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GLM OCR OQ8 FP16

This model was quantized using oQ mixed-precision quantization.

TipoText modelModelo basezai-org/GLM-OCRVersiónmodelBcalidad

Fuente del modelo

Tipo
Text model
Tamaño del archivo
1,48 GB
Modelo base
zai-org/GLM-OCR
Versión
vmodel
Actualizado
2 nov 2026
Descargas
30
Fuente
Hugging Face

Descripción de la fuente

GLM-OCR-oQ8-fp16

This model was quantized using oQ mixed-precision quantization.

float16 gives ~20% faster prefill on M1/M2 Apple Silicon (native fp16). bfloat16 is safer on M3/M4 and for numerical stability.

Benchmark (on M1 Max)

Model VariantPP (Tokens per second)TG (Tokens per second)
Original (bf16)4,684104.8
oQ8-fp163,80699.0

Fuentes

1 fuente
Hugging FacePrincipalVersión a022b88dff7e5846cec52dc3dc27d520fd3a37e6
huggingface.co/RepublicOfKorokke/GLM-OCR-oQ8-fp16/tree/a022b88dff7e5846cec52dc3dc27d520fd3a37e6

Verificado 2 nov

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Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 1,48 GB · SHA-256 d64c990014b0…d778 · Hugging Face

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Extractos de fuentes

3 extractos

--- license: mit base_model: - zai-org/GLM-OCR pipeline_tag: image-to-text language: - zh - en - fr - es - ru - de - ja - ko tags: - mlx - oq - quantized library_name: mlx --- # GLM-OCR-oQ8-fp16 This model was quantized using [oQ](https://github.com/jundot/omlx) mixed-precision quantization. float16 gives ~20% faster prefill on M1/M2 Apple Silicon (native fp16). bfloat16 is safer on M3/M4 and for numerical stability. # Benchmark (on M1 Max) | Model Variant | PP (Tokens per second) | TG (Tokens per second) | | :--- | :---: | :---: | | Original (bf16) | 4,684 | 104.8 | | oQ8-fp16 | 3,806 | 99.0 |

Source context: 30 downloads · 3 likes · Pipeline image-to-text · Library mlx · Repo RepublicOfKorokke/GLM-OCR-oQ8-fp16

Source context: 69 downloads · 3 likes · Pipeline image-to-text · Library mlx · Repo RepublicOfKorokke/GLM-OCR-oQ8-fp16