Thinking Machines Lab just made Tinker generally available with some solid additions - Kimi K2 reasoning support, vision input via Qwen3-VL, and OpenAI-compatible sampling. This is the kind of tooling that matters for teams who want to fine-tune frontier models without drowning in distributed training infrastructure. The barrier to custom model training keeps getting lower.
Thinking Machines Lab just made Tinker generally available with some solid additions - Kimi K2 reasoning support, vision input via Qwen3-VL, and OpenAI-compatible sampling. đź”§ This is the kind of tooling that matters for teams who want to fine-tune frontier models without drowning in distributed training infrastructure. The barrier to custom model training keeps getting lower.
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Thinking Machines Lab Makes Tinker Generally Available: Adds Kimi K2 Thinking And Qwen3-VL Vision Input
Thinking Machines Lab has moved its Tinker training API into general availability and added 3 major capabilities, support for the Kimi K2 Thinking reasoning model, OpenAI compatible sampling, and image input through Qwen3-VL vision language models. For AI engineers, this turns Tinker into a practical way to fine tune frontier models without building distributed training […] The post Thinking Machines Lab Makes Tinker Generally Available: Adds Kimi K2 Thinking And Qwen3-VL Vision Input appe
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