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The Evolution of Qwen: From 7B to 2.4T, a Full Retrospective of Alibaba's AI Model Series

Alibaba Cloud's Qwen series began with Tongyi Qianwen in April 2023, open-sourced Qwen-7B in August 2023, launched the first Qwen3-Max-Preview with over 1 trillion parameters in September 2025, and ultimately evolved to an open-weight model with 2.4 trillion parameters. In 2024, three generations—Qwen1.5, Qwen2, and Qwen2.5—were released in succession; Qwen2.5's pre-training data grew from 7 trillion to 18 trillion tokens, and model downloads exceeded 40 million. In 2025, Qwen3 adopted a hybrid thinking mode, covering 119 languages, and Qwen3-Next-80B-A3B claims training costs of only 10% of Qwen3-32B and 10x higher inference throughput above 32K tokens.

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Google Releases Gemini 4 Argon, Topping Multiple Leaderboards and Focusing on Cybersecurity Defense

Google has released its new-generation flagship model Gemini 4 Argon, which scores 77.9% on DeepSWE v1.1, surpassing Claude Opus 5.5's 74.2% and GPT-6 Astra's 74.1%, and tops the Vals Index with 68.90%. The model supports output of up to one million tokens, and during the promotional period costs $2 per million input tokens and $10 per million output tokens, with a per-question cost of about 40% of Astra's. It is currently available only to vetted cybersecurity defense teams, with the first batch entering Google's Fairwind program.

OpenAI Team Responds to Computer Use Progress Doubts, Recaps One-Week Sprint on Decisions API

In a podcast after OpenAI DevDay, Ari Weinstein, who is in charge of the Computer Use agent, responded to Dwarkesh's doubts about Computer Use progressing slowly, saying it is now completely different from a few months ago because the model has become better at debugging and retrying, and can write JavaScript to execute multiple steps at once while combining screenshots, accessibility, DOM, and Playwright. He also mentioned that Dots provides each Dot with a cloud Linux virtual computer, and that Computer Use has entered the Agents API. Nikunj Handa, head of the OpenAI API team, introduced updates to GPT-6 such as asynchronous tool calling, mid-turn steering, WebSockets, UltraFast inference, prompt caching and pre-warming, and compaction, and said the Decisions API is based on Luna weights, with no new model trained, and took only about a week from the emergence of the idea to a prototype.

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The Father of OpenAI Reasoning Noam Brown's Latest Interview: Mathematics Is Just an Appetizer for the Multi-Agent Era

OpenAI researcher and core o1 author Noam Brown said in the latest podcast that multi-agent systems are a way to change inference-time compute from serial scaling to parallel scaling, but in solving the Millennium Prize Problems, multi-agent systems account for at most 10% of the credit; the core is still that the model itself is sufficiently powerful. He revealed that when 5.6 was released, they had a truly formed multi-agent system for the first time, provided in the form of Ultra Mode, with 4 Agents by default and adjustable higher; with 4 Agents, the problem-solving speed is about twice as fast, and tests scaled up to as many as 16 Agents.

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AIhub Monthly Roundup: September 2026 — Tracking Animal Populations, Recommender Systems, and an Interview with Ken Goldberg

AIhub has published its September 2026 monthly roundup, covering an interview with roboticist Ken Goldberg, tracking wildlife populations with deep learning, early-stage ranker optimization for large-scale recommender systems, and research on how external knowledge flows through AI systems. This month, the new GPT-series model GPT-6 Astra was made available to paying users, and Sebastian Raschka wrote about his first impressions; several Fields Medalists signed a statement warning that using generative AI for mathematical research involves a misalignment between purpose and results.

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Ant Ling open-sources two 6B models in the Ming-Image-0.1-Design series

Ant Ling has open-sourced the Ming-Image-0.1-Design series, comprising two 6B models: Design generates complete visual designs such as UIs, infographics, and posters from text requirements, while Layer decomposes a design image into 2–9 semantically independent RGBA layers; Design Skill and PPT Skill are also open-sourced. In the UI/UX Design evaluation updated by Artificial Analysis on September 18, 2026, Design ranks 1st among open-source models with an Elo score of 1082; Layer achieves the best results on all 12 metrics of Crello-Test, reducing single-inference time from 795 seconds to 183 seconds. After Ant's internal Huamei integrated Layer, the time to first obtain editable layers dropped from over 5 minutes to about 40 seconds.

