---
format: "aidr-story-markdown/v1"
id: "abec50fa368223e1f49183ed15c646bf14fd5e7700956ee4a6c261050c8760f7"
canonical_url: "https://aidr.today/abec50fa?lang=en"
title: "Alibaba Qwen3.8 27B Matches GPT 5.6 Luna Performance in First Local Model Frontier Score"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
translation_fallback: null
fallback_fields: []
published_at: "2026-08-17T20:53:05.000Z"
category: "Models"
topics: ["alibaba","qwen","benchmark","open-source","multimodal","nvidia"]
source_urls: ["https://huggingnews.com/ai/update-alibaba-qwen38-27b-matches-gpt-56-luna-performance-in-first-local-ea7210d7","https://x.com/cline/status/2089425906569977896","https://x.com/xenovacom/status/2089435071384076306","https://x.com/sgl_project/status/2089337991181598989","https://x.com/rohanpaul_ai/status/2089363481124593942"]
summary: "The latest Artificial Analysis Intelligence Index shows a score of 52 for the new open weight release from Alibaba, placing it alongside industry leading models like DeepSeek V4-Pro. This benchmark puts the 27B parameter tool in a performance tier previously reserved for proprietary non local systems. The model is natively multimodal and licensed under Apache 2.0 to enable broad developer access. Users running the model on a single Nvidia RTX 5090 with 32 GB VRAM reported speeds of 115 tokens per second, while optimized recipes from SGLang support 206.1 tokens per second."
---

# Alibaba Qwen3\.8 27B Matches GPT 5\.6 Luna Performance in First Local Model Frontier Score

> [Open the canonical story](<https://aidr.today/abec50fa?lang=en>)

**Published:** 2026-08-17T20:53:05.000Z
**Category:** Models
**Topics:** alibaba, qwen, benchmark, open\-source, multimodal, nvidia

## Summary

The latest Artificial Analysis Intelligence Index shows a score of 52 for the new open weight release from Alibaba, placing it alongside industry leading models like DeepSeek V4\-Pro\. This benchmark puts the 27B parameter tool in a performance tier previously reserved for proprietary non local systems\. The model is natively multimodal and licensed under Apache 2\.0 to enable broad developer access\. Users running the model on a single Nvidia RTX 5090 with 32 GB VRAM reported speeds of 115 tokens per second, while optimized recipes from SGLang support 206\.1 tokens per second\.

## Sources

- [Story source](<https://huggingnews.com/ai/update-alibaba-qwen38-27b-matches-gpt-56-luna-performance-in-first-local-ea7210d7>)
- [Story source](<https://x.com/cline/status/2089425906569977896>)
- [Supporting source](<https://x.com/xenovacom/status/2089435071384076306>)
- [Supporting source](<https://x.com/sgl_project/status/2089337991181598989>)
- [Supporting source](<https://x.com/rohanpaul_ai/status/2089363481124593942>)