AI roundup
Qwen3.8-Flash-Next: 6B active, 125B+ total
Thu 27 August 2026
Alibaba's MoE preview beats DeepSeek-V4-Flash on DeepSWE 1.1 at 46% of the active params
| Architecture | MoE, 125B+ total / 6B active, 512 experts |
| Context Window | 262,144 native / 1,000,000 via YaRN |
| Coding (DeepSWE 1.1) | 58.7 (vs 54.4 DeepSeek-V4-Flash) |
| Coding (SWE-bench Pro) | 62.5 |
| API Pricing | $0.16 in / $0.47 out per 1M tokens |
| Training Cost | ~1/9 of Qwen3.7-Plus |
Key takeaways
- 6B active beats 13B: Outperforms DeepSeek-V4-Flash on DeepSWE 1.1 (58.7 vs 54.4) with less than half the activated parameters per token (10 routed + 1 shared expert).
- 20M n-gram embeddings: Built-in bigram/trigram lookup at layer 2 (51B params) for retrieval-augmented reasoning without external vector DB calls.
- Quantized deployable: Unsloth quants available at 72.5GB (UD-IQ1_S) and 78.9GB (UD-Q2_K_XL), confirmed running on DGX Spark for local agent testing.
Source: Simon Willison