Model Detail
LFM2.5-24B-A2B
▲ 8.9%LFM2.5-24B-A2B is a large language model with 24B parameters released by LiquidAI. The model is registered under the text-generation pipeline tag on Hugging Face, and supports text->text inputs, distributed under a other license.
LFM2.5-24B-A2B is priced at $0.05/M input tokens and $0.7/M output tokens. Operationally the model offers a 128K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. At this input rate the model sits in the commodity tier and is suitable for high-volume workloads where per-call cost dominates the decision.
LFM2.5-24B-A2B ships with 24B parameters. Total weight footprint is approximately 24.0 GB, which is the relevant figure when planning local-inference VRAM. Distribution is governed by the other license — review the exact terms before commercial deployment.
Downloads of LFM2.5-24B-A2B have moved +8.9% over the past 24 hours. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.
LFM2.5-24B-A2B is best fit for general-purpose chat and instruction-following workloads, and high-volume batch jobs where per-call cost dominates the budget. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
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arXiv:2607.16204v1 Announce Type: new Abstract: Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixed task and reward difficulties become ineffective signals as model performance improves, and sparse rewa