AionLabs: Aion-2.0 vs LiquidAI: LFM2.5-2.6B

AionLabs: Aion-2.0 is a text model from AionLabs, released on 2026-02-23. LiquidAI: LFM2.5-2.6B is a text model from LiquidAI, released on 2026-08-11. Both are served as text in, text out models, so neither one accepts images, audio or other non-text inputs, and neither returns anything but text. The choice between them therefore comes down to context size, parameter support and price rather than modality.

The two are close on context. Aion-2.0 offers 131072 tokens of context, while LFM2.5-2.6B offers 128000, which is not a meaningful difference for most workloads, and the qualitative comparison marks bigger context as a tie. Where they genuinely diverge is in the sampling and output controls they accept. LFM2.5-2.6B supports a wider set of parameters, including frequency_penalty, presence_penalty, repetition_penalty, min_p, top_k, seed, stop, logprobs and top_logprobs, and it is the only one of the two with structured_outputs support. Aion-2.0 supports a smaller set: include_reasoning, max_tokens, reasoning, response_format, temperature, tool_choice, tools and top_p. Both accept tools and tool_choice, so function calling is available on either side, and both expose reasoning controls, so that is not a differentiator either.

For practical selection, reach for Aion-2.0 when you want a straightforward chat or tool-calling loop and you do not need fine grained sampling control. Its parameter set covers the common cases: temperature, top_p, max_tokens, response_format and tools. Reach for LFM2.5-2.6B when you need deterministic or reproducible sampling (seed), when you want to penalise repetition or adjust presence and frequency penalties, when you need token level log probabilities for scoring or classification, or when you want structured outputs rather than relying on response_format alone. If your application does ranking, confidence estimation or constrained decoding, LFM2.5-2.6B is the better fit. If your application is a plain assistant with tools, either works, and the deciding factor is likely to be cost.

On cost, LFM2.5-2.6B is the cheaper option on both input and output tokens. The live price table on this page shows the exact numbers, so check it before committing, but qualitatively the LiquidAI model is the lower cost side for both directions. That makes it the default pick for high volume workloads where the extra parameters are useful anyway, and it means Aion-2.0 needs a reason to be chosen beyond price, such as a preference for its behaviour on your particular prompts.

Calling either model through api14 is the same operation. Both are exposed through the OpenAI-compatible endpoint, so you point your existing OpenAI client at the api14 base URL, supply your api14 key, and set the model field. To use Aion-2.0, set the model id to "aion-labs/aion-2.0". To use LFM2.5-2.6B, set it to "liquid/lfm-2.5-2.6b". Everything else in the request body stays the same, with one caveat: if you switch to LFM2.5-2.6B you can add the extra parameters it supports, such as seed or logprobs, and if you switch back to Aion-2.0 you should drop any parameter it does not list, since unsupported fields may be rejected. A single string change is enough to move between the two models.