Articles Tagged “Qwen”
9 articles found

Qwen3.8-27B Runs a 262K-Context Vision Model Locally
Alibaba's Qwen3.8-27B lands under Apache 2.0 with vision, a 262K context, and a 17GB quantization that runs at 15-30 tokens per second on a laptop.

Qwen3.8-Max Open Weights Make a 2.4T Model Downloadable
Alibaba published Qwen3.8-Max open weights on August 12: 2.4 trillion parameters, 95B active per token, and a 262K context that extends past 1M tokens.

Qwen3.8-Max Packs 2.4T Parameters Into a 1M Context
Alibaba's Qwen3.8-Max is a 2.4-trillion-parameter sparse MoE model with a 1M-token window, priced at $2 per million input tokens and open weights next week.

Qwen3.7 Flash Brings 1M-Token Vision at $0.03 per Million
Alibaba's Qwen3.7 Flash is a native vision-language model with a 1M-token context window, priced at $0.03 per million input tokens with tool calling.

Qwen3.8-Max Benchmarks: What to Watch in the Preview
Alibaba's Qwen3.8-Max preview brings 2.4 trillion parameters and multimodal input, but no benchmark table yet. Here's the baseline to measure it against.

Xiaomi's HarnessX: Agents That Rewrite Their Own Scaffolding
Xiaomi's HarnessX lets AI agents rewrite their own scaffolding mid-task, delivering a +14.5% average gain, with smaller open models benefiting the most.

Qwen-AgentWorld Is an Open Model That Simulates Worlds for AI Agents
Alibaba's Qwen team open-sourced AgentWorld on June 24, 2026 — a language world model that simulates digital environments so AI agents can practice and improve.

Alibaba's Qwen3.7-Plus Pairs Vision With Autonomous Agent Skills at $0.40 per Million Tokens
Alibaba's Qwen team launched Qwen3.7-Plus on June 2, 2026 — a multimodal model combining vision and video understanding with deep reasoning, tool use, and autonomous iteration.

Alibaba's Qwen3.6-Plus Delivers 1M-Token Context and Repository-Level Agentic Coding
Qwen3.6-Plus arrives with a default 1 million-token context window and breakthrough agentic coding performance, enabling AI that can navigate and rewrite entire software repositories autonomously.
