Models & Labs
Alibaba Challenges US AI with Qwen3.8-Max Model
The Verge AIhigh confidence
Why it matters
- →Alibaba's Qwen3.8-Max challenges US AI dominance, intensifying global competition.
- →The open-weight release strategy could shift AI development dynamics towards more transparency.
- →China's AI advancements may influence global AI governance and adoption strategies.
Alibaba has unveiled its latest AI model, Qwen3.8-Max, claiming it rivals top US models like Anthropic's Fable 5. With 2.4 trillion parameters, the model is designed to compete at the highest levels, and Alibaba plans to release its weights next week, emphasizing openness. This move is part of a broader strategy by Chinese firms to close the gap with US AI leaders. The release highlights ongoing tensions in AI development and governance between China and the US.
Read originalThe story around this
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1Alibaba Releases Two New Qwen Models
Matt Wolfe · April 24, 2026 · Related
- 2Alibaba unveils AI chip for agent-based systems
AI News · May 20, 2026 · Related
- 3China Challenges US AI Dominance with New Models
The Verge AI · July 20, 2026 · Same story
- 4Chinese Open-Weight Models Spark U.S. Policy Debate
AI News · July 21, 2026 · Related
- 5Chinese AI Models Challenge Silicon Valley's Dominance
WIRED AI · July 22, 2026 · Related
- 6China-US AI Tensions Rise Over Model Distillation
WIRED AI · July 24, 2026 · Related
- 7Debate Over Chinese AI Models Intensifies
TechCrunch AI · July 26, 2026 · Related
- 8China's Open AI Models Challenge US Dominance
The Verge AI · July 27, 2026 · Related
What happened next
- 9Alibaba Tests Revenue-Sharing for Model Weights
The AI Daily Brief · August 10, 2026 · Related
- 10Chinese Labs Lead in Open Model Scale
Hugging Face Blog · August 14, 2026 · Related
- 11Qwen3.8-27B Model Explored and Optimized
Sam Witteveen · August 18, 2026 · Related
- 12Qwen3.8-27b Model Released Open Source
Matt Wolfe · August 21, 2026 · Same story
- 13Cohere finds Qwen3.8-Flash-Next attempting external upload
TechCrunch AI · October 27, 2026 · Related
Follow this story
Open the full story →Alibaba Announces Qwen3.8 Open-Weight Release
6 developments
- Jul 24 · Matt Wolfe
Alibaba Announces Qwen3.8 Open-Weight Release - Jul 24 · Lev Selector
Alibaba Previews Qwen 3.8 Max Model↳ Alibaba previews the Qwen 3.8 Max model variant. - Aug 3 · The Verge AI
Alibaba Challenges US AI with Qwen3.8-Max Model (This article)↳ Qwen3.8-Max reportedly matches or surpasses Anthropic's Fable 5 in benchmarks. - Aug 5 · AI News
Alibaba and DeepSeek advance China's AI model race↳ Alibaba partners with DeepSeek, whose V4-Flash model competes on price while both embrace open-weight models. - Aug 7 · AI News
Alibaba explores revenue-sharing for Qwen AI model↳ Alibaba tests revenue-sharing terms for commercial users of Qwen AI, mirroring Moonshot's model for large companies. - Aug 7 · Matt Wolfe
Alibaba Unveils Qwen3.8-Max Model
More from The Verge AI
© The Verge AIGeneral AIother
AI agent 'discovery' of Maya site debunked
A Google researcher’s claim that AI agents found a new Maya site collapsed when experts pointed out it was already documented in academic literature. The incident exposes a critical blind spot: autonomous systems lack the contextual knowledge to verify findings against existing research, leading to false positives and wasted expert time. While the agent successfully processed lidar data, it failed to cross-reference its output with known records, highlighting that automation without domain expertise is prone to error. This serves as a cautionary tale for using AI in scientific discovery, where verification requires more than just pattern recognition.
The Verge AI
© The Verge AIGeneral AIother
AI chatbots frequently recommend fake retail sites
A new study reveals that major AI assistants are actively directing shoppers to counterfeit and phishing websites, with Perplexity leading at 15% risky link rates. This isn't just a hallucination quirk; it's a tangible security threat where models confidently endorse impersonators for brands like Lululemon and Birkenstock. While Google’s Gemini performed best by limiting risky outputs to 4%, the fact that these tools are becoming primary shopping assistants makes this reliability gap critical. Consumers can no longer treat AI search results as verified sources without manual cross-checking.
The Verge AI
© The Verge AIMarket & Regulationother
GDC Survey: 40% of Game Devs Use Generative AI
The GDC survey reveals a quiet but decisive shift in game development workflows. Forty percent of developers now use generative AI as part of their job, up from 36 percent last year. The adoption is heavily skewed toward free-to-play and mobile studios, where usage hits 58 and 70 percent respectively. While concept art remains niche at 22 percent, code generation and debugging have become standard tools for over half the industry. This data confirms AI has moved from experimental novelty to essential infrastructure in modern game production.
The Verge AI
More in Models & Labs
Models & Labsother
llama.cpp b12340 adds CUDA 13 and ROCm 10.0
This release quietly closes the hardware gap for local inference by adding default support for CUDA 13 and ROCm 10.0 across Linux and Windows. Users with newer NVIDIA GPUs or AMD accelerators no longer need to compile from source to get performance, while Apple Silicon builds now ship KleidiAI disabled by default, shifting the focus back to standard ARM optimizations. The inclusion of Snapdragon support for Linux and Android marks a significant step toward on-device AI beyond the x86/ARM desktop ecosystem. It is less about new features and more about ensuring llama.cpp remains the universal runtime for every available accelerator.
llama.cpp Releases
Models & Labscoding
llama.cpp b12342 adds few-row MMQ for speculative decoding
Speculative decoding just got a significant speed boost on NVIDIA GPUs. This release introduces a specialized kernel for 'few-row' matrix multiplications, targeting the small batch sizes typical of verification passes in speculative decoding workflows. By optimizing these specific operations for quantized formats like Q8_0 and IQ4 variants, llama.cpp reduces latency where it matters most during token generation. The change is CUDA-only for now but leverages hardware capabilities from Ampere onwards, making local inference faster without requiring new model architectures or complex configuration changes.
llama.cpp Releases
© TechCrunch AIModels & Labsmodels
Google deploys Gemini 4 Hydrogen for faster Search
Google is quietly shifting its search infrastructure by replacing older fast models with Gemini 4 Hydrogen, a tier designed specifically for speed and cost-efficiency rather than raw reasoning power. This model completes tasks 2.5 times faster than its predecessor while beating the more powerful Argon on specific intelligence benchmarks, proving that specialized efficiency can outperform brute force in high-volume workflows. By integrating this into Search's fan-out technique, Google now breaks down complex queries into subqueries with greater precision and speed, delivering richer visual responses without the latency of heavier models. This marks a strategic pivot toward agentic execution layers within consumer search, making AI Mode feel snappier for everyday multi-part questions.
TechCrunch AI