A quick digest of AI-relevant signals from Chinese tech channels — one opinion worth arguing with, one new model worth testing, and two tool updates for agent workflows.
▸ Text-first agents beat VLM agents — by a quadratic margin (@openclaw1024): A widely-shared take argues VLM is a dead end: 100k tokens of text carries far more information density than images, let alone video. The argument runs like this — if a 1T–10T-parameter VLM agent can solve a problem of difficulty X, an equivalent text-only LLM agent given full context, memory, wiki, and tool access (text/bash/cli/api/mcp) solves 1000X. And the gap keeps widening: by the time VLMs reach 1000X, text agents are already at (1000²)·X. Provocative, but a useful counterweight to multimodal hype.
▸ "Ox 牛来" is being called August's surprise model (@aigc1024): The channel rates it the most impressive model release this month and claims DeepSeek V4-flash-vision-exp can't compete. It's free for 7 days and already live on Cola, OpenRouter, Hermes, and Opencode — worth a spin if you're comparing vision-capable models.
▸ Tonghuashun ships an official A-share data API with MCP support (@https1024): The new Financial-API covers market snapshots, daily K-lines, financials, sector data, limit-up, and dragon-tiger lists. One key works across REST, Python, CLI, and MCP, with local DuckDB for storage — aimed squarely at Cursor/Claude-style agents for quant scripts, financial analysis, and automated pipelines, and a way to retire your self-maintained scrapers. An English version of the announcement was cross-posted, signaling an overseas push.
▸ ChatGPT + Flightpoints plugin for award-mile searches (@knowledge1024): A quick tip — the Flightpoints plugin lets ChatGPT search mileage award tickets directly in chat, saving a trip to airline portals.
Bottom line: multimodal agents are being talked down in favor of text-plus-tools, model churn keeps accelerating, and Chinese data vendors are now shipping MCP-native APIs for the agent ecosystem.