the Artificial Analysis Intelligence Index by 3 points, breaking a three-way tie with Anthropic and Google OpenAI gave us pre-release access to test all five reasoning effort levels: xhigh, high, medium, low and non-reasoning. ➤ OpenAI topping five headline evaluations: GPT-5.5 (xhigh) leads Terminal-Bench Hard, GDPval-AA and our newly hosted APEX-Agents-AA. The model trails only other OpenAI models in CritPt and AA-LCR, and comes second to Gemini 3.1 Pro Preview on three additional evaluations. The largest gains are on AA-Omniscience ( 14 pts), our knowledge and hallucination benchmark, and τ²-Bench Telecom ( 7 pts), a customer service agent benchmark. ➤ 20% more expensive to run our Intelligence Index: Per-token pricing has doubled from GPT-5.4 to $5/$30 per 1M input/output tokens. However, a ~40% token use reduction largely absorbs the hike - resulting in a net ~ 20% cost to run our Intelligence Index. ➤ Effort a clear ladder for balancing intelligence and cost: GPT-5.5 (medium) scores the same as Claude Opus 4.7 (max) on our Intelligence Index at one quarter of the cost (~$1,200 vs $4,800) - although Gemini 3.1 Pro Preview scores the same at a cost of ~$900. GPT-5.5 (low) approximates Claude Opus 4.7 (Non-reasoning, high) on our Intelligence Index at half the cost to run (~$500 vs ~$1 ,000). ➤ Number one in GDPval-AA with an Elo of 1785: GPT-5.5 (xhigh) leads Claude Opus 4.7 (max) by ~30 pts and Gemini 3.1 Pro Preview by ~470 pts. GDPval-AA is Artificial Analysis’ benchmark that leverages OpenAI’s GDPval dataset to evaluate models on real-world economically valuable tasks. ➤ Top AA-Omniscience accuracy, but trailing the frontier on hallucination: Our private AA-Omniscience benchmark rewards factual knowledge across diverse topics, but punishes hallucination. GPT-5.5 (xhigh) has the highest accuracy at 57% - meaning the model can recall facts in the Omniscience corpus more effectively than any other model. However, it has a hallucination rate of 86% - vs Opus 4.7 (max) at 36%, and Gemini 3.1 Pro Preview at 50%. This makes it more likely to answer a question when it does not ‘know’ the answer. The 14 pt gain in AA-Omniscience from GPT-5.4 (xhigh) was largely driven by knowledge, with a modest improvement in hallucination. Congratulations to the team at @OpenAI and @sama on the launch

It becomes much smarter than previous generations!

Shall we be looking forward to V4 now? Serving the burst of K2.6 has made us GPU poor again now😂

💥 Kimi-K2.6-thinking is the new best open-weight model on HalluHard (without web search)! K2.5 had 76.9% hallucination rate, whereas K2.6 now has 63.6%. Since our benchmark contains hard hallucination cases, this improvement is very notable. Thank you @Kimi_Moonshot for providing API credits and @dyfan22 for running the eval! Full results: halluhard.com/ Paper: arxiv.org/abs/2602.01031

Looling forward to more open-source models on vision arena （但等等这玩意是open-source吗）

Kimi K2.6 by @Kimi_Moonshot is #8 in Document Arena. Up 14 points over Kimi K2.5-Thinking, extending Kimi K2.6's lead as the #1 open model.