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MegawizCo/typhoon-ocr-7b-mlx-q8
typhoon-ocr-7b-mlx-q8 is a image-text-to-text model from MegawizCo. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
MLX-quantized port of typhoon-ai/typhoon-ocr-7b for native Apple Silicon inference. Highest-fidelity local option in the MegawizCo Typhoon-OCR collection — pick this when you can afford the RAM and latency.
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From the Hugging Face model README
MLX-quantized port of typhoon-ai/typhoon-ocr-7b for native Apple Silicon inference. Highest-fidelity local option in the MegawizCo Typhoon-OCR collection — pick this when you can afford the RAM and latency.
Quantization: 8-bit affine, group size 64. Effective rate 9.112 bits/weight. Size on disk: 8.8 GB.
The upstream typhoon-ai/typhoon-ocr-7b config.json is missing the vision_config fields that mlx-vlm's Qwen2.5-VL loader requires. We patched the config by copying those fields verbatim from upstream Qwen/Qwen2.5-VL-7B-Instruct. See the q4 variant for the patch script.
Same 7-image internal smoke set as the q4 variant, Mac mini Apple Silicon, 2026-05-13:
| Backend | HW CER median | HW CER max | Wall median | Generation TPS | Peak RAM |
|---|---|---|---|---|---|
| 3b MLX q4 | 0.009 | 0.081 | 1.95 s | ~107 | ~3.5 GB |
| 3b MLX q8 | 0.000 | 0.081 | 2.34 s | ~65 | ~5 GB |
| 7b MLX q4 | 0.012 | 0.037 | 3.55 s | ~56 | ~6 GB |
| 7b MLX q8 (this) | 0.012 | 0.028 | 4.66 s | ~32 | ~9 GB |
Read: lowest CER ceiling on this set (0.028 max). Pay 2× latency vs 3b q8 to get a ~3× lower worst-case CER (0.028 vs 0.081). Right call when accuracy on tricky cases matters more than throughput — e.g. legal documents, insurance claim escalation, Curator-marked high-stakes.
The test set is synthetic — real photographed handwriting will be harder.
uv pip install mlx-vlm
from mlx_vlm import generate, load
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
model, processor = load("MegawizCo/typhoon-ocr-7b-mlx-q8")
config = load_config("MegawizCo/typhoon-ocr-7b-mlx-q8")
prompt = apply_chat_template(processor, config, "Extract all text from this image.", num_images=1)
out = generate(model, processor, prompt, image=["prescription.png"], max_tokens=512)
print(out.text) # 7b wraps in {"natural_text": "..."}
⚠️ Output uses {"natural_text": "..."} (3b uses {"text": "..."}).
Same config-patch step as q4, then convert with --q-bits 8. See the q4 README for the full command.
MegawizCo/typhoon-ocr-7b-mlx-q4 — faster 7bMegawizCo/typhoon-ocr-3b-mlx-q4 — fastest, throughput-defaultMegawizCo/typhoon-ocr-3b-mlx-q8 — 3b high-fidelity