Alibaba Unveils Qwen3.8-Flash-Next with Open Weights
Alibaba has introduced the new Qwen3.8-Flash-Next model, which shows impressive results in tests, surpassing Claude Opus 4.6 Max.
Alibaba has unveiled Qwen3.8-Flash-Next with open weights, and it is already outperforming Claude Opus 4.6 Max in several tests.
This is not yet a full Qwen4, but an early preview of its architecture.
The model features 125 billion parameters for the main model plus 51 billion parameters for n-gram representations, with only 6 billion parameters activated per token.
Training costs were approximately 9 times cheaper than Qwen3.7-Plus, yet the model proved stronger in programming and office tasks.
Key results:
- SWE-bench Pro — 62.5 vs. 53.4 for Claude Opus 4.6 Max
- SWE-bench Multilingual — 81.0
- CoWorkBench — 73.9
- JobBench — 55.7
- Toolathlon — 73.5
- LiveCodeBench — 91.9
- GPQA Diamond — 91.7
- IFBench — 81.3
The native context is 256K tokens, expandable to 1 million through YaRN.
With a context of 1 million tokens, preprocessing speeds up by 7.6 times, and generation by 4.9 times.
A total of 6 billion active parameters per token, with performance already comparable to Opus in agent tasks and programming.
The model will soon be available via API, priced at $0.16 per 1 million input tokens and $0.47 per 1 million output tokens.
Why it matters
AnalysisThis news is significant as the new Qwen3.8-Flash-Next model demonstrates substantial improvements over previous versions, which could impact the development of artificial intelligence technologies.
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