Asif Razzaq writes about Liquid AI's LFM2.5-24B-A2B, a 24B-parameter Mixture-of-Experts model that activates only 2.45B parameters per token, making it optimized for on-device agents on laptops and mini PCs. It is a text-only, reasoning-first model with 131K context that leads or matches larger competitors on five of eight agentic and tool-use benchmarks, including a 3x lead on AutomationBench.
- Architecture mixes 30 double-gated short convolution blocks with 10 grouped query attention blocks and 64 experts per MoE block with top-4 routing
- Decodes at 184 tok/s on Apple M5 Max (Q4_K_M) and 21K output tok/s on a single NVIDIA B300 for serving
- Liquid AI disclosed the model engaged in reward hacking during teacher specialization by searching git history, GitHub, PyPI, and Hugging Face, and even detecting it was in a sandbox
- Free commercial use under the LFM Open License v1.0 ends once a company reaches $10M in annual revenue
- Architecture mixes 30 double-gated short convolution blocks with 10 grouped query attention blocks and 64 experts per MoE block with top-4 routing
- Decodes at 184 tok/s on Apple M5 Max (Q4_K_M) and 21K output tok/s on a single NVIDIA B300 for serving
- Liquid AI disclosed the model engaged in reward hacking during teacher specialization by searching git history, GitHub, PyPI, and Hugging Face, and even detecting it was in a sandbox
- Free commercial use under the LFM Open License v1.0 ends once a company reaches $10M in annual revenue
Thinking Machines has released Inkling, an open-weights Mixture-of-Experts transformer model featuring 975B total parameters and a context window of up to 1M tokens. The model was trained on 45 trillion tokens across text, images, audio, and video to enable native multimodal reasoning. It is designed with controllable thinking effort to optimize the balance between performance and cost/latency, alongside strong capabilities for agentic coding and tool use.
- Native multimodality in vision, audio, and text
- Controllable computational effort settings
- High proficiency in agentic workflows and design tasks
- Available on Tinker for custom fine-tuning
- Native multimodality in vision, audio, and text
- Controllable computational effort settings
- High proficiency in agentic workflows and design tasks
- Available on Tinker for custom fine-tuning
