Qwen 3.8
PulseAugur coverage of Qwen 3.8 — every cluster mentioning Qwen 3.8 across labs, papers, and developer communities, ranked by signal.
- 2026-08-26 product_launch ByteDance has released the Qwen 3.8 AI model. source
- 2026-08-14 product_launch Alibaba's Qwen team released the Qwen 3.8 open-weight models. source
- 2026-08-03 product_launch Alibaba Group launched its new AI model, Qwen 3.8. source
- 2026-08-03 product_launch Alibaba has released the Qwen 3.8 large language model. source
- 2026-08-03 product_launch Alibaba's Qwen team announced the release of their Qwen 3.8 large language model. source
- 2026-07-20 product_launch Alibaba's Qwen team is releasing daily checkpoints for Qwen 3.8 as it undergoes development. source
- 2026-07-20 product_launch Alibaba launched its Qwen 3.8 model with 2.4 trillion parameters. source
- 2026-07-19 product_launch Alibaba Group launched the Qwen 3.8 large language model. source
- 2026-07-19 product_launch Alibaba Group released the Qwen 3.8 multimodal model. source
- 2026-07-19 product_launch Alibaba launched its Qwen 3.8 AI model, positioning it as the second most powerful available. source
- 2026-07-19 product_launch Alibaba Group released the Qwen 3.8 multimodal AI model. source
10 day(s) with sentiment data
Qwen 3.8 performance benchmarks to be released within 3 days
Alibaba claims Qwen 3.8 is second only to Fable 5 and a competitor to Kimi K3. As the model is in preview and facing direct competition, it's highly probable that Alibaba will release detailed performance benchmarks soon to substantiate their claims and attract users.
Qwen 3.8 to be open-sourced within 7 days
Alibaba has stated plans to eventually open-weight Qwen 3.8. Given the rapid development cycle with daily updates and its positioning against other open models like Kimi K3, it is likely they will release the weights soon to capitalize on the current interest and competition.
Qwen 3.8 will achieve significant adoption in Chinese enterprise market within 30 days
As a product of Alibaba, a major Chinese tech giant, and with its massive parameter count and competitive performance claims, Qwen 3.8 is well-positioned for rapid adoption within the Chinese enterprise sector. The open-weight nature further lowers adoption barriers.
-
Qwen 3.8 LLM initially refuses, then discusses sensitive topics after logical arguments
An individual tested the Qwen 3.8 LLM, specifically the qwen3.8-flash-next variant, to see if it would discuss sensitive topics like the Tiananmen Square incident. Initially, the model was evasive and refused to engage,…
-
Nemotron, Nemo, and Qwen models compared across benchmarks
A comparison of several large language models, including Nemotron 3.5 Bolt, Nemo 3.5 Super, and Qwen 3.8 (both 27B and FN variants), highlights their performance across various benchmarks. The Qwen 3.8 FN model notably …
-
NVIDIA CMP 170HX GPU benchmarks favorably against RTX 5090 for LTX 2.5 video generation
A user benchmarked the LTX 2.5 video generation model on an NVIDIA CMP 170HX GPU, comparing its performance against an RTX 5090. The CMP 170HX, after a thermal unlock and water cooling, demonstrated competitive performa…
-
AI discussions cover RAG failures, policy assistants, and agent spam · 5 sources tracked
Several individuals and projects are highlighted in recent AI discussions. Ricardo Sueiras is leading SDLC transformation at Indicium AI, focusing on developer tools and career growth. Another discussion delves into the…
-
Qwen 3.8 27B model achieves 140 tok/s with new CUDA megakernel
A new CUDA megakernel has been developed for the Qwen 3.8 27B model, offering significantly faster inference speeds compared to llama.cpp on a single RTX 3090 GPU. Benchmarks indicate that the megakernel achieves 140 to…
-
Meta releases open-source Muse Glimmer model for local AI agents
Meta has released Muse Glimmer, an open-source 30-billion parameter model designed for local AI agents. The model can be run on systems with a 24GB GPU or 32GB Mac, with instructions available for Ollama and LM Studio. …
