Measured model
Measured on a Mac Studio (M5 Max, 36GB)LFM2-24B-A2B
Liquid AI · Ollama name hf.co/LiquidAI/LFM2-24B-A2B-GGUF:Q4_K_M
On a Mac Studio (M5 Max, 36GB), LFM2-24B-A2B answers a simple question in about 0.1 s, gets 54% of the Japanese knowledge questions right, 58% of the math problems, and uses 14.8GB of memory.
These numbers are from before the method changed on Oct 2, 2026 (see how it was measured).
Results
| Measure | Result | Among measured models | Note |
|---|---|---|---|
| Reply time | about 0.1 s | 2 of 30 | Until one simple common-sense question is answered (median of 50) |
| Knowledge (high school to university) | 54% | 29 of 30 | 200 questions, ±7, 2 cut off (counted wrong) |
| Math (word problems) | 58% | 28 of 30 | 100 questions, ±10, 3 cut off (counted wrong) |
| Memory used | 14.8GB | 16 of 30 | |
| EN→JA translation | 33 pts | 10 of 28 | out of 100 (chrF), about 0.3 s a sentence |
| JA→EN translation | 56 pts | 13 of 28 | out of 100 (chrF), about 0.2 s a sentence |
"Among measured models" is the place among the 30 models measured on this site (lower is better for time and memory).
Try it on your Mac
- Install the Mac version of Ollama from ollama.com and start it.
- Type this in Terminal. The first time, the model downloads; then you can chat with it.
ollama run hf.co/LiquidAI/LFM2-24B-A2B-GGUF:Q4_K_M
It used 14.8GB here. To use it comfortably alongside other apps, a Mac with 32GB of memory or more is a good guide (the model then takes about half the memory).
About the model
- Maker
- Liquid AI
- Size
- 23.8B parameters
- Quantization
- Q4_K_M
- Thinks before answering
- Yes
- Longest input at once
- 128,000 tokens
- Released (Hugging Face)
- Feb 24, 2026
- Generation speed
- 161.2 tok/s
- Start-up (loading)
- about 0.8 s
- Measured on
- Sep 30, 2026
- Ollama
- 0.34.3
- Hugging Face
- LiquidAI/LFM2-24B-A2B
- Series
- LFM
Models of similar memory
- Devstral-Small-2-24B-Instruct-2512 (16.3GB of memory, knowledge 66%, reply about 0.2 s)
- Mistral-Small-3.1-24B-Instruct-2503 (16.3GB of memory, knowledge 72%, reply about 0.2 s)
- Mistral-Small-3.2-24B-Instruct-2506 (16.3GB of memory, knowledge 77%, reply about 0.2 s)
- gpt-oss:20b (12.8GB of memory, knowledge 81%, reply about 1.9 s)
- muse-glimmer:30b (17.6GB of memory, knowledge 85%, reply about 14.3 s)
Compare the main models on the text page. The series page lists every model measured.