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LFM3-VL-2B

Liquid AIOpen WeightLFM Open License v1.0 · Usage Commercial

Description

LFM3-VL-2B is Liquid AI's open-weight 1.92B vision-language model (1.73B LFM3 language model + new 164M in-house conv/attention vision encoder + 25M projector), released Oct 27, 2026 as part of the LFM3 family. Inputs: text, images, and video (first LFM vision model with video, sampled at 2 fps) at native resolution; text output. Reasons step by step before answering (thinking), with spatial/embodied reasoning and grounding aimed at robotics, plus document/OCR/chart and GUI understanding. 128K context; 16 languages. Vendor reports a 71.4 average across 62 vision benchmarks (vs 57.6 for LFM2.5-VL-3B). Not recommended for coding, multi-turn conversations, or complex reasoning per the model card. Hugging Face: LiquidAI/LFM3-VL-2B (+ GGUF, MLX, ONNX). License: LFM Open License v1.0. Catalog benches are the thinking-mode column from the model card table. No catalog id (recorded here only): SEED-Bench image 78.6, MM-Vet v1 57.4, PerceptionBench 37.1 (catalog id is Moonshot's internal benchmark), HR-Bench 8K 76.2, ZoomBench 62.6, V*Bench 86.4, CV-Bench 88.8, LogicVista 60.4, RefCOCO-M 95.2, Point-Bench 73.8, MindCube tiny 56.5, SAT 80.2, Where2Place 44.9, OpenEQA 76.3, VSI-Bench 63.1, ScreenSpot-v2 desktop/mobile/web 94.6/92.2/89.9, MMMB 85.2, Multilingual MMBench 83.6, MM-ToolSandbox 42.5. No gateway id or price at time of adding, so no provider row. Sources: https://huggingface.co/LiquidAI/LFM3-VL-2B · https://www.liquid.ai/blog/lfm3.

Date de sortie
2026-10-27
Paramètres
1.9B
Longueur du contexte
—
Modalités
—

Radar de capacités

70
general
0
coding
70
reasoning
43
scienceest.
49
agents
70
multimodal

Science est estimé à partir des scores scientifiques de LLM Stats ou du raisonnement lorsque les benchmarks scientifiques dédiés ne sont pas disponibles.

Classements

Domaine#RangScoreSource
Classement multimodal129
27.0
LS

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

General

MLVU-M71.3%Aut.

Math

MathVista-Mini84.2%Aut.
DynaMath79.2%Aut.
We-Math68.6%Aut.
MathVision51.6%Aut.

Multimodal

MM IF-Eval72.8%Aut.
VideoMME w/o sub.62.8%Aut.
VideoMMMU49.6%Aut.

Reasoning

ChartQAMasry et al. (2022)92.7%Aut.
CharXiv-D87.5%Aut.
CharXiv-R70.2%Aut.

Vision

DocVQADocVQA (2020)96.7%Aut.
CountBench0.93 / 100Aut.
RefCOCO-avg0.91 / 100Aut.
POPE88.7%Aut.
TextVQA87.9%Aut.
MME86.9%Aut.
OCRBench86.3%Aut.
InfoVQA86.2%Aut.
MMBench-V1.186.1%Aut.
EmbSpatialBench0.83 / 100Aut.
HR-Bench (4k)82.3%Aut.
RealWorldQA79.3%Aut.
MMStar74.4%Aut.
ActivityNet71.2%Aut.
BLINK71.1%Aut.
MVBench69.4%Aut.
VideoMME w sub.69.0%Aut.
MuirBench66.4%Aut.
Hallusion Bench65.6%Aut.
MotionBench64.0%Aut.
OCRBench-V2 (en)63.5%Aut.
RoboSpatialHome0.63 / 100Aut.
MMMU (val)55.7%Aut.
ScreenSpot Pro55.5%Aut.
MMVU52.9%Aut.
RefSpatialBench0.50 / 100Aut.
ERQA48.2%Aut.
MMMU-Pro45.7%Aut.
LVBench41.2%Aut.
SimpleVQA0.36 / 100Aut.

Indices d'évaluation AA

(Artificial Analysis)

Aucune donnée d'évaluation AA disponible

Scores par catégorie LLM Stats

(LLM Stats (zeroeval))
Safety
90
Structured Output
80
Embodied
80
Image To Text
70
Math
70
Multimodal
70
Reasoning
70
Spatial Reasoning
70
General
70
Grounding
70
3d
70
Vision
70
Video
60
Healthcare
50
Long Context
40

Tarification

Aucune donnée de prix disponible

Vitesse

Aucune donnée de vitesse disponible

Classement des Prix par Fournisseur

Aucune donnée de fournisseur disponible

Sources externes