AionLabs: Aion-2.0 vs DeepSeek: R1 0528

AionLabs: Aion-2.0 is a text model from AionLabs, released on 23 February 2026. DeepSeek: R1 0528 is a text model from DeepSeek, released on 28 May 2025. Both are text in, text out, and both are served through api14 alongside each other, so the choice between them comes down to how they handle a particular workload rather than to any difference in basic modality.

The most concrete difference is context. DeepSeek R1 0528 accepts up to 163,840 tokens, while Aion-2.0 accepts up to 131,072, so the DeepSeek model is the one to reach for when a single prompt has to hold a very large codebase, a long transcript or a stack of documents. The two also differ in the tuning parameters they expose. Aion-2.0 supports include_reasoning, max_tokens, reasoning, response_format, temperature, tool_choice, tools and top_p. DeepSeek R1 0528 supports all of those plus frequency_penalty, logit_bias, logprobs, min_p, presence_penalty, repetition_penalty, seed, stop, structured_outputs, top_k and top_logprobs. In practice that means DeepSeek gives you more levers for controlling sampling and for getting structured or inspectable output, which matters if you are building evaluation harnesses or need reproducible runs via seed. Both models accept tool definitions, so neither has an edge there, and both expose reasoning controls.

For day to day work, pick based on the shape of the request. If you are feeding in long documents and want the model to reason over them in one pass, DeepSeek R1 0528's larger window is the safer fit, and its extra sampling parameters help when you need to pin down output behaviour. If your prompts fit comfortably within 131,072 tokens and you care most about output cost, Aion-2.0 is the cheaper option on the output side, which matters for long generations such as summaries, rewrites or extended reasoning traces. On input cost the picture reverses: DeepSeek is the cheaper of the two for input tokens, so workloads dominated by large prompts favour DeepSeek while workloads dominated by long responses favour Aion-2.0. The live price table on this page has the exact figures.

Calling either model through api14 works the same way. The endpoint is OpenAI compatible, so you keep your existing client library and request shape, and the only thing that changes is the model id: use "aion-labs/aion-2.0" for AionLabs and "deepseek/deepseek-r1-0528" for DeepSeek. Parameters that a given model does not list in its supported set should be left out of the request body rather than sent and ignored, so if you switch ids, trim any DeepSeek specific fields such as logit_bias or top_k when moving to Aion-2.0.

There are still cases where the other model wins. If your task is input heavy, with a large prompt and a short answer, DeepSeek R1 0528 is both the cheaper input option and the one with the larger context, so it is the better pick even if you do not need its extra parameters. Conversely, if you need the widest set of sampling and structured output controls, Aion-2.0 does not offer them, and DeepSeek is the only one of the two that does.