Loading...
11 entries with this tag
One new research article published: Qwen3.8-Max, Alibaba's 2.4T-parameter sparse MoE model with open weights coming next week, 16-day autonomous coding project, and the first model to reproduce and improve upon a research paper without human intervention.
Alibaba released Qwen3.8-Max on August 3, 2026 — a 2.4T-parameter sparse MoE model with 95B active parameters, 1M-token context, and open weights coming next week. Covers the architecture, benchmark results (86.6 Terminal-Bench 2.1, 56.6 DeepSWE 1.1, 73.5 FrontierSWE), the 16-day autonomous coding project (oh-my-cli), research paper reproduction with improvement, multimodal capabilities, and the strategic implications for the open-weight frontier.
One new research article published: deep analysis of Alibaba's Qwen3.8-Max-Preview announcement at WAIC Shanghai — a 2.4T-parameter multimodal MoE claiming 'second only to Fable 5' with no benchmarks, no model card, and an open-weight release promised 'soon.'
Alibaba previews Qwen3.8-Max on July 19, 2026 at WAIC Shanghai — a 2.4T-parameter multimodal MoE claiming 'second only to Fable 5' performance. No benchmarks, no model card, no active-parameter count, no license yet. Open weights promised 'soon.' Available now via Token Plan, Qoder, and QoderWork at 10% preview pricing. Analysis of what's confirmed, what's claimed, and what to wait for.
Alibaba's Qwen team released Qwen3.7-Max, a next-generation proprietary flagship designed for the agent-centric era with 1M-token context, deep reasoning, and strong coding/agent benchmarks. Paired with the open-source Qwen-AgentWorld-35B-A3B (a language world model covering 7 agent domains), the release positions Qwen3.7-Max at 90/100 on BenchLM overall, #6 in coding, and ahead of DeepSeek-V4-Pro on Terminal-Bench 2.0 — while remaining within 0.2 points on SWE-bench Verified.
June 19: Two major research articles — Zhipu AI's GLM-5.2 (1M-context open frontier coding model with IndexShare architecture) and Alibaba's Qwen-Robot Suite (three-model embodied AI stack). Both releases signal a decisive shift: open-source from China is challenging the closed-weight elite on both digital coding and physical robotics.
Alibaba's Tongyi Lab released the Qwen-Robot Suite on June 16, 2026 — three foundation models (Qwen-RobotNav, Qwen-RobotManip, Qwen-RobotWorld) that bridge the gap between digital intelligence and physical action. RobotManip tops RoboChallenge with 20% relative improvement over π0.5, RobotNav achieves 76.5% on VLN-CE RxR, and RobotWorld ranks 1st on EWMBench. All models are open-weight with technical reports on arXiv.
June 16: One major research article published — deep-dive on Alibaba's Qwen3.7 Max & Plus family. Analysis of the open-to-closed pivot, 35-hour autonomous kernel demo, verbosity cost trap, and the dual-model strategy positioning against Opus 4.7 and GPT-5.5.
Alibaba's Qwen3.7 family — Max (closed-weight flagship, 1M context, SWE-Bench Pro 60.6%, $2.50/$7.50) and Plus (multimodal agent, vision+video, $0.32/$1.28) — represents a strategic pivot from open-weight leadership to closed-weight enterprise competition. Max scores 56.6 on the AA Intelligence Index (#5 overall, highest Chinese model), leads Opus 4.6 on agentic coding benchmarks, and completed a 35-hour autonomous kernel-optimization demo. Plus adds vision-language capabilities at roughly 1/6 the cost. This article analyses the full Qwen3.7 landscape, the open-to-closed pivot, benchmark reality, the verbosity cost trap, and where both models fit in the 2026 frontier.
Qwen3.7-Max is Alibaba's new proprietary agent foundation model, released May 20, 2026. It challenges the April 2026 frontier trio (DeepSeek-V4-Pro, GPT-5.5, Claude Opus 4.7) by combining coding agent leadership (69.7% Terminal-Bench, 60.6% SWE-Pro), office productivity (87% SpreadsheetBench), and 35-hour autonomous execution. Available via Alibaba Cloud Model Studio API only.
Alibaba's Qwen model family — open-weight leaders (Qwen3.6-27B) and closed-weight pivot (Qwen3.7 Max/Plus); SEA-LION regional variant