Open weights gain at the bottom as the frontier closes at the top
DeepSeek and Qwen keep open models near-frontier and cheap; Meta and Alibaba keep their best tiers proprietary
Summary
The open-vs-closed line is splitting by tier in 2026. Near-frontier open weights are advancing and cheap: DeepSeek V4 (1.6T MoE, open on Hugging Face) and Alibaba's Apache-2.0 Qwen 3.6 keep open models close to the frontier. But the very top is closing: Alibaba keeps Qwen 3.7-Max/Plus API-only, and Meta abandoned open Llama for closed Muse models. Mistral holds an open-weight European position. US closed labs (Openai, Anthropic) face the new wrinkle that export controls gate their top models by nationality while open Chinese weights face no equivalent restriction, an asymmetry reshaping the non-US market.
By the numbers
- 1.6T, DeepSeek V4-Pro params (open weights).
- Apache 2.0, licence on Qwen 3.6 open line.
- Closed, Qwen 3.7-Max/Plus and Meta's Muse Spark.
- 0, export restrictions on open Chinese weights vs. gated US models.
Why it matters
The competitive map is no longer "open vs closed" but "open-and-cheap at the near-frontier vs closed-and-gated at the top." Open Chinese weights gain structural advantage in markets where US models are restricted, while Western leaders monetise closed frontiers, bifurcating the global stack by both licence and nationality.
What to watch
- Whether any lab open-weights a true frontier model in 2026.
- US policy toward open-weight Chinese models.
- Enterprise share shifting to open weights on cost grounds.