# Together AI — How to train your own Jev for $17

- Company: Together AI (together.ai)
- Announced: 2026-09-23
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://www.together.ai/blog/how-to-train-your-own-jev
- Record: https://forck.live/items/13488-how-to-train-your-own-jev-for-17
- Subject: Inference platform
- Models affected: together/Tev1-4B-experimental, Qwen3.5 4B
- Pricing: fine-tuning costs about $17.0 for 38,340 examples

40+ Models Chosen for Production...40+ Models Chosen for Production...40+ Models Chosen for Production... Summary We just launched our own Jev-like classifier, together/Tev1-4B-experimental , on top of Qwen3.5 4B on Together’s serverless platform. In this blog post we’ll show you how to fine-tune your own version! Jev has quickly become one of the most talked about model releases in the AI space. It’s a powerful classification model that’s both fast and incredibly cheap to run. Give Jev a piece of state plus predefined questions and it will quickly give back a result in the form of a score, boolean value, or multiple choice answer. This sort of classification model has many real-world applications, such as an e-commerce site evaluating automated customer returns, categorizing ML papers, or even providing a sentiment rating for a piece of text. Today we’re going to fine-tune our own Jev-like classification model that takes state and returns an answer. Our goal is to create a model that can quickly and efficiently answer questions like: Customer message: Hi, I checked my statement and your company charged my card twice for the October subscription. …

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