Debating RSI, the China-US gap, and uneven model capabilities with Epoch AI's JS Denain

In episode 19 of the Interconnects podcast, Nathan Lambert and JS Denain, head of the insights team at Epoch AI, discuss RSI, the China-US model gap, and uneven capabilities. JS believes the evidence in public blog posts from OpenAI and Anthropic is insufficient to prove that AI is about to self-accelerate, but the 2x monthly growth in Codex research spending mentioned in OpenAI's blog post is worth noting; both hold highly uncertain views on where AI is heading.

TypeSafe CEO Diogo Almeida on Jev: Building a System One Model for Production, Not for God

InstructGPT paper author and TypeSafe CEO Diogo Almeida detailed his new model Jev on the Latent Space podcast, describing it as a System One large programmatic model oriented toward code consumption, with its core innovation being an unpublished RLCD (reinforcement learning for calibrated decision-making), optimized for "intelligence per dollar" rather than human preference feedback. He criticized RLHF for causing mode collapse, sycophancy, and hallucinations, arguing that safety alignment suits products like ChatGPT but fragments intelligence at the API layer, and said TypeSafe would rather be seen as a data lab, refusing to publish benchmark tests. He revealed that Jev's daily token consumption has exceeded one trillion since launch, and previewed follow-up models such as ReasoningJev.

AIUC Completes $40 Million Series A, Launches AIUC-1 Agent Safety Standard and Insurance Program

AIUC announced the completion of a $40 million Series A funding round, led by Ribbit Capital and First Harmonic, with customers including Cursor, Harvey, Lovable, and ElevenLabs. Its AIUC-1 standard covers agent safety, security, and reliability, requiring thousands of simulated tests each quarter for jailbreaks, hallucinations, and data leaks, with a certification period of about 3 to 10 weeks. ElevenLabs has purchased the first AI agent insurance policy, underwritten with participation from Lloyd's of London, and AIUC's evaluation results are used directly for pricing.

Ant Ling Open-Sources Native Multimodal Model Ling-3.0-flash-VL

Ant Ling has released and open-sourced Ling-3.0-flash-VL, the first native multimodal large model in the Ling series. Built as an extension of the Ling-3.0-flash MoE architecture, it has 124B total parameters and 5.5B activated per inference, natively supports image, text, and video inputs, and has a 256K Token context window. The company says native multimodal joint training improved the model's score on the Artificial Analysis Intelligence Index v4.1.1 by 4 points over the text-only version, and it introduces a visual feedback loop of observe, act, verify, and correct for front-end replication, GUI Agent, and medical report interpretation. The model is now available for free trial on Ling Studio, and the BF16 and FP8 versions have been open-sourced on Hugging Face and ModelScope.

Latest Open Source Model Roundup, Issue 24: Motif-3, GLM-5.3, Hy4-preview, and Open Source License Changes

The Interconnects Issue 24 open source model roundup notes that in 2026 Western vendors shifted to Apache 2.0, while leading Chinese vendors instead tightened their licenses: Zhipu's GLM-5.3 changed from MIT to a custom license, requiring model service providers with annual revenue exceeding $10 billion to first pass a Z.AI security review, and Kimi K3 and MiniMax M3 also attached commercial agreements or revenue thresholds. The models included in this issue are the MIT-licensed Motif-3, Xiaohongshu dots-studio's dots3-note-prev, Qwen3.8-Flash-Next (125B-A6B, including 51B n-gram embeddings, using GDN and Qwen Sparse Attention), GLM-5.3-Flash, which is being trialed first on OpenRouter and OpenCode under the name Ox-Alpha, Tencent's Hy4-preview, as well as NVIDIA Nemotron-3.5-Lightning-30B-A3B, Ant Group's Ling-3.0-flash, and Qwen3.8-2.4T-A95B.