Qwen 3.8 27B (Fully Tested on Local Mac 48GB) + Hermes: I might CANCEL Claude & Codex NOW!
Thank you to TestSprite for sponsoring this video: https://www.testsprite.com/?via=aicodingki-dwGithub repo for TestSprite: https://github.com/TestSprite/testsprite-cli
In this video, I'll be telling you about Qwen 3.8 27B, a new open-weight local AI model that is built for agent workflows, vision, computer use, long context, and tool calling. I’ll also explain why I did not run it on KingBench, how it compares to frontier models, and how to run it properly with Ollama, LM Studio, and Hermes Agent.
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Key Takeaways:
🚀 Qwen 3.8 27B is an Apache 2.0 open-weight model that can run locally on your own hardware.
🧠 It is not meant to compete as a frontier reasoning model, but it performs extremely well as a local agent brain.
👁️ The model is a native vision-language model with support for images, documents, diagrams, screens, and video.
📏 Qwen 3.8 27B supports a massive 262K native context window, extendable up to 1 million tokens with RoPE scaling.
💻 It performs especially well on agent, coding, browser, computer-use, and multimodal software engineering benchmarks.
⚙️ Ollama and LM Studio both offer simple ways to run the model locally, with day-one quantized model support.
🔧 Setting the context length properly is critical, because the default settings may waste most of the model’s long-context capability.
🧰 Tool calling works smoothly through Ollama and LM Studio, making Qwen 3.8 27B a strong fit for Hermes Agent.
🤖 Hermes Agent can use Qwen 3.8 27B through a custom OpenAI-compatible local endpoint for a complete local agent stack.
👍 Overall, Qwen 3.8 27B is one of the most impressive local agent models available, especially for long, tool-heavy workflows. Receive SMS online on sms24.me
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