Mohamed Hazeem retweeted
From recognizing text to understanding documents. 📄
Meet Xiaomi-OCR-0, an open-source document understanding model with just 0.8B parameters.
It brings document parsing, key information extraction, and OCR-oriented visual question answering into one lightweight model.
It scores 95.24 on Real5-OmniDocBench and 83.2 on average across five OCR-oriented VQA benchmarks.
On OmniDocBench v1.6, Xiaomi-OCR-0 ranks first in document parsing performance among models with fewer than 1B parameters.
Model weights, inference code, an interactive demo, MCP service, and Agent Skill are now open source. 👇
🤗 Huggingface: huggingface.co/xiaomi-resear…
🔗 GitHub: github.com/xiaomi-research/X…
📄 Demo: huggingface.co/spaces/loongw… #XiaomiAI #OCR #OpenSource
Mohamed Hazeem retweeted
Qwen3.8-Flash is now available in the European Union on Alibaba Cloud Model Studio.
Leverage its advanced reasoning, multimodal capabilities, and high-speed performance to develop intelligent AI applications.
Build with Qwen3.8-Flash: click.alibabacloud.com/m/200…
#AlibabaCloud #Qwen #ModelStudio #EuropeanUnion
Mohamed Hazeem retweeted
Introducing Kimi K3.1 Pro: our most capable 3T-class open-weight model.
🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal.
🔹 Full-project coding: games in Unreal, Unity & Godot.
🔹 Excels at parametric 3D modeling in Blender & CAD.
🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%.
🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks.
Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on Kimi.ai, Kimi Work, Kimi Code, and the Kimi API.
Open weights by Nov 4, 2026.
🔗 API: platform.kimi.ai
🔗 Tech blog: kimi.ai/blog/kimi-k3-1-pro
Mohamed Hazeem retweeted
Will they ever meet? 🤔👀
Two men are walking around a massive circular water tank, trying to find each other.
Mohamed Hazeem retweeted
Introducing Ling-3.1-flash-1019 🚀
It scores 44 on the Artificial Analysis Intelligence Index, up from 41 for Ling-3.1-flash. Gains in agentic work: AA-Briefcase ~1400→1524 Elo and AutomationBench-AA 62%→68%.
API access and open weights coming soon. Stay tuned.
Mohamed Hazeem retweeted
Space Bunny just landed in Qoder.
MiniMax M3.1 Flash is available from Day 0 across the Qoder suite. Switch models and put it to work.
MiniMax M3.1 Flash: Space Performance + Bunny Speed
🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash.
💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed.
API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens.
Model weights will arrive on Oct 23.
API: platform.minimax.io
M Plan: minimax.io/m-plan
MiniMax Code for desktop: agent.minimax.io/download
