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Alibaba releases Qwen3.8-Max with 2.4T parameters and autonomous coding

Alibaba's Qwen has announced Qwen3.8-Max, its most capable model to date, featuring 2.4 trillion parameters. This new model demonstrates advanced autonomous coding capabilities, capable of self-evolving development for over 10 days without human intervention. Qwen3.8-Max also showcases native multimodal intelligence, integrating vision as a continuous feedback loop for planning and execution, and will be released with open weights next week alongside Qwen3.8-27B. AI

IMPACT Sets a new benchmark for autonomous coding and multimodal integration, potentially accelerating enterprise adoption of advanced AI agents.

RANK_REASON Frontier-lab model release with system card and open weights announcement.

Read on X — Qwen (Alibaba) →

AI-generated summary · Google Gemini · from 11 sources. How we write summaries →

Alibaba releases Qwen3.8-Max with 2.4T parameters and autonomous coding

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0 / 100
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Frontier Release
Frontier-lab model release with system card and open weights announcement.
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11 independent sources
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Topics
model release, product
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50 days old
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COVERAGE [11]

  1. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    VL Performance - English Version https://t.co/95NsmZI1hz

    VL Performance - English Version https://t.co/95NsmZI1hz

  2. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    LM Performance - English Version https://t.co/Bi9WefHHLB

    LM Performance - English Version https://t.co/Bi9WefHHLB

  3. X — Qwen (Alibaba) TIER_1 Italiano(IT) · Alibaba_Qwen ·

    Visual agentic intelligence https://t.co/bUhsuYAqzb

    Visual agentic intelligence https://t.co/bUhsuYAqzb

  4. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    Dynamic workflows to quant strategies https://t.co/cGL1EeJdeK

    Dynamic workflows to quant strategies https://t.co/cGL1EeJdeK

  5. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    16 days autonomous coding https://t.co/OX0RN7itxP

    16 days autonomous coding https://t.co/OX0RN7itxP

  6. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    Cowork: Any role, build beyond https://t.co/Hggkj3DFSs

    Cowork: Any role, build beyond https://t.co/Hggkj3DFSs

  7. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    VL Performance https://t.co/gsuM0XTYTY

    VL Performance https://t.co/gsuM0XTYTY

  8. X — Qwen (Alibaba) TIER_1 English(EN) · Alibaba_Qwen ·

    LM Performance https://t.co/zMUpEbIupH

    LM Performance https://t.co/zMUpEbIupH

  9. X — Qwen (Alibaba) TIER_1 Français(FR) · Alibaba_Qwen ·

    📢Meet Qwen3.8-Max — our most capable model to date.

    📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: - Autonomous coding: 10+ days of http…

  10. Mastodon — mastodon.social TIER_1 Türkçe(TR) · [email protected] ·

    @technofili AMD's move is very good. The 16B total 16B MoE structure and MI300X optimization have brought a serious breath of fresh air to the open-source ecosystem. Especially all 2.8B active

    @ teknofili AMD’nin hamlesi çok iyi. 16B toplam16B MoE yapısı ve MI300X optimizasyonu, açık kaynak ekosistemine ciddi bir soluk getirmiş. Özellikle tüm2.8B aktif parametre ile düşük-verim dengesi, edge cihazlar ve düşük malilatency senaryoları için ideal. Kod ve checkpoint’lerin …

  11. Mastodon — mastodon.social TIER_1 Türkçe(TR) · [email protected] ·

    @teknofili Qwen 3.6 27B is truly impressive. I am eagerly awaiting details on alternatives like Emu3.5 and BAGEL. The vLLM-Omni integration is also [of interest] in terms of performance.

    @ teknofili Qwen 3.6 27B gerçekten etkileyici. Emu3.5 ve BAGEL gibi alternatiflerin detlarını merakla bekliyorum. vLLM-Omni entegrasyonu da performans açısından kritik önem olmalı. Linkteki detaylı karşılaştırmayı hemen okuyup notlar alıyorum, açık kaynak dünyistemi hızla büyüyor…