Apsara 2026: Alibaba says Qwen 4 is in training, targets 5-10T-parameter Qwen 4.5/5, reports self-improvement runs and unveils Zhenwu V900 chip
At its Apsara Conference in Hangzhou on 2026-09-22 Alibaba said Qwen 4 is in training, projected Qwen 4.5 and Qwen 5 to reach 5-10 trillion parameters, and reported "recursive self-improvement" runs in which Qwen3.8-Max ran 33 fully automated cycles in a month and lifted its Artificial Analysis score from 40 to 45. It also unveiled the Zhenwu V900 AI chip (Q1 2027) and set a target of over 20 GW of Alibaba Cloud data-center capacity by 2032.
Key facts
- Qwen 4 in training; no release date, price or benchmarks given. Press reports four tier names shown on slides (Qwen 4 Max, Plus, Flash, 27B) - not confirmed in the official release
- Roadmap: Qwen 4.5 and Qwen 5 'projected to scale up to 5 to 10 trillion parameters' (Alibaba press release)
- RSI claim: Qwen3.8-Max ran 33 iterative cycles over one month of fully automated runs (pipeline design, data validation, experiments, error diagnosis); Artificial Analysis score 40 -> 45 (company claim)
- Chip-design demo: 60+ hours of self-improvement and 10,000+ EDA tool calls produced chip bus modules with 42% less area and no performance loss (company claim)
- Zhenwu V900 AI chip: 3x the Zhenwu M890, 216 GB memory, 1,200 GB/s inter-chip bandwidth, FP8/FP4; release Q1 2027. Zhenwu chips serve 650+ customers
- Yitian 730 CPU: +40% SPECint2017/GHz vs Yitian 710
- Eddie Wu (CEO): Alibaba Cloud's global data-center capacity to exceed 20 GW by 2032
- Also: Qwen3.8-LiveTranslate, Qwen-Audio-3.1-TTS-Next, Qwen-Image 3.1 (later in 2026), AgentCore enterprise agent platform, Agent Context memory layer, HPN 8.0 Pro network
What happened
Alibaba used its annual cloud conference to lay out a full-stack plan covering chips (Zhenwu, Yitian), networking and storage, models (Qwen 4 in training, larger successors planned) and enterprise agent platforms. The Qwen team released Qwen3.8-LiveTranslate and the Qwen-Audio-3.1 stack around the same days.
Why it matters
It is the most concrete public scale target from a Chinese lab: 5-10T-parameter models plus a 20 GW data-center target. Alibaba also joined the labs that publicly claim automated self-improvement loops on frontier models, although the 40 -> 45 Artificial Analysis gain is a company claim that has not been independently checked.
Changelog
- 2026-09-29: created
Related events
- Alibaba launches Qwen3.8-Max (2.4T MoE) and open-sources the Qwen3.8 family ★★★★
- Qwen3.8-Flash-Next: 125B MoE with only 6B active previews Qwen 4 architecture ★★★
- Alibaba launches Qwen-Audio-3.1 five-model voice stack and cuts audio API prices up to 95% ★★★
Sources (5)
- officialAlibaba Cloud press room - Alibaba unveils roadmap on full-stack AI strategy
- officialAlizila - Alibaba Cloud's 2026 Apsara Conference: full-stack AI roadmap (403 to our fetcher)
- pressVIR - Alibaba targets 10 trillion parameters with next-generation Qwen 4 model
- pressPandaily - Alibaba puts Qwen4 family into training; roadmap points to 5-10T Qwen4.5 and Qwen5
- pressOrcaRouter - Qwen 4 Max announced at Apsara 2026: the four tiers (secondary)
id: 2026-09-22-alibaba-apsara-2026-qwen-4-roadmap · updated 2026-09-29 · open in the interactive timeline