]633;E;echo "=== 3. hparams as seen by the C++ loader"\x3b timeout 60 ./build-vis/diff_tokenizer /tmp/hf_verify/sam3-q4_0.gguf /tmp/tok_diff 2>&1 | grep -E "mem_selection|max_cond|max_obj" ;a7ba6c53-87c6-427f-92bf-6a5106a2fee1]633;C# github: https://github.com/Asher-1/sam3-ggml

Model Zoo — models/

This directory holds ready-to-run GGUF models for sam3.cpp.

Each file name encodes three things:

<family>_<backbone/size>_<precision>.gguf

| Part | Meaning |

|------|---------|

| sam3 / sam3-visual | SAM 3 — ViT-32 backbone + text encoder + DETR detector (850M params) |

| sam2 / sam2.1 | SAM 2 / SAM 2.1 — Meta's Hiera-backbone segmentation models (visual only) |

| tiny / small / base_plus / large | Backbone size (39M / 46M / 81M / 224M params) |

| f32 / f16 / q8_0 / q4_1 / q4_0 | Weight precision (see Precision guide) |

> Architecture lineage: this directory covers 2 architectures —

> SAM 3 (sam3-, sam3-visual-) and the SAM 2 family

> (sam2, sam2.1). There are no SAM 1 checkpoints (SAM 1 / ViT-B/L/H is a separate

> architecture not shipped by this project). The SAM 2 family is visual-only

> (points/box + tracking); SAM 3 full adds text-prompted detection (PCS):

> type "cat" and get every cat in the image.

Download

All checkpoints listed in this README are published as ready-to-run GGUF

files on Hugging Face — no PyTorch weights or conversion step needed:

> https://huggingface.co/Asher-1/sam3-gguf

> Tracker/tokenizer alignment patch (2026-09, updated on HF): the sam3-*

> checkpoints (f32/f16/q8_0/q4_1/q4_0) on the HF repo now carry the repaired

> BPE merge table (all 48894 official rows — the old converter silently

> dropped the 6 #-first merges) and the SAM3 tracker-alignment hparams

> (max_cond_frames_in_attn / use_memory_selection / mf_threshold_x100).

> Locally cached copies downloaded before 2026-09-13 can be repaired in place

> with the idempotent scripts/fix_gguf_merges.py (a dry-run prints "already

> patched; nothing to do" when current). sam2 / sam3-visual- files are

> unaffected (no tokenizer / SAM2-compatible defaults).

The repo mirrors this directory 1:1 (40 files, ~14 GB total).

# All 40 models into models/
huggingface-cli download Asher-1/sam3-gguf --local-dir models

# Or just one file
huggingface-cli download Asher-1/sam3-gguf sam3-f16.gguf --local-dir models

# Or plain curl (single-file direct URL)
curl -L -o models/sam3-f16.gguf \
  https://huggingface.co/Asher-1/sam3-gguf/resolve/main/sam3-f16.gguf

(huggingface-cli comes from pip install huggingface_hub.)

Quick pick

| You want… | Pick |

|-----------|------|

| Text-prompted detection ("type cat, get every cat") | sam3-f16.gguf (1.8 GB) or sam3-q8_0.gguf (1.1 GB) |

| Best visual quality-to-speed balance on GPU | sam2.1_hiera_base_plus_f16.gguf (156 MB) |

| Fastest interactive point/box segmentation on any device | sam2.1_hiera_tiny_q4_0.gguf (23 MB) |

| Best segmentation quality | sam2.1_hiera_large_f16.gguf (431 MB) or _q8_0 (231 MB) |

| Debugging / numerical reference (never for deployment) | sam2.1_hiera_tiny_f32.gguf |

Model files

Sizes below are the actual .gguf files in this directory. Latency is a

single-image PVS run (encode + segment) at 1008×1008 on RTX 3060 CUDA,

point (315,250) on tests/cat.jpg. The current SAM 3 F16 result uses

sam3_encode_image_pvs(), 2 warmups and 7 timed runs (p50); the remaining

rows are the earlier all-model snapshot. score = mask IoU confidence.

