LFM2.5 — lokalny model AI od Liquid AI
Autor: Jakub Rusinowski · Ostatnia aktualizacja:
Liquid AI's on-device line, built around their hybrid LIV convolution architecture rather than a stack of attention blocks. The 8B-A1B is the flagship: a sparse MoE small enough for phones, laptops and robots, reasoning-only (it emits an explicit chain of thought before answering), and trained on 38T tokens with large-scale RL. Liquid claims tool-calling quality comparable to models up to 4x its active size.
Warianty
Najmniejszy wariant LFM2.5 potrzebuje około 2 GB VRAM przy Q4_K_M — skwantyzowane wagi plus narzut frameworka, bez pamięci podręcznej KV.
| Model | VRAM przy Q4 | VRAM | Kontekst | Uruchom |
|---|---|---|---|---|
| LFM2.5 2.6B → 2.69B | ~2.4 GB | 131,072 | ollama run lfm2-5 | |
| LFM2.5-8B-A1B → 8.3B (1.5B active) | ~5.8 GB | 131,072 | ollama run lfm2.5:8b | |
| LFM2.5-24B-A2B → 24B (2.45B active) | ~15.3 GB | 131,072 | ollama run lfm2.5:24b |
Pamięć to skwantyzowane wagi plus narzut przy Q4_K_M, liczone tym samym silnikiem co sprawdzarka GPU i VRAM.
Jak uruchomić LFM2.5 lokalnie
Zainstaluj Ollama, a potem pobierz tag.
ollama run lfm2-5Wybierz rozmiar powyżej, aby zobaczyć jego VRAM, szacowaną szybkość i polecenie instalacji.
Licencja
Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.
Dotyczy: LFM2.5 2.6B, LFM2.5-8B-A1B, LFM2.5-24B-A2BPolecane GPU
Najtańsze GPU z naszego katalogu, które uruchomi LFM2.5 lokalnie (min. 2 GB VRAM), to Intel Arc B570 (10 GB).
Czy uruchomię LFM2.5 na moim GPU?
- LFM2.5 na AMD Radeon RX 9060 XT 8GB
- LFM2.5 na Intel Arc B570
- LFM2.5 na Intel Arc B580
- LFM2.5 na NVIDIA GeForce RTX 3060 (12GB)
- LFM2.5 na NVIDIA GeForce RTX 3070
- LFM2.5 na NVIDIA GeForce RTX 3070 Ti
- LFM2.5 na NVIDIA GeForce RTX 3080 (10GB)
- LFM2.5 na NVIDIA GeForce RTX 4060
- LFM2.5 na NVIDIA GeForce RTX 4070
- LFM2.5 na NVIDIA GeForce RTX 4070 Super
- LFM2.5 na NVIDIA GeForce RTX 4070 Ti
- LFM2.5 na NVIDIA GeForce RTX 5060
- LFM2.5 na NVIDIA GeForce RTX 5060 Ti 8GB
- LFM2.5 na NVIDIA GeForce RTX 5070
LFM2.5 — najczęściej zadawane pytania
How much VRAM does LFM2.5 need?
LFM2.5 needs about 2 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: LFM2.5 2.6B (2 GB, Q4_K_M); LFM2.5-8B-A1B (6 GB, Q4_K_M); LFM2.5-24B-A2B (15 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run LFM2.5 on an RTX 4090 (24 GB)?
Yes — LFM2.5 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
What quantization should I use for LFM2.5?
Q4_K_M is the best balance of quality and VRAM for LFM2.5 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run LFM2.5 with Ollama?
LFM2.5 has no local Ollama tag — the published tag is cloud-hosted, so running it sends your prompts to a hosted GPU rather than your own machine.