Text / LiquidAI

LFM2.5 2.6B

LFM2.5-2.6B is a text-generation model from LiquidAI with 2.69B parameters, a 131,072-token context window, and a 128,000-token vocabulary. It uses a hybrid architecture with 30 layers, including 22 double-gated short convolution blocks and 8 GQA layers, and was trained on 34 trillion tokens. The model is described as general-purpose, text-only, and post-trained for agentic workloads, with multilingual coverage across 16 languages. It is distributed under the lfm1.0 license and supports safetensors and text-generation tags.

EstimatedRepository opened Jul 28, 2026Source checked 9/24/2026Version: 654f9463

LOCALRENTED GPUOPEN WEIGHTS

Freshness 74 out of 100. Repository age: 79 days old, Jul 28, 2026. Measures age, not quality.

Popularity 70 out of 100. 114,916 downloads in 30 days; 831 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

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Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

WORKFLOWS FOR THIS MODEL 1

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AI agent

LFM2.5 2.6B local agent setup

Metadata for building a local tool-using agent with LFM2.5 2.6B using Transformers or llama.cpp across Windows, Linux, and macOS.

Freshness 74 out of 100. Repository age: 79 days old, Jul 28, 2026. Measures age, not quality.

Transformersllama.cpp

3 packagesmacOS / Windows / LinuxUncensored option

Open agent guide

Open a guide for its software, hardware requirements, and setup steps.

At a glance

Parameters: 2.70B
Architecture: lfm2
Context length: 131,072
License: lfm1.0
Disk space: 5 GB
Software: Transformers

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Best for

Local text generation with a compact model footprint
Tool-use and multi-step agentic task experimentation
Instruction-following and conversational workflows
Multilingual text generation across the listed languages
Fine-tuning or inference with compatible local runtimes

Tradeoffs

Source provides limited detail beyond the model card summary.
No independent performance or compatibility validation is included.
Usefulness depends on local setup and supported runtimes.
Agentic behavior may require careful prompting and oversight.
Not positioned as a replacement for larger or more specialized models.

Ways to run it

Transformers · See official guide

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

model_id = "LiquidAI/LFM2.5-2.6B"
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map="auto",
    dtype="bfloat16",
#   attn_implementation="flash_attention_2" <- uncomment on compatible GPU
)
tokenizer = AutoTokenizer.from_pretrained(model_id)
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

prompt = "What is C. elegans?"

input_ids = tokenizer.apply_chat_template(
    [{"role": "user", "content": prompt}],
    add_generation_prompt=True,
    return_tensors="pt",
    tokenize=True,
)["input_ids"].to(model.device)

output = model.generate(
    input_ids,
    do_sample=True,
    temperature=0.1,
    top_k=50,
    repetition_penalty=1.1,
    max_new_tokens=512,
    streamer=streamer,
)

Official instructions

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Arena Open Source Text: rank 5 of 225. Ranked model: deepseek-v4.1-flash-max. Export dated Oct 13, 2026. Source checked Oct 15, 2026. Human preference ranking, not hardware suitability.+3

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