SAM 3 (850M params — ViT-32 backbone + text encoder + DETR decoder)

| File | Size | Load | Encode | Segment | Total | score |

|------|------|-----:|-------:|--------:|------:|------:|

| sam3-f32.gguf | 3.3 GB | 3.3 s | 4.2 s | 0.21 s | 7.7 s | 0.953 |

| sam3-f16.gguf | 1.8 GB | 0.81 s | 0.566 s | 0.032 s | 1.41 s | 0.953 |

| sam3-q8_0.gguf | 1.1 GB | 1.4 s | 3.5 s | 0.20 s | 5.1 s | 0.953 |

| sam3-q4_1.gguf | 730 MB | 1.1 s | 3.6 s | 0.21 s | 4.9 s | 0.937 |

| sam3-q4_0.gguf | 707 MB | 1.5 s | 3.6 s | 0.25 s | 5.3 s | 0.915 |

Best for: text-prompted detection (PCS) + point/box segmentation (PVS) +

video tracking in one model. The full SAM 3 is the only family here that

supports text prompts; the visual path matches sam3-visual exactly.

SAM 3 Visual (no text encoder — PVS + tracking only)

| File | Size | Load | Encode | Segment | Total | score |

|------|------|-----:|-------:|--------:|------:|------:|

| sam3-visual-f16.gguf | 902 MB | 1.5 s | 2.3 s | 0.22 s | 4.0 s | 0.952 |

| sam3-visual-q8_0.gguf | 494 MB | 0.7 s | 2.2 s | 0.22 s | 3.1 s | 0.953 |

| sam3-visual-q4_1.gguf | 303 MB | 0.7 s | 2.2 s | 0.21 s | 3.1 s | 0.937 |

| sam3-visual-q4_0.gguf | 276 MB | 0.6 s | 2.2 s | 0.23 s | 3.0 s | 0.915 |

Best for: SAM 3-quality segmentation without the text encoder — half the

size and ~40% faster than full SAM 3. Same PVS + tracking capabilities as

sam2.1_hiera_base_plus but with the stronger SAM 3 backbone.

SAM 2 (Hiera backbone, visual only)

| File | Size | Load | Encode | Segment | Total | score |

|------|------|-----:|-------:|--------:|------:|------:|

| sam2_hiera_tiny_f16.gguf | 76 MB | 0.79 s | 1.43 s | 0.37 s | 2.6 s | 0.959 |

| sam2_hiera_tiny_f32.gguf | 149 MB | 0.90 s | 0.98 s | 0.20 s | 2.1 s | 0.959 |

| sam2_hiera_tiny_q8_0.gguf | 41 MB | 0.39 s | 0.82 s | 0.16 s | 1.4 s | 0.959 |

| sam2_hiera_tiny_q4_1.gguf | 25 MB | 0.35 s | 0.81 s | 0.16 s | 1.3 s | 0.930 |

| sam2_hiera_tiny_q4_0.gguf | 23 MB | 0.43 s | 0.83 s | 0.17 s | 1.4 s | 0.933 |

| sam2_hiera_base_plus_f16.gguf | 156 MB | 0.82 s | 1.22 s | 0.20 s | 2.2 s | 0.957 |

| sam2_hiera_base_plus_f32.gguf | 309 MB | 0.97 s | 1.22 s | 0.17 s | 2.4 s | 0.957 |

| sam2_hiera_base_plus_q8_0.gguf | 84 MB | 0.93 s | 1.57 s | 0.28 s | 2.8 s | 0.955 |

| sam2_hiera_base_plus_q4_1.gguf | 51 MB | 0.73 s | 1.16 s | 0.18 s | 2.1 s | 0.954 |

| sam2_hiera_base_plus_q4_0.gguf | 46 MB | 0.65 s | 1.19 s | 0.22 s | 2.1 s | 0.952 |

| sam2_hiera_large_f16.gguf | 430 MB | 1.42 s | 1.47 s | 0.25 s | 3.1 s | 0.909 |

SAM 2.1 (improved SAM 2, same Hiera architecture)

| File | Size | Load | Encode | Segment | Total | score |

|------|------|-----:|-------:|--------:|------:|------:|

| sam2.1_hiera_tiny_f32.gguf | 149 MB | 0.78 s | 1.11 s | 0.21 s | 2.1 s | 0.943 |

| sam2.1_hiera_tiny_f16.gguf | 76 MB | 0.60 s | 1.03 s | 0.23 s | 1.9 s | 0.943 |

| sam2.1_hiera_tiny_q8_0.gguf | 41 MB | 0.62 s | 1.11 s | 0.24 s | 2.0 s | 0.945 |

