Liquid Ai
PulseAugur coverage of Liquid Ai — every cluster mentioning Liquid Ai across labs, papers, and developer communities, ranked by signal.
- developed LFM2.5-2.6B 95%
- instance of LFM2.5-2.6B 95%
- instance of LFM2.5-VL-3B 95%
- developed LFM2.5-VL-3B 95%
- developed LFM2.5-230M 95%
- instance of LFM2.5-230M 95%
- instance of LFM2.5-8B-A1B 95%
- developed LFM2.5-8B-A1B 95%
- developed LFM2.5 95%
- instance of LiquidAI 90%
- used by LFM2.5-2.6B 70%
- used by LFM2.5 70%
- 2026-08-22 product_launch Liquid AI is reportedly developing a new 100 billion parameter model. source
- 2026-08-20 product_launch Liquid AI released DSpark draft models for its LFM2.5 family, offering up to 3.18x faster decoding speeds. source
- 2026-08-20 product_launch Liquid AI released DSpark draft models for its LFM2.5 series, enhancing decoding speed. source
- 2026-07-29 product_launch Liquid AI released LFM2.5-Encoders, a model for fast long-text analysis on CPUs. source
- 2026-07-29 product_launch Liquid AI released two new open-weight bidirectional encoder models, LFM2.5-Encoder-230M and LFM2.5-Encoder-350M. source
- 2026-06-19 product_launch Liquid AI released two new retrieval models, LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M, designed for efficient multilingual search on edge devices. source
- 2026-06-19 product_launch Liquid AI released two new retrieval models for multilingual search. source
- 2026-05-29 product_launch Liquid AI released its LFM2.5-8B-A1B model, featuring an expanded context window and increased training data. source
- 2026-05-26 product_launch Liquid AI launched two new Japanese-capable AI models, LFM2.5-1.2B-JP-202606 and LFM2.5-Audio-1.5B-JP. source
3 day(s) with sentiment data
Liquid AI's LFM2.5-2.6B model to see widespread adoption in on-device agent applications within 6 months
The release of LFM2.5-2.6B, with its strong emphasis on agentic capabilities, compact size, and ability to run on-device with a large context window, positions it well for use in applications requiring local AI processing. The partnership with MacPaw for macOS integration further suggests a strategic push towards broader adoption in consumer devices. We expect to see this model integrated into various agentic applications targeting mobile and desktop within the next six months.
Liquid AI to release a fine-tuned version of LFM2.5-2.6B optimized for coding tasks within 3 months
While current reports indicate LFM2.5-2.6B is not recommended for complex coding, its compact size and agentic focus make it a strong candidate for specialized fine-tuning. Given the general demand for capable coding assistants, Liquid AI may prioritize developing a version of this model specifically for code generation or assistance, leveraging its efficient architecture. We hypothesize such a release within the next three months.
Liquid AI's LFM2.5-2.6B model demonstrates strong performance in tool-use and instruction-following benchmarks
Multiple releases highlight that Liquid AI's LFM2.5-2.6B model, despite its small parameter count (2.69B), shows competitive performance against much larger models in specific benchmarks, particularly instruction-following and tool-use. This suggests that Liquid AI is effectively optimizing for agentic workflows and efficient execution on resource-constrained devices.
