Tencent / Hunyuan

DeepSeek is pursuing RMB 70 billion in funding at an estimated valuation of about $45 billion, with Tencent and IDG Capital close to participating and founder Liang Wenfeng potentially investing RMB 20 billion personally.

Tencent released Hy-MT2 translation models in 1.8B, 7B, and 30B-A3B sizes, supporting translation across 33 languages; AngelSlim 1.25-bit quantization reduces the 1.8B model’s storage requirement to 440 MB and raises inference speed by 1.5x.

Tencent open-sourced the Hy-MT2 multilingual translation model with support for translation across 33 languages; its 1.8B version uses AngelSlim 1.25-bit quantization, occupies 440 MB of storage, and runs locally on mainstream mobile chipsets.

Tencent launched the OS-level AI assistant Mavis on May 21 across Windows, Mac, and Android, with document parsing, image recognition, system maintenance, partial offline use, model dispatching, and desktop control of mobile apps listed as supported functions.

DeepSeek’s financing talks with Alibaba fell through after both sides failed to agree on terms. The post says DeepSeek was valued at RMB 300 billion and sought RMB 50 billion.

DeepSeek is negotiating a $7.3 billion funding round at an estimated $51.5 billion valuation; Liang Wenfeng reportedly plans to contribute 40%, while Tencent and China’s RMB 60 billion national AI fund are also in talks.

DeepSeek is nearing a $45bn valuation in fundraising talks, with Tencent among investors seeking a stake. The post does not disclose round size, terms, or timeline. The key question is valuation versus model revenue.

Ruanyifeng’s Weekly Issue 394 argues that production-ready LLMs in H2 2025 triggered a second API-opening wave. The post says agents need platform APIs to act, citing Tencent opening WeChat interfaces after OpenClaw and adoption of MCP and Skills. The key shift is consumer services exposing actions, not only cloud APIs.

Tencent announced a major upgrade to its AI foundation model. It is the company's first high-stakes AI test since hiring a top OpenAI researcher. The post does not disclose the model name, parameter count, benchmarks, or launch timing.

Tencent and Alibaba are in talks to join DeepSeek’s first funding round, and the snippet confirms this is DeepSeek’s maiden financing. The RSS text discloses only the talks and the first-round status; it does not disclose the round size, valuation, lead investor, or timing. What matters is whether strategic capital from two Chinese internet giants also brings compute or distribution terms, but the post does not disclose them.

Tencent engineers report a one-week practice that used Claude Code plus custom Skills, Commands, and MCP servers to run an 11-stage backend workflow in one terminal session. The post gives reproducible details: one requirement-exploration step used 20 tool calls, 93.8k tokens, and 56 seconds; execution was split into 4 tasks and produced 3 commits. The real point is workflow orchestration, not raw code generation; human review remains at plan, deploy, and review gates.

Tencent Hunyuan open-sourced the 3B-parameter HiVG, claiming 62.7%-63.8% shorter SVG sequences via hierarchical tokenization and better SVG generation metrics than GPT-5.2, Claude-4.5-Sonnet, and some 8B open models. The post reports 0.896 SSIM, 0.114 LPIPS, and 0.957 CLIP-S on Image-to-SVG; the core method packs drawing commands plus coordinates into segment tokens and uses HMN to initialize coordinate embeddings. The part to watch is token design, not parameter count; paper, code, and project page are public.

Tencent Hunyuan and Robotics X released HY-Embodied-0.5; its MoT-2B uses 4B total params with 2B active and ranks first in 16 of 22 embodied evaluations. The post says it uses 100M+ embodied data, 600B+ pretraining tokens, 30M+ mid-training samples, plus visual latent tokens, bidirectional attention, RFT, RL, and online distillation. The key point is a rebuilt edge-oriented embodied stack, not a simple VLM fine-tune.

Yuxian said OpenClaw has issued about 250 security advisories, and v3.2 added stricter defaults, yet broad permissions, network access, and Skill installs still expand risks like file deletion, data leaks, and loss of control. The discussion breaks risk into layers: readable local files, chat data sent upstream, logged-in browser sessions, malicious links or Skills, and automated tasks that fail repeatedly. The practical rule is isolation: separate devices or networks, local-only access or Tailscale, and strict caution with external inputs.

Beijing engineer Feng Qingyang turned OpenClaw installation support into a 100+ person business after starting in January, handling 7,000 orders at about RMB 248 each. Taobao and JD now show hundreds of related listings priced at RMB 100-700; the real story is setup friction and data-isolation risk turning an open-source agent into a service market.

Chinese women are using AI companion apps as emotional substitutes, complicating Beijing’s push for marriage and births; one 21-year-old user said she had 200+ virtual dates in a year and spends at least one hour daily with two AI boyfriends. MiniMax said Xingye and Talkie had more than 147 million users by last September, while Sensor Tower data shows downloads for Xingye and ByteDance’s Maoxiang fell about 95% from monthly peaks last year. The key signal is regulatory: platforms are required to intervene when users develop unhealthy dependence.

Ruan Yifeng’s Issue 381 excerpts talks from Beijing’s AGI-Next summit on Jan 10, covering views from Zhipu, Alibaba Qwen, and Tencent AI leaders on China’s model roadmap. The post cites Lin Junyang saying US compute is 1-2 orders of magnitude larger, Yao Shunyu calling the odds of a China-led top AI company in 3-5 years high, while Lin puts it at 20%. The key split is strategic: Tang Jie points to RLVR in 2025, Lin bets on multimodal foundation agents, and Yao says B2B buyers pay a $200/month premium for stronger models.