liodon-ai/LocateAnything-3B-imatrix-GGUF overview
LocateAnything 3B — iMatrix GGUF iMatrix GGUF quantizations of nvidia/LocateAnything 3B https://huggingface.co/nvidia/LocateAnything 3B — the first GGUF availa…
Runs locally from ~1.19 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| LocateAnything-3B-IQ2_M.gguf | GGUF | IQ2_M | 1.19 GB | Download |
| LocateAnything-3B-IQ3_M.gguf | GGUF | IQ3_M | 1.51 GB | Download |
| LocateAnything-3B-IQ4_XS.gguf | GGUF | IQ4_XS | 1.78 GB | Download |
| LocateAnything-3B-Q2_K.gguf | GGUF | Q2_K | 1.28 GB | Download |
| LocateAnything-3B-Q3_K_M.gguf | GGUF | Q3_K_M | 1.61 GB | Download |
| LocateAnything-3B-Q4_K_M.gguf | GGUF | Q4_K_M | 1.96 GB | Download |
| LocateAnything-3B-Q5_K_M.gguf | GGUF | Q5_K_M | 2.27 GB | Download |
| LocateAnything-3B-Q6_K.gguf | GGUF | Q6_K | 2.60 GB | Download |
| LocateAnything-3B-Q8_0.gguf | GGUF | Q8_0 | 3.37 GB | Download |
Model Details
| Model ID | liodon-ai/LocateAnything-3B-imatrix-GGUF |
|---|---|
| Author | liodon-ai |
| Pipeline | text-generation |
| License | other |
| Base model | nvidia/LocateAnything-3B |
| Last modified | 2026-07-13T04:54:31.000Z |
Model README
---
license: other
license_name: nvidia-open-model-license
base_model: nvidia/LocateAnything-3B
base_model_relation: quantized
pipeline_tag: text-generation
library_name: gguf
tags:
- gguf
- ollama
- imatrix
- nvidia
- locate-anything
- vision-language
- grounding
- local-llm
- llama.cpp
- lm-studio
- quantized
quantized_by: liodon-ai
---
LocateAnything-3B — iMatrix GGUF
iMatrix GGUF quantizations of nvidia/LocateAnything-3B — the first GGUF available for this model.
LocateAnything-3B is NVIDIA's 3B visual grounding model — it locates and identifies objects in images given natural language descriptions. Designed for on-device deployment and robotics applications.
These GGUFs use importance matrix (iMatrix) calibration on 2M tokens of wikitext-103: iMatrix runs calibration text through the model, measures which weights activate most, and protects them during quantization. Result: noticeably better coherence at Q2/Q3/Q4 — same file size, better output.
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Quick Start
llama.cpp
llama-cli -hf liodon-ai/LocateAnything-3B-imatrix-GGUF:Q4_K_MLM Studio / Jan
Search liodon-ai/LocateAnything-3B-imatrix-GGUF and pick your quant.
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Available Quants
| Quant | Size | VRAM | Notes |
|-------|------|------|-------|
| IQ2_M | 1.28 GB | 2 GB | ultra-tiny + iMatrix — better than standard Q2 |
| IQ3_M | 1.62 GB | 2.5 GB | tiny + iMatrix — sharper than standard Q3 |
| IQ4_XS | 1.91 GB | 3 GB | small + iMatrix — rivals Q5 at Q4 size |
| Q2_K | 1.38 GB | 2 GB | tiniest standard — runs almost anywhere, iMatrix-improved |
| Q3_K_M | 1.73 GB | 2.5 GB | great for 4GB VRAM, iMatrix-improved |
| Q4_K_M | 2.11 GB | 3 GB | sweet spot (recommended), iMatrix-improved |
| Q5_K_M | 2.44 GB | 4 GB | high quality, iMatrix-improved |
| Q6_K | 2.80 GB | 4 GB | near-lossless, iMatrix-improved |
| Q8_0 | 3.62 GB | 5 GB | basically full quality |
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What is iMatrix?
Standard quantization rounds all weights equally. iMatrix:
- Runs calibration text through the full-precision model
- Measures which weights activate most (the "importance matrix")
- Allocates more precision to important weights, less to unimportant ones
Same file size. Better output. Most noticeable at Q2/Q3/Q4.
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Calibration
Importance matrix computed from 2M tokens of wikitext-103 — 128 calibration chunks.
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Source Model
- Original: nvidia/LocateAnything-3B
- Architecture: 3B visual grounding model
- Strengths: Object localization, visual grounding, on-device robotics
- License: NVIDIA Open Model License
Run liodon-ai/LocateAnything-3B-imatrix-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models