Updated 4 h ago · first seen 11 Sept 2026
model_01M294WVRY9NNJ1G9WZX2WNC60
Overview
Identity
- Canonical model
- Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- 1 quantization0 official · 1 third-partySeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 1
- API aliases
- lfm2-5-2-6bliquid/lfm-2.5-2.6bIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Restricted weights— weights downloadable under LFM-Open-1.0; commercial use allowed; redistribution allowed; derivatives allowed; 4 dimensions unknown.
Weights downloadable, but the licence restricts commercial use, hosting, derivatives or field of use (community, research and RAIL licences).
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
Yes
Redistribution
Yes
Derivatives
Yes
Licence: LFM Open License v1.0 (Liquid AI) (community)
dimensions marked null are unknown, not false
Key facts
- Release date
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 5 d agomedium
Architecture
- Architecture
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Model type
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Pipeline tag
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 5 d agomedium
Capabilities
Modalities
- Modalities
- text
- Input
- text
- Output
- text
Capabilities
Tool calling
Unavailable
Structured output
Unavailable
Reasoning
Yes
Artificial Analysis · T2
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:Artificial AnalysisT2observed 5 d agomedium
- Languages
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
Benchmarks10
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 10 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →
Providers & Pricing1
All offers in the price terminal →USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →
Price history
Output price · USD / 1M tokens 1 provider
- OpenRouter
- OpenRouterfirst observed $011 Sept 2026
Input price · USD / 1M tokens 1 provider
- OpenRouter
- OpenRouterfirst observed $011 Sept 2026
Hardware fit37
Assumptions (7)
- Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
- bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
- KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), independent of architecture (GQA/MLA models need less).
- A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
- Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
- Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
- Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.
Lineage
Open in Graph →- ancestor: LFM2.5-2.6B-Base
Versions & Artifacts1
Version history
License1 change
11 Sept 2026→12 Sept 2026current
Openness1 change
11 Sept 2026→12 Sept 2026current
Context windowfirst observation only
11 Sept 2026current
Parametersfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 1
quantization 1
- LiquidAI/LFM2.5-2.6B-GGUFLiquid AI · GGUF—
Papers1
- arXiv:2511.23404Active35
Timeline7
Full timeline →LFM2.5-2.6B (free): openness changed from open-weights to restricted-weights
Opennessopen-weights→restricted-weightshuggingfaceLFM2.5-2.6B (free): license changed from Other to LFM-Open-1.0
LicenseOther→LFM-Open-1.0huggingfaceLFM2.5-2.6B (free) scores 4.49% on Terminal-Bench
artificial_analysisLFM2.5-2.6B (free) scores 14.35% on SciCode
artificial_analysisLFM2.5-2.6B (free) scores 6.21% on Humanity's Last Exam
artificial_analysisLFM2.5-2.6B (free) scores 55.76% on GPQA Diamond
artificial_analysisLFM2.5-2.6B (free) scores 8.39 on Artificial Analysis Intelligence Index
artificial_analysis
Change history61
Viewing AI Atlas as of 16 Aug 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →LFM2.5-2.6B (free) was not yet in AI Atlas on 16 Aug 2026
Release daterelease_date1
Opennessopenness2
Licenselicense2
Architecturearchitecture1
Parametersparameter_count1
Context windowcontext_length1
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
Languageslanguages1
Base modelbase_model1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads6
Likesmetric.likes10
Aa context windowaa_context_window1
Aa opennessaa_openness1
Accessaccess1
Commercial use allowedcommercial_use_allowed1
Derivatives allowedderivatives_allowed1
Gatedgated1
Last modifiedlast_modified1
Library namelibrary_name1
License keylicense_key1
License namelicense_name1
License rawlicense_raw1
License urllicense_url1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second3
Downloads all timemetric.downloads_all_time6
Model typemodel_type1
Openrouter idopenrouter_id1
Reasoningreasoning1
Redistribution allowedredistribution_allowed1
Weights availableweights_available1
Weights dtypeweights_dtype1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
39
Source tiers
T239
Freshest observation
5 h ago
Conflicts
None
Source documents 6
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (69/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →