On November 5, 2026, Thinking Machines Lab introduced Inkling 2 Small, a mixture-of-experts model with 594 billion total parameters and 17 billion active, with image input and variable effort, first available under closed weights on Tinker. For teams evaluating an open-weight ‘flash’ model for agentic coding, the real story is not the parameter total but the gap between today’s closed access and the Apache 2.0 weights promised next week.

On 17 October 2026, DeepSeek released and open-sourced V4.1 Flash 1017 under the MIT license: a 763-billion-parameter MoE with a one-million-token context and self-feedback RL post-training that improves coding and agent use. Existing deepseek-flash API users get it with no code change and no price increase.

On August 13, 2026, DeepSeek moved V4-Pro to general availability and published its weights on Hugging Face under an MIT license. Independent benchmarks rank it third globally, but only three points ahead of its smaller sibling V4-Flash.

On August 28, 2026, Tencent posted Hy4 preview to Hugging Face: a mixture-of-experts model with 770 billion parameters, only 49 billion of which activate per request, tuned for software engineering, research and finance. The headline is not the size — it is that open weights are now a distribution channel.

On July 31, 2026, DeepSeek upgraded its V4 Flash model through re-post-training alone, with zero architecture changes. The result: the smaller 13B active parameter model now outperforms the larger V4 Pro on nine coding benchmarks.