We are excited to share a new milestone — we've open-sourced dInfer, a high-performance inference framework for diffusion language models (dLLMs).
🚀10.7X speedup over NVIDIA’s diffusion model framework Fast-dLLM.
🧠1,011 tokens per second in single-batch inference — on the
InclusionAI
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AI Lab @AntGroup, we envision AGI as humanity's shared milestone. Our Language Model @AntLingAGI and LLaDA, Embodied AI @robbyant_brain, OSS projects AReaL etc.
Joined March 2025
- One of the largest non-thinking models ever open sourced🚀🚀🚀🚀 Ling-1T — Trillion-Scale Efficient Reasoner Introducing Ling-1T, the first flagship non-thinking model in the Ling 2.0 series — 1 Trillion total parameters with ≈ 50 B active per token, trained on 20 T+ reasoning-dense tokens. Highlights → Evo-CoT curriculum +
- Officially introduce Ring-1T, silver-level to the IMO 2025.🚀🚀🚀⚡️⚡️⚡️🚀We officially release Ring-1T, the open-source trillion-parameter thinking model built on the Ling 2.0 architecture. Ring-1T achieves silver-level IMO reasoning through pure natural language reasoning. → 1 T total / 50 B active params · 128 K context window → Reinforced by
- AWorld introduces a dynamic multi-agent system that achieved 1st place on the GAIA leaderboard. @_akhaliq @Grad62304977 Check out the paper:
- Thanks for the pick of Ling-1T, also we have its thinking version Ring-1T. Welcome to download and vibe coding with them.Latest open models (#15): It’s Qwen's world and we get to live in it, on CAISI's report, & GPT-OSS update After a quiet month, Qwen is back in full force. interconnects.ai/p/latest-open-…
- Ring-flash-linear-2.0 :cost effective ,as fast as flashlight ⚡️🚀Meet Ring-flash-linear-2.0 & Ring-mini-linear-2.0 --> ultra-fast, SOTA reasoning LLMs with hybrid linear attentions --> 2x faster than same-size MoE & 10x faster than 32B models --> Enhanced with advanced RL methods Try the future of reasoning!
- A remarkable moment on scaling!🚀 Ring-1T-preview: Deep Thinking, No Waiting The first 1 trillion open-source thinking model -> Early results in natural language: AIME25/92.6, HMMT25/84.5, ARC-AGI-1/50.8, LCB/78.3, CF/94.7 -> Solved IMO25 Q3 in one shot, with partial solutions for Q1/Q2/Q4/Q5 Still evolving!
- 🚀🚀🚀 Ring-flash-2.0 shows a new breakthrough about Long-CoT RL traning on MoE models.We open-source Ring-flash-2.0 — the thinking version of Ling-flash-2.0. --> SOTA reasoning in math, code, logic & beyond. --> 100B-A6B, 200+ tok/s on 4×H20 GPUs. --> Powered by "icepop"🧊, solving RL instability in MoE LLMs.
- Looking forwardI’m starting a new series of interviews on @interconnectsai with all the leading open model labs around the world to show why people are doing this, how people train great models, and where the ecosystem is going. The first one is Ant Group’s Ling (@AntLingAGI) / InclusionAI
- Ant Group’s Inclusion AI ranked in this list,we will release more works in the coming days.China's Top 19 Open Model Labs We ranked all the organizations in China releasing open models, from the top of DeepSeek to small, newer academic labs making waves with tech reports and niche models. interconnects.ai/p/chinas-top-1…
- Nice work!We released Ling-flash-2.0, Ring -flash-2.0, you can try more and talk to us.😇Another demo of the iPhone 17 Pro’s on-device LLM performance This time with Ling mini 2.0 by @TheInclusionAI, a 16B MoE model with 1.4B active parameters running at ~120tk/s Thanks to @awnihannun for the MLX DWQ 2-bit quants
00:00 - congs to the release! my wife has contributions in the post-training part 🥳
- Today Inclusion AI’s AWorld have hit#1 on #GAIA leaderboard,the benchmark developed for real-world AI evalutions. With a series of innovative works ,such as developing a Multi-Agent System (MAS), an adaptive intervention and logical validation,AWorld just achieved anWe just hit #1 on the GAIA Test Leaderboard—the leading benchmark for real-world AI evaluation! Our open-sourced Multi-Agent System hit 81.73%—a new milestone for real-world AI evaluation. Learn more ⬇️ GitHub: github.com/inclusionAI/AW… Leaderboard: huggingface.co/spaces/gaia-be… Blog:
- Ant AQ-Team @AQ_MedAI @TheInclusionAI and SGLang RL Team @sgl_project just helped land Kimi-K2-Instruct RL on slime — fully wired up and running on 256× H20 141GB 🚀 Huge shout-out to @yngao016, @menlzy, @Yonah_x from AQ Team and @Ji_Li_233, @Yefei_RL from the SGLang RL Team for















