Qwen

Alibaba's Qwen3.8 Max jumps 10 points to 56 on the Artificial Analysis Intelligence Index, putting it on par with Claude Opus 4.8. But Kimi K3 still edges it out at a lower per-task cost, and Qwen3.8 Max shows a sharp rise in hallucination rate.

Alibaba announced Qwen3.8-Max, a 2.4T-parameter flagship model targeting coding and long-horizon agentic work, with open weights promised for next week alongside Qwen3.8-27B. The model posted strong third-party benchmark results, ranking #4 in Frontend Code Arena and matching Claude Opus 4.7 on the Vals Index at roughly 2.3x lower cost.

Alibaba is promoting its new Qwen 3.8 model with marketing that frames AI automation as liberating rather than threatening, a departure from the fear-based messaging common among Western AI labs. The company has not disclosed technical specifications, benchmark scores, or pricing for the model.

Alibaba has moved Qwen3.8 Max out of preview into general availability, positioning it as the flagship of the Qwen3.8 series with a 1 million token context window and multimodal input support. The model is priced at $2.00 per million input tokens and $6.00 per million output tokens via OpenRouter.

Alibaba has released Qwen3.8-Max, a 2.4-trillion-parameter model with 95 billion active parameters per query, designed to run autonomous tasks over multiple days. The company claims it hits 93 on PaperBench and rivals Claude Opus 4.8 and GPT-5.6 Sol on internal benchmarks, with open weights arriving next week.

Alibaba has released Qwen3.7 Flash, a vision-language reasoning model with a 1 million token context window aimed at multimodal agents, visual coding, and computer-use tasks. The model is priced at $0.03 per 1M input tokens and $0.13 per 1M output tokens and is available through OpenRouter.

Alibaba's Qwen team has released Qwen-Image-3.0, an image generator that accepts prompts up to 4,500 tokens and can render legible text as small as ten pixels, complex LaTeX formulas, and twelve languages in a single pass. The model is currently invite-only via API, and unlike its predecessor, it likely won't ship with open weights.

Alibaba has released Qwen 3.8, a 2.4 trillion parameter open-weight model that the company claims trails only Fable 5. The multimodal model processes images, videos, and documents, with a preview available through Alibaba's platforms at 10 percent of standard pricing.

China's Cyberspace Administration approved Apple Intelligence for launch in the country, backed by integration of Alibaba's Qwen AI model across Apple's operating systems. The deal ends a two-year delay that began when Apple Intelligence debuted in 2024.

Alibaba's Qwen team released Qwen-AgentWorld-35B-A3B, a 35 billion parameter language world model designed for agentic environment simulation. The model covers seven domains—MCP tool calling, Search, Terminal, Software Engineering, Android, Web, and OS—in a single model with a 262,144 token context window.

Alibaba's Qwen has released Qwen3.7 Plus, a multimodal model with a 1 million token context window. The model accepts text and image input with text output, priced at $0.40 per million input tokens and $1.60 per million output tokens through OpenRouter's API.

Alibaba has released Qwen3.7 Max, the flagship model in its Qwen3.7 series, featuring a 1 million token context window. The text-only model is designed for agent-centric workloads with strengths in coding, office productivity, and long-horizon autonomous execution, and includes explicit prompt caching support.

Microsoft Research has released Fara-7B, a 7-billion parameter small language model designed for computer automation tasks. The model, which took 2.5 days to train on 64 H100 GPUs, can navigate websites to complete tasks like booking restaurants and shopping, using screenshots as input with a 128K token context window.

Alibaba's Qwen team has released Qwen3.6 Flash, a multimodal language model supporting text, image, and video input with a 1 million token context window. The model is priced at $0.25 per 1M input tokens and $1.50 per 1M output tokens, with tiered pricing above 256K tokens.

Qwen has released three models in its Qwen3.6 series: a flagship Max Preview model, a 35B parameter A3B variant, and a 27B parameter base model. All three models are now accessible through OpenRouter's API platform.

Alibaba Cloud has released Qwen3.6-35B-A3B, an open-weight sparse mixture-of-experts model with 35 billion total parameters but only 3 billion active parameters per token. The model features a 262K native context window (expandable to 1M tokens), multimodal input support, and integrated reasoning mode with preserved thinking traces.

Alibaba Cloud has released Qwen3.6 Max Preview, a proprietary frontier model built on sparse mixture-of-experts architecture with approximately 1 trillion total parameters. The model supports a 262,144-token context window and features integrated thinking mode for multi-turn reasoning, priced at $1.30 per million input tokens and $7.80 per million output tokens.

Alibaba's Qwen Team has released Qwen3.6 27B, a 27-billion parameter multimodal language model with a 262,144-token context window. The model accepts text, image, and video inputs and includes a built-in thinking mode for extended reasoning, with pricing at $0.195 per million input tokens and $1.56 per million output tokens.

Alibaba announced Friday that its Qwen AI model will be integrated into vehicles from 10 Chinese automakers including BYD, Geely, Li Auto, and SAIC Volkswagen. The system runs on Nvidia's automotive chip platform and allows drivers to order food delivery, book hotels, and make payments through voice commands, even with limited network connectivity.

Alibaba Cloud released Qwen 3.6 27B, a 27-billion parameter language model, alongside an FP8 quantized version for deployment efficiency. Separately, OpenAI published a privacy filter model on Hugging Face, marking a rare public model release from the company.

Alibaba Qwen has released Qwen3.6-35B-A3B, a 35-billion parameter mixture-of-experts model with 3 billion activated parameters and a 262,144-token native context window extendable to 1,010,000 tokens. The model scores 73.4 on SWE-bench Verified and features FP8 quantization with performance metrics nearly identical to the original model.