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lfm2.5-1.2b-instruct
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# LFM2.5-1.2B-Instruct
LFM2.5 is a new family of hybrid models designed for **on-device deployment**. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.
- **Best-in-class performance**: A 1.2B model rivaling much larger models, bringing high-quality AI to your pocket.
- **Fast edge inference**: 239 tok/s decode on AMD CPU, 82 tok/s on mobile NPU. Runs under 1GB of memory with day-one support for llama.cpp, MLX, and vLLM.
- **Scaled training**: Extended pre-training from 10T to 28T tokens and large-scale multi-stage reinforcement learning.
Find more information about LFM2.5 in our blog post.
## 🗒️ Model Details
LFM2.5-1.2B-Instruct is a general-purpose text-only model with the following features:
...
Repository: localaiLicense: other
lfm2.5-230m
LFM2.5-230M is LiquidAI's compact text model for edge and on-device use.
It has 230M parameters, a 128K-token context window, and support for ten
languages. This entry uses the recommended Q4_K_M GGUF quantization from
LiquidAI's official repository.
Repository: localaiLicense: other
lfm2.5-230m-q8
LFM2.5-230M is LiquidAI's compact text model for edge and on-device use.
It has 230M parameters, a 128K-token context window, and support for ten
languages. This entry uses the higher-quality Q8_0 GGUF quantization from
LiquidAI's official repository.
Repository: localaiLicense: other
lfm2.5-2.6b
LFM2.5-2.6B is LiquidAI's compact, text-only reasoning model for on-device
agentic workloads. It has 2.69B parameters, a 128K-token context window,
multilingual support, and post-training for tool use, instruction following,
data extraction, RAG, and multi-step agents. This entry uses the recommended
Q4_K_M GGUF quantization from LiquidAI's official repository.
Repository: localaiLicense: other
lfm2.5-2.6b-q8
LFM2.5-2.6B is LiquidAI's compact, text-only reasoning model for on-device
agentic workloads. It has 2.69B parameters, a 128K-token context window,
multilingual support, and post-training for tool use, instruction following,
data extraction, RAG, and multi-step agents. This entry uses the higher-quality
Q8_0 GGUF quantization from LiquidAI's official repository.
Repository: localaiLicense: other
lfm2.5-2.6b-dspark
LFM2.5-2.6B with LiquidAI's DSpark speculative drafter. This build pairs
the Q4_K_M target with the compact Q4_K_M draft sidecar for lower-memory
hosts. DSpark proposes blocks of tokens that the target model verifies,
which preserves the target model's output while accelerating generation.
Repository: localaiLicense: other
lfm2.5-2.6b-q8-dspark
LFM2.5-2.6B with LiquidAI's DSpark speculative drafter. This build pairs
the higher-quality Q8_0 target with the recommended F16 draft sidecar for
the best acceptance length. DSpark proposes blocks of tokens that the
target model verifies, which preserves the target model's output while
accelerating generation.
Repository: localaiLicense: other
lfm2.5-8b-a1b
Try LFM •
Docs •
LEAP •
Discord
# LFM2.5-8B-A1B
LFM2.5 is a new family of hybrid models designed for on-device deployment. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.
- **On-device personal assistant**: Designed to power real-life applications, chaining tool calls, and following complex instructions on all devices.
- **Compressed performance**: Competitive with much larger dense and MoE models on instruction following and agentic tasks.
- **Unmatched throughput**: Fastest in its size class on both CPU and GPU inference, with day-one support for llama.cpp, MLX, vLLM, and SGLang.
Find more information about LFM2.5-8B-A1B in our blog post.
**AA-Omniscience Index (higher is better) rewards correct answers and penalizes hallucinations. Scores range from -100 to 100. See more results on Artificial Analysis.*
## 🗒️ Model Details
LFM2.5-8B-A1B is a general-purpose text-only model with the following features:
...
Repository: localaiLicense: other
lfm2.5-1.2b-nova-function-calling
The **LFM2.5-1.2B-Nova-Function-Calling-GGUF** is a quantized version of the original model, optimized for efficiency with **Unsloth**. It supports text and multimodal tasks, using different quantization levels (e.g., Q2_K, Q3_K, Q4_K, etc.) to balance performance and memory usage. The model is designed for function calling and is faster than the original version, making it suitable for tasks like code generation, reasoning, and multi-modal input processing.
Repository: localaiLicense: apache-2.0
lfm2.5-audio-1.5b-realtime
LFM2.5-Audio-1.5B is LiquidAI's any-to-any audio foundation model. The
1.2B LFM2.5 backbone plus a FastConformer audio encoder and an LFM2-based
audio detokenizer give real-time speech-to-speech with text + audio output
interleaved at 12.5 Hz / 24 kHz. This entry runs in S2S (speech-to-speech)
mode and is the model the LocalAI realtime API any-to-any path consumes.
Switch to ASR, TTS, or chat by picking the sibling gallery entries.
Repository: localaiLicense: LFM-Open-License-v1.0
lfm2.5-audio-1.5b-chat
LFM2.5-Audio-1.5B in text-only chat mode. The model runs `generate_sequential`
with no audio modality, behaving like a small LFM2 chat model. Pick this
entry for tool-calling experiments without the audio overhead.
Repository: localaiLicense: LFM-Open-License-v1.0
lfm2.5-audio-1.5b-asr
LFM2.5-Audio-1.5B in ASR mode. System prompt `Perform ASR.` is prepended;
output is capitalised and punctuated. Wire this entry as a transcription
model on the /v1/audio/transcriptions endpoint.
Repository: localaiLicense: LFM-Open-License-v1.0
lfm2.5-audio-1.5b-tts
LFM2.5-Audio-1.5B in TTS mode. Four baked voices: us_male, us_female,
uk_male, uk_female — pick the default at load time via `voice:` option,
or override per-request via the OpenAI `/v1/audio/speech` `voice` field.
Repository: localaiLicense: LFM-Open-License-v1.0
lfm2.5-vl-1.6b
LFM2.5-VL-1.6B is Liquid AI's compact vision-language model for edge deployment. It improves instruction following, multilingual vision understanding, OCR, high-resolution images, and multi-image input over LFM2-VL-1.6B. This default entry uses the official Q4_K_M GGUF with the F16 vision projector.
License: LFM Open License 1.0.
Repository: localaiLicense: lfm1.0
lfm2.5-vl-1.6b-q8
LFM2.5-VL-1.6B in the higher-fidelity Q8_0 GGUF format with the F16 vision projector.
License: LFM Open License 1.0.
Repository: localaiLicense: lfm1.0
lfm2.5-8b-a1b-apex-i-quality
Repository: localai
lfm2.5-8b-a1b-apex-i-balanced
Repository: localai
lfm2.5-8b-a1b-apex-i-compact
Repository: localai
lfm2.5-8b-a1b-apex-i-mini
Repository: localai
lfm2.5-8b-a1b-ud-q4-k-m
Repository: localai
lfm2.5-8b-a1b-ud-q5-k-m
Repository: localai
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