AionLabs: Aion-2.0 vs ByteDance: UI-TARS 7B

AionLabs: Aion-2.0 is a text model from AionLabs, released on 23 February 2026. ByteDance: UI-TARS 7B is a text model from ByteDance, released on 22 July 2025. Both are served through api14 under the model ids aion-labs/aion-2.0 and bytedance/ui-tars-1.5-7b, and both take text in and return text out, so at first glance they look interchangeable. The differences show up in what each one accepts as input and which request parameters it honours.

Aion-2.0 has a context window of 131072 tokens, while UI-TARS 7B sits at 128000 tokens, which is close enough that context length should not drive your decision. The real split is modality and parameter support. UI-TARS 7B accepts images as well as text, so it is the only one of the two that can look at a screenshot or a diagram alongside your prompt. Aion-2.0 is text only. On the parameter side, Aion-2.0 supports tools, tool_choice, response_format, reasoning and include_reasoning, which makes it the one to reach for when you need function calling or an exposed reasoning pass. UI-TARS 7B instead supports structured_outputs, logprobs, top_logprobs, logit_bias, seed, stop, frequency_penalty, presence_penalty, repetition_penalty and top_k, which gives you tighter control over sampling and token level output.

For a task that is purely text and needs the model to call functions, chain tool calls or emit a reasoning trace you can inspect, Aion-2.0 is the natural pick. For a task where the input includes an image, or where you want log probabilities, a fixed seed for reproducibility, or structured outputs, UI-TARS 7B is the one that can do it. If your workload is plain text generation with no tools and no images, both will work, and the deciding factor becomes cost. UI-TARS 7B is the cheaper of the two on both input and output, so when capability does not separate them, it is the more economical call.

Calling either model through api14 works the same way, because the gateway exposes an OpenAI-compatible interface. You point your client at the api14 base URL, send your messages to the chat completions endpoint, and set the model field to aion-labs/aion-2.0 or bytedance/ui-tars-1.5-7b. Everything else in the request body follows the OpenAI shape you already use. Switching between the two is a one line change to the model id, though you should keep in mind that parameters are not universal: sending tools to UI-TARS 7B or structured_outputs to Aion-2.0 may not behave as you expect, so adjust the body to match the model you selected. The live price table on this page shows the current rates for each.

There are cases where the pricier model is still the right choice. If your application depends on tool calling or on reading a reasoning trace, Aion-2.0 is the only one of the two that supports those parameters, and no amount of savings on UI-TARS 7B makes up for a capability it does not have. Likewise, if you need a context window slightly above 128000 tokens, Aion-2.0 gives you that headroom. Pick on capability first, then let the price difference between the two settle the cases where both models can do the job.