MiniCPM-OCR 1.0 1.3B on AMD Ryzen 7 8845HS / Ryzen 7 255 NAS (8 GB)

Can the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS (8 GB) run MiniCPM-OCR 1.0 1.3B?

Yes, it runs great

Runs great. At Q8_0 it needs about 2.4 GB of 4.0 GB usable, with an estimated speed of 47.9 tok/s.

Best quant: Q8_0
Generation speed: 47.9 tok/s
Prompt processing: 10,215 tok/s
First token (1K prompt): 0.3 s
Largest safe context: 135K

Best app to run it on the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS (8 GB)

On Linux

llama.cpp

Command line + local API · runs on llama.cpp

Usually the first to support new model architectures.

llama-server -hf openbmb/MiniCPM-OCR-1.0-gguf:Q8_0

Ollama Runs the Hugging Face GGUF with ollama run hf.co/…
KoboldCpp

How we choose: the files published for this model, which apps run in a container on a NAS without a graphics card (models run on its processor), and whether the model fits fully in the memory models can use. Details.

Download MiniCPM-OCR 1.0 1.3B

Recommended for the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS (8 GB): Q8_0. Every other quantization has its own download link in the table below.

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q8_0 file (opens in a new tab)

huggingface.co/openbmb/MiniCPM-OCR-1.0-gguf (opens in a new tab)

ollama run hf.co/openbmb/MiniCPM-OCR-1.0-gguf:Q8_0

Original weights · Hugging Face

Full-precision files from OpenBMB, for fine-tuning, vLLM, Transformers.

huggingface.co/openbmb/MiniCPM-OCR-1.0 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from OpenBMB. The weights themselves download from Hugging Face.

github.com/OpenBMB/MiniCPM-OCR (opens in a new tab)

git clone https://github.com/OpenBMB/MiniCPM-OCR

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 42Fair quality (C) · 42 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at Q8_0, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Runs great: How well it runs on the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS (8 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	18.9 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.	25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	13.8 / 15
Match score	72.7 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS (8 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	1.5 GB	4.0 GB	154 tok/s	Runs great	29Basic quality (D) · 29 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`Q3_K_M`	1.7 GB	4.0 GB	122 tok/s	Runs great	35Basic quality (D) · 35 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`Q4_K_M`	1.8 GB	4.0 GB	94.0 tok/s	Runs great	39Basic quality (D) · 39 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q5_K_M`	1.9 GB	4.0 GB	77.7 tok/s	Runs great	40Fair quality (C) · 40 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q6_K`	2.1 GB	4.0 GB	65.2 tok/s	Runs great	41Fair quality (C) · 41 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q8_0`	2.4 GB	4.0 GB	47.9 tok/s	Runs great	42Fair quality (C) · 42 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`F16`	3.6 GB	4.0 GB	22.1 tok/s	Runs welltight fit	42Fair quality (C) · 42 of 100: how capable the model is at F16, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab) Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

42Fair quality (C) · 42 of 100: how capable the model is at F16, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4060 F16 · 60.3 tok/s · Runs great
42Fair quality (C) · 42 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. Intel Arc B580 F16 · 77.2 tok/s · Runs great
42Fair quality (C) · 42 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 3060 12GB F16 · 79.8 tok/s · Runs great
42Fair quality (C) · 42 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 SUPER F16 · 112 tok/s · Runs great
42Fair quality (C) · 42 of 100: how capable the model is at F16, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. Apple M4 Pro (24 GB) F16 · 52.1 tok/s · Runs great
42Fair quality (C) · 42 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. Apple M4 (16 GB) Q8_0 · 49.7 tok/s · Runs great

Quick answers

How much memory does MiniCPM-OCR 1.0 1.3B need on the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS 8GB?

At Q8_0 it needs about 2.4 GB. The AMD Ryzen 7 8845HS / Ryzen 7 255 NAS 8GB has 4.0 GB usable.

How fast is MiniCPM-OCR 1.0 1.3B on the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS 8GB?

About 47.9 tok/s at Q8_0, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of MiniCPM-OCR 1.0 1.3B should I use on the AMD Ryzen 7 8845HS / Ryzen 7 255 NAS 8GB?

Q8_0. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.