| sam2.1_hiera_tiny_q4_1.gguf | 25 MB | 0.62 s | 0.95 s | 0.19 s | 1.8 s | 0.956 |

| sam2.1_hiera_tiny_q4_0.gguf | 23 MB | 0.73 s | 1.13 s | 0.25 s | 2.1 s | 0.927 |

| sam2.1_hiera_small_f32.gguf | 176 MB | 0.69 s | 0.88 s | 0.18 s | 1.8 s | 0.945 |

| sam2.1_hiera_small_f16.gguf | 90 MB | 0.75 s | 0.99 s | 0.19 s | 1.9 s | 0.945 |

| sam2.1_hiera_small_q8_0.gguf | 48 MB | 0.61 s | 0.96 s | 0.19 s | 1.8 s | 0.944 |

| sam2.1_hiera_small_q4_1.gguf | 30 MB | 0.72 s | 1.27 s | 0.19 s | 2.2 s | 0.947 |

| sam2.1_hiera_small_q4_0.gguf | 27 MB | 0.62 s | 1.11 s | 0.19 s | 1.9 s | 0.949 |

| sam2.1_hiera_base_plus_f32.gguf | 309 MB | 0.99 s | 1.25 s | 0.21 s | 2.5 s | 0.953 |

| sam2.1_hiera_base_plus_f16.gguf | 156 MB | 0.71 s | 1.09 s | 0.18 s | 2.0 s | 0.953 |

| sam2.1_hiera_base_plus_q8_0.gguf | 84 MB | 0.79 s | 1.40 s | 0.21 s | 2.4 s | 0.954 |

| sam2.1_hiera_base_plus_q4_1.gguf | 51 MB | 0.74 s | 1.44 s | 0.24 s | 2.4 s | 0.944 |

| sam2.1_hiera_base_plus_q4_0.gguf | 46 MB | 0.79 s | 1.34 s | 0.23 s | 2.4 s | 0.936 |

| sam2.1_hiera_large_f32.gguf | 857 MB | 1.42 s | 1.57 s | 0.18 s | 3.2 s | 0.940 |

| sam2.1_hiera_large_f16.gguf | 431 MB | 1.00 s | 1.29 s | 0.17 s | 2.5 s | 0.940 |

| sam2.1_hiera_large_q8_0.gguf | 231 MB | 0.76 s | 1.44 s | 0.19 s | 2.4 s | 0.938 |

| sam2.1_hiera_large_q4_1.gguf | 138 MB | 0.75 s | 1.68 s | 0.23 s | 2.7 s | 0.928 |

| sam2.1_hiera_large_q4_0.gguf | 124 MB | 0.77 s | 1.49 s | 0.23 s | 2.5 s | 0.900 |

Charts

• Latency chart — 40 locally benchmarked checkpoints (RTX 3060 CUDA)
• Effect grid — 40 locally benchmarked checkpoints on cat.jpg

Precision guide

| Precision | Relative size | Quality | Use |

|-----------|---------------|---------|-----|

| f32 | 1.0× | reference | Debugging, numerical checks only — never deploy |

| f16 | 0.5× | ≈ f32 | Recommended default — near-lossless, half the size |

| q8_0 | 0.25× | very close to f16 | Big models (large/sam3) when f16 is too big |

| q4_1 | ~0.14× | good (retains scale + offset) | Aggressive size cuts with better fidelity than q4_0 |

| q4_0 | ~0.13× | acceptable for interactive use | Smallest files; quality gap is visible on thin structures |

Size selection guide

| Need | SAM 3 | SAM 3 Visual | base_plus | tiny |

|------|-------|--------------|-----------|------|

| Text prompts (PCS) | Yes | - | - | - |

| PVS + tracking | Yes | Yes | Yes | Yes |

| Encode latency (RTX 3060) | 0.566 s (F16 PVS) | snapshot: 2.2 s | ~1.1–1.6 s | ~0.8–1.1 s |

| Size (f16) | 1.8 GB | 902 MB | 156 MB | 76 MB |

• SAM 2 vs SAM 2.1: prefer 2.1 for new projects (better training data and

tracking; same architecture, same speed, same sizes).

• Video tracking: tiny is the practical choice for interactive playback on

CPU; larger backbones work well on GPU.

• Point/box (PVS) + tracking work on every model here; **text-prompted

detection (PCS) requires a SAM 3 checkpoint* (the sam3- files above).