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Arm Holdings launches Total Design for Physical AI and robotics framework
Arm Holdings has launched Arm Total Design for Physical AI, a new initiative aimed at standardizing development for physical industries like robotics, agriculture, and transport. This program brings together over 80 par…
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Time magazine's AI 100 list spotlights key figures in AI development
Time magazine has released its "AI 100" list, highlighting individuals influential in the AI revolution. The list features prominent figures such as Daniela Rus of MIT CSAIL for her work on Liquid AI, a project focused …
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AI research advances inference, optimization, and mobile benchmarking
Researchers are exploring advanced techniques for improving AI inference and statistical analysis, particularly in resource-constrained environments. One paper introduces IMABO, a framework for Online Hyperparameter Opt…
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Fish Audio achieves $21M revenue; Liquid AI releases new benchmark tool
Fish Audio, initially a GitHub hobby project, has rapidly grown into a profitable venture, generating $21 million in annual revenue within a year. Meanwhile, Liquid AI has released an open-source tool called Pipette. Th…
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Liquid AI open-sources Pipette for on-device AI model benchmarking
Liquid AI has open-sourced Pipette, a new benchmarking suite designed to evaluate the performance of on-device AI models. Developed in partnership with Artificial Analysis, Pipette measures models by considering the ent…
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Liquid AI reportedly developing new 100B parameter model
Liquid AI is reportedly developing a new 100 billion parameter model, building on its existing fast LLM and SLM architectures. The company is known for its efficient model designs, and the upcoming larger model is antic…
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Liquid AI boosts LFM2.5 model speed up to 3.18x with DSpark speculative decoding
Liquid AI has released DSpark draft models for its LFM2.5 series, which enhance decoding speed by up to 3.18x without altering output quality. These models utilize speculative decoding, where a smaller draft model propo…
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Liquid AI releases QAD versions of LFM2.5 models for efficient edge deployment
Liquid AI has released a Quantization-Aware Distillation (QAD) version of its LFM2.5 series of small AI models. This new version is designed to reduce memory usage while minimizing performance degradation, making the mo…
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Liquid AI releases QAD checkpoints for LFM2.5 models, boosting edge performance
Liquid AI has released new checkpoints for its LFM2.5 models, utilizing Quantization-Aware Distillation (QAD) to improve performance. These QAD Q4_0 checkpoints maintain the low memory footprint and high throughput of s…
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Muse Glimmer 30B and LFM2.5-VL-3B enhance local AI capabilities
This week's AI digest highlights advancements in local AI usage, featuring the release of Muse Glimmer 30B, a model optimized for local agents and supported by llama.cpp. Also notable is the small VLM, LFM2.5-VL-3B, cap…
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Liquid AI unveils compact LFM2.5-VL-3B vision model for local processing
Liquid AI has released a compact vision model, LFM2.5-VL-3B, featuring 3.1 billion parameters. This model achieves a processing speed of 228 tokens per second on Apple M5 Max processors. The development signifies a brea…
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Liquid AI releases LFM2.5-VL-3B, a smartphone-compatible vision-language model
Liquid AI has released LFM2.5-VL-3B, a lightweight vision-language model designed to run on smartphones. This open model, with 3.1 billion parameters and under 3.3GB of memory usage, supports OCR, UI recognition, and mu…
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New vision model LFM2.5-VL-3B runs on iPhone, identifies Minecraft character
Liquid AI has released LFM2.5-VL-3B, a 3.1 billion parameter vision model that can run on mobile devices. In a demonstration, the model successfully identified a toy Steve from Minecraft and provided a detailed descript…
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Liquid AI releases 3B vision-language model for on-device use
Liquid AI has launched LFM2.5-VL-3B, a 3.1 billion parameter vision-language model designed for on-device applications. This model excels at reading digital screens, identifying objects with coordinates, and processing …
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Liquid AI releases cookbook with tutorials for LFM and LEAP SDK
Liquid AI has released a new GitHub repository named "cookbook." This repository contains examples, end-to-end tutorials, and applications built using their Liquid AI Foundational Models (LFM) and the LEAP SDK. The proj…
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Liquid AI releases compact agent model; Mistral launches safety classifier
Liquid AI has released LFM2.5-2.6B, a compact text-only model optimized for agent harnesses and tool interaction, featuring a large context window and multilingual support. While not recommended for complex coding, its …
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MacPaw and Liquid AI partner for on-device AI on Macs
MacPaw and Liquid AI have formed a partnership to develop on-device AI capabilities for macOS. This collaboration will integrate Liquid AI's foundation models with MacPaw's Elix and Mnemos technologies to create a local…
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Liquid AI releases on-device agentic model LFM2.5-2.6B with 128K context
Liquid AI has released LFM2.5-2.6B, an open-weights, on-device agentic model designed for mobile and edge devices. This model boasts 2.69 billion parameters, a 128,000-token context window, and can perform multi-step ta…
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Liquid AI releases 2.6B model capable of 128K context on phones
Liquid AI has released LFM2.5-2.6B, a compact language model designed for local AI applications. Despite its small size of 2.69 billion parameters, the model boasts a 128K context window and supports tool calling, makin…
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Liquid AI releases LFM2.5-2.6B model with agentic focus
Liquid AI has released LFM2.5-2.6B, a new small-scale language model. The release emphasizes enhanced agentic capabilities, aiming to excel at high-volume tasks such as document summarization. The developers are particu…