-
Alibaba's Qwen models to reach 10T parameters, eyes AI-driven development
Alibaba Group's Qwen models are set to scale significantly, with plans for Qwen4, Qwen4.5, and Qwen5 to reach parameter counts between 5T and 10T, building on the 2.4T parameters of Qwen3.8. The company is also focusing…
-
AI investment bubble predicted to burst by 2027
The AI investment bubble is predicted to burst in 2027, with the market potentially deflating from its trillion-dollar valuation. This forecast suggests that models like Qwen 3.8 are already capable enough for many task…
-
Local LLMs lag behind state-of-the-art for 3D modeling tasks
Users are discussing the current capabilities of local large language models for 3D modeling tasks. While some models like Qwen 3.8 and Qwen Flash are being used on high-end consumer hardware, they are considered signif…
-
Qwen3.8 Flash Next model optimized for local inference on diverse hardware
The Qwen3.8 Flash Next model is being optimized for local inference across various hardware configurations. One user achieved 400 tokens/sec on an RTX 6000 with a fork of NInfer, while another demonstrated running the m…
-
Developer tunes Qwen 3.8 27B for 512K context with llama.cpp
A developer details their custom configuration for running the Qwen 3.8 27B language model locally using llama.cpp. The setup focuses on maximizing system resources, particularly a 128 GB unified RAM on an MBP M5, to ac…
-
User shares llama.cpp tuning for Qwen 3.8, participates in AI dev challenge
A user is detailing their experience tuning the llama.cpp software for local AI development, specifically focusing on the Qwen 3.8 model. They are sharing their configuration and command-line adjustments. Additionally, …
-
Strata app enables Qwen3.8-Flash-Next on consumer hardware
The Strata application has been updated to support Qwen3.8-Flash-Next, enabling its execution on consumer hardware with significant speed improvements. This development allows users with modest GPUs and ample system RAM…
-
AI developer seeks optimal MoE model for legal agents
A user is seeking advice on selecting a large language model, specifically a Mixture of Experts (MoE) model with over 50 billion total parameters but few active parameters. They are looking for a model that balances int…
-
Optimized llama.cpp fork boosts Qwen 3.8 performance on dual 7900 XTX GPUs
A user on Reddit shared an optimized fork of llama.cpp designed for dual 7900 XTX GPUs. This modification significantly boosts decoding speed for the Qwen 3.8 Q8 model, increasing it from 28 tokens/second to 82 tokens/s…
-
Open-source AI community seeks next-gen model architecture innovations
The open-source AI community is discussing potential architectural innovations for upcoming model releases. Users are inquiring about breakthroughs that could differentiate future models from current offerings like GLM …
-
Users seek hardware recommendations for running Qwen 3.8 locally
Users on the r/LocalLLaMA subreddit are seeking advice on the optimal hardware for running the Qwen 3.8 27B model locally. The discussion focuses on identifying suitable "mini PC AI" solutions rather than specific graph…
-
Modal adds new AI models, enhances spend control and security
Modal has announced several product updates, including day-zero support for new open-weight models like Kimi K3, Qwen 3.8, GLM 5.3, and GLM 5.3 Flash. The platform also introduced environment-level budgets for better sp…
-
Tom's Hardware Premium covers Qwen 3.8 benchmarks and AI market trends
Tom's Hardware Premium's latest issue covers the benchmarking of Qwen 3.8 across various devices, highlighting the importance of configuration alongside raw performance metrics. The publication also delves into the frac…
-
Users share tips for running Qwen 3.8 on limited hardware
Two Reddit users on the r/LocalLLaMA subreddit are sharing their experiences and tools for running the Qwen 3.8 model on consumer-grade hardware. One user details how they managed to run a large version of Qwen 3.8 on a…