'Open-source' in AI doesn't mean what it means in software. MIT and Apache 2.0 let you do almost anything; the Llama License requires a separate deal above 700M MAU; old Gemma terms let Google change rules unilaterally (Gemma 4 switched to Apache 2.0). This guide maps what you can and can't do by license type.
Qwen3.8-Flash-Next: open-weight preview of the Qwen4 architecture, 125B total parameters with only 6B active (plus a 51B N-gram embedding), 262K native context extensible to 1M, Qwen Community License 1.0 (not Apache 2.0). Official benchmarks show it beating both its own 27B dense model and the 397B Qwen3.7-Plus on agentic coding (DeepSWE 1.1: 58.7) and scoring highest on CoWorkBench long-horizon office tasks (73.9) — but no official API pricing or independent third-party testing exists yet
DeepReinforce's Ornith 1.5 family, trained with self-improvement RL: the 397B flagship scores 86.0 on SWE-bench Verified, matching Claude Opus 4.8; the 35B-A3B activates only 3B parameters per token yet leads every coding benchmark in its class; the 9B runs on phones. MIT-licensed, fully open-source.
Qwen is the most-downloaded model family on HuggingFace, spanning sizes from 0.8B to 2.4T. In August 2026, Alibaba open-sourced a Max-tier flagship for the first time (Qwen3.8-2.4T-A95B) — but swapped the customary Apache 2.0 license for custom terms. Meanwhile the other new release, Qwen3.8-27B, runs native vision on laptop-class hardware and is the only one shipping under Apache 2.0. This post traces the family from 2023 through generation 3.8, explains how the open line and the commercial line split apart, and helps you pick the right model at each tier.
The main on-device LLMs in 2026 are Gemma 3n, Qwen 3.5 Small, Llama 3.2, Phi-4-mini, Ministral 3, and SmolLM3. Sub-3B quantized models can hit 30-50 tokens/sec on phones with 8GB RAM, but RAM, thermal throttling, and context window remain hard constraints.
2026 Q1 saw a full-blown open-source model explosion: on the LLM front, GLM-5, Kimi K2.5, and Qwen3.5 caught up with closed-source models; Embedding and Reranker are dominated by Qwen3 and BGE; speech has Voxtral TTS and Whisper V3; image has FLUX.2; and video has Wan 2.2 rivaling Sora. This is the complete navigation map.