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
Post-training
PyTorch
SFT
LLM
Computer Vision
Reinforcement Learning
Edge AI
Synthetic Data
llama.cpp
Quantization
vLLM
DeepSpeed
FSDP
Function Calling
TensorRT
MLX ML
ONNX
SGLang
VLM
Hugging Face
Megatron-LM
Text-to-Speech
Speech Recognition
Knowledge Distillation
Hadoop
Ray
AWQ
GGUF
Jupyter Notebook
TensorRT-LLM
JAX
TensorFlow
CUDA Toolkit
Mixture of Experts
CUDA
Triton
Pre-training
cuDNN
LLM Guardrails
Recommender Systems
OCR
NCCL
AI Agents
Structured Outputs
DPO
RLHF
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
10 jobs
Required
Multimodal AI
9 jobs
Required
Post-training
8 jobs
Required
SFT
7 jobs
Required
PyTorch
7 jobs
Required
LLM
5 jobs
Required
Python
5 jobs
Required
Computer Vision
4 jobs
Required
Salary medians are calculated from this company's open jobs and compared with the market.
Industry adoption
Python
19%
AI Agents
13%
Kubernetes
13%
LLM
12%
GitHub
9%
C++
7%
Share of companies in the same industry that use each technology.
Stack changes
RLHF
Aug 2026
DPO
Aug 2026
Structured Outputs
Aug 2026
AI Agents
Aug 2026
Speech Recognition
Aug 2026
Function Calling
Aug 2026
NCCL
Aug 2026
Text-to-Speech
Aug 2026
Technologies recently added to or removed from this company's stack - a signal of tech migrations and new initiatives.
NVIDIA
Adobe
Sarvam AI
Jobgether
Cohere
Weekday
Growth
Hiring Momentum
51/100
Stable
Open positions
18
0 opened / 4 closed in 30 days
Median time-to-fill
215 days
faster than 6% of the market
ATS activity
Every ~17 hours
09/02/2026
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
Member of Technical Staff - ML Scientist, Japanese Multimodal
Verified live · 1 day ago 2 months ago≈ $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
Member of Technical Staff - Embedded ML Engineer (Audio/Omni)
Verified live · 1 day ago 2 months ago≈ $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
≈ $192k – $389k per year (Estimated) • Remote/Hybrid • Full-Time • San Francisco • Boston
Fine-tuning
Function Calling
LLM
Multimodal AI
Post-training
Reinforcement Learning
SFT
Speech Recognition
Structured Outputs
Text-to-Speech
Apply
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