Overview
News
Technologies
Salaries
Products
People
Growth
Jobs
Financials
Overview
Liquid AI is an artificial intelligence company headquartered in Boston, Massachusetts, and founded in 2023 as a spin-off from the MIT Computer Science and Artificial Intelligence Laboratory. The company builds Liquid Foundation Models, an architecture derived from liquid neural networks that aims to match transformer quality at a fraction of the memory and compute. It targets on-device and edge deployment where models must run on phones, vehicles, and embedded hardware rather than in a data center.
News
Liquid AI Ships LFM2.5-VL-3B for Faster Vision-Language AI on the Edge
Liquid AI released LFM2.5-VL-3B on August 12, 2026, a 3.1-billion-parameter open-weight vision-language model built to run on phones, laptops, and single GPUs rather than in a data center. The model, announced on the com...
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LFM2.5-VL-3B: A Better and Faster Vision-Language Model for the Edge - Blog
LFM2.5-VL-3B is Liquid AI's most capable vision-language model, with grounding, screen understanding, and function calling, fast enough to run on-device.
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No cloud, no GPUs, no problem: Liquid AI's new model LFM2.5-2.6B brings powerful AI agents to devices as small as a Raspberry Pi
One test found it performed 3.7 times faster than DeepSeek-V4-Flash, the model has skyrocketed to the top of OpenRouter since its release last week.
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MacPaw Partners With Liquid AI To Bring On-Device AI To Macs
Liquid Foundation Models and MacPaw's own AI stack will create the first Mac assistant with on-device intelligence, persistent memory and native task execution.
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LFM2.5-2.6B
2.6B dense model trained for agentic workloads, with a 128K context window and native tool calling for on-device agents
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Technologies
Tech DNA
Python
C++
Rust
PyTorch
MLX ML
Megatron-LM
Cerebras
LLM
VLM
AWQ
AI/ML
Python
C++
Fine-tuning
Multimodal AI
PyTorch
Post-training
SFT
Computer Vision
Edge AI
Reinforcement Learning
Synthetic Data
LLM
llama.cpp
Quantization
DeepSpeed
FSDP
vLLM
MLX ML
ONNX
VLM
Megatron-LM
Function Calling
Knowledge Distillation
Hadoop
Ray
AWQ
GGUF
Jupyter Notebook
TensorRT
TensorRT-LLM
JAX
TensorFlow
CUDA Toolkit
SGLang
Mixture of Experts
CUDA
Triton
Pre-training
cuDNN
LLM Guardrails
Recommender Systems
Hugging Face
OCR
Text-to-Speech
NCCL
Speech Recognition
AI Agents
Kubernetes
SLURM
HPC
GitHub
PyTorch C++
Cerebras
Groq
TPU
Other
Rust
A/B Testing
Stack modernity
77/100
How modern this stack is, based on technology relevance, AI adoption and the share of legacy tools.
In-demand technologies
Fine-tuning
8 jobs
Required
Multimodal AI
8 jobs
Required
Post-training
6 jobs
Required
PyTorch
6 jobs
Required
SFT
5 jobs
Required
Python
5 jobs
Required
Computer Vision
4 jobs
Required
Edge AI
4 jobs
Required
Salary medians are calculated from this company's open jobs and compared with the market.
Industry adoption
Python
19%
Kubernetes
13%
LLM
12%
AI Agents
11%
C++
7%
PyTorch
7%
Share of companies in the same industry that use each technology.
Stack changes
AI Agents
Aug 2026
Speech Recognition
Aug 2026
Function Calling
Aug 2026
NCCL
Aug 2026
Text-to-Speech
Aug 2026
OCR
Aug 2026
Megatron-LM
Aug 2026
Hugging Face
Aug 2026
Technologies recently added to or removed from this company's stack - a signal of tech migrations and new initiatives.
NVIDIA
Adobe
Jobgether
Cohere
Weekday
Qualcomm
Growth
Hiring Momentum
51/100
Stable
Open positions
16
0 opened / 4 closed in 30 days
Median time-to-fill
215 days
faster than 6% of the market
ATS activity
Every ~1 days
08/31/2026
Hiring Dynamics
+100%
Hiring Focus
The percentage next to each role is its share of the company's job openings over the last 90 days; the arrow shows the shift versus the previous period.
AI/ML
86% ▲
Product
14% ▼
Activity Timeline
Added AI Agents to stack
Aug 2026
Added Speech Recognition to stack
Aug 2026
Added Function Calling to stack
Aug 2026
Added NCCL to stack
Aug 2026
Added Text-to-Speech to stack
Aug 2026
Added OCR to stack
Aug 2026
Added Megatron-LM to stack
Aug 2026
Added Hugging Face to stack
Aug 2026
Added GitHub to stack
Aug 2026
Added FSDP to stack
Aug 2026
Added TPU to stack
Aug 2026
Added Recommender Systems to stack
Aug 2026
Jobs
≈ $194k – $394k per year (Estimated) • Remote/Hybrid • Full-Time • Master's Degree • San Francisco
Python
Computer Vision
DeepSpeed
Multimodal AI
Reinforcement Learning
VLM
FSDP
Hugging Face
Megatron-LM
Post-training
SFT
DevOps
GitHub
Apply
≈ $156k – $316k per year (Estimated) • Remote/Hybrid • Full-Time • Boston
C++
Python
llama.cpp
MLX ML
ONNX
Quantization
Edge AI
Apply
≈ $67k – $146k per year (Estimated) • Remote/Hybrid • Full-Time • Tokyo
Fine-tuning
Knowledge Distillation
Multimodal AI
Reinforcement Learning
Synthetic Data
Post-training
SFT
Apply
≈ $66k – $144k per year (Estimated) • Remote/Hybrid • Full-Time • Tokyo
Fine-tuning
llama.cpp
LLM
MLX ML
Multimodal AI
ONNX
Quantization
SGLang
vLLM
Post-training
SFT
Apply
≈ $174k – $324k per year (Estimated) • Remote • Internship • 2+ years exp • Bachelor's Degree
Computer Vision
Fine-tuning
Edge AI
Function Calling
Apply
≈ $180k – $364k per year (Estimated) • Remote/Hybrid • Full-Time • San Francisco
Hadoop
Ray
DevOps
Kubernetes
SLURM
HPC
Apply
≈ $191k – $386k per year (Estimated) • Remote/Hybrid • Full-Time • 2+ years exp • San Francisco
Computer Vision
Fine-tuning
Edge AI
Function Calling
Apply
≈ $153k – $306k per year (Estimated) • Remote/Hybrid • Full-Time • San Francisco
Fine-tuning
LLM
AI Agents
Edge AI
Apply
≈ $183k – $335k per year (Estimated) • Remote/Hybrid • Full-Time • San Francisco • Boston
AWQ
Fine-tuning
GGUF
Jupyter Notebook
llama.cpp
LLM
Quantization
TensorRT
TensorRT-LLM
vLLM
Apply
≈ $197k – $400k per year (Estimated) • Remote/Hybrid • Full-Time • San Francisco • Boston
Fine-tuning
Multimodal AI
Reinforcement Learning
Synthetic Data
VLM
OCR
Post-training
SFT
Apply
≈ $158k – $320k per year (Estimated) • Remote/Hybrid • Full-Time • Boston
Python
Fine-tuning
PyTorch
Recommender Systems
Analytics
A/B Testing
Apply
≈ $199k – $404k per year (Estimated) • Remote/Hybrid • Full-Time • San Francisco • Boston
DeepSpeed
Multimodal AI
PyTorch
FSDP
Text-to-Speech
Speech Recognition
Apply
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