Run MiniCPM-V 4.7 35B-A3B on M4 Pro

MiniCPM-V 4.7 35B-A3B runs at 48 tok/s (48.2 as recorded) on a 64 GB M4 Pro, a community run reported by omlx.ai (MLX, 5-bit, 1k context). It needs about 23 GB of unified memory. It is OpenBMB's 35.2B mixture-of-experts model (3B active), released under the Apache 2.0 licence.

Speed
community48
tok/s
First Token
—
seconds
RAM Needed
23
GB minimum
Engine
MLX
of this figure
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The figure

This is a community run: a real run, reported by its source and linked below. The index records it as given and never adjusts it.

MetricValue
Tokens per secondcommunity48 tok/s
Provenancecommunity run · omlx.ai
Quantization5-bit
EngineMLX
Context1k
Figure dated2026-10-16
Minimum RAM23 GB
Parameters35.2B MoE (3B active)
Chip bandwidth273 GB/s

Every figure for MiniCPM-V 4.7 35B-A3B on the M4 Pro

Each row as the index holds it, with its source. “Mac RAM” is the memory of the Mac a run used, not the model’s requirement (23 GB). The headline figure follows the reference rule: the lower-median measured plain-decode run at 5 bits or fewer (a run whose quant was not stated counts only when no stated-quant run qualifies), else the estimate; a run marked “not used to anchor estimates” is listed here but never becomes the headline.

SpeedQuantEngineMac RAMContextSourceNote
community48.2 tok/s5-bitMLX64 GB1komlx.ai16-core GPU. oMLX v0.7.1.dev2, MTP/DFlash off. 47.9 tok/s at 4k.
Provenance key
sourced
Published figure — vendor or press review
estimated
community
Linked individual run — blog, forum or submission

Setup: run MiniCPM-V 4.7 35B-A3B on a Mac

Ollama — install it (brew install ollama or the app from ollama.com), then pull the model by its tag, checked on ollama.com on 2026-10-17:

ollama run openbmb/minicpm-v4.7:35b-a3b

MLX — pick a build from Hugging Face’s MLX listings, then run it with its repo id:

pip install -U mlx-lm
mlx_lm.generate --model <repo-id> --prompt "Hello"

Downloads: Hugging Face repo → · model card →

The 48 tok/s figure above came from MLX at 5-bit; other runtimes and quants run at different speeds.

Prefer a GUI? LM Studio downloads GGUF and MLX builds in one click. Step by step: install Ollama on a Mac.

MiniCPM-V 4.7 35B-A3B on other Apple Silicon chips

ChipSpeedQuantEngineBandwidth
M5 Maxcommunity100 tok/sMXFP4MLX614 GB/s
M4 Maxestimated92 tok/sQ4_K_MMLX546 GB/s
M5 Proestimated59 tok/sQ4_K_MMLX307 GB/s
M6estimated37 tok/sQ4_K_MMLX170 GB/s

About MiniCPM-V 4.7 35B-A3B

OpenBMB's Apache 2.0 vision-language MoE (Oct 2026): 35B total with ~3B active, image, multi-image and video input, 256K context. Q4_K_M is 21 GB plus a 1.1 GB vision projector, so it fits a 24 GB Mac; it runs in llama.cpp b11551+ (an image-grounding fix, PR #30510, is still open), mlx-vlm 0.7.8 and OpenBMB's Ollama namespace. Community oMLX runs measured 100.2 tok/s on an M5 Max (MXFP4) and 48.2 on an M4 Pro (5-bit).

Apache 2.0 licence · 35.2B MoE · 262K context · LLMCheck capability 35/50 · see its leaderboard rank →

System requirements

Macs with the M4 Pro

🛒 Get a Mac that runs MiniCPM-V 4.7 35B-A3B

MiniCPM-V 4.7 35B-A3B needs about 23 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:

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