Can RTX 4090 run MiniCPM-V 2.6?
Yes — runs locally
~192 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4090 (24 GB VRAM) handles MiniCPM-V 2.6 comfortably using the Q8_0 quantization, which fits in 3.0 GB. Expected throughput is around 192 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Efficient multimodal model with strong image understanding. Optimized for edge devices.
How to run it
- 1. Install Ollama or LM Studio.
- 2. Pull the
Q8_0GGUF — best balance of quality and speed on 24 GB. - 3. Start chatting. Expect ~192 tok/sec on first-token, faster after warmup.
Other models that run great on RTX 4090
FAQ (20)
What GPU do I need to run MiniCPM-V 2.6?
To run MiniCPM-V 2.6, you need a GPU with at least 2.1 GB of VRAM, but 3.0 GB is recommended for better performance.
Is MiniCPM-V 2.6 good for coding?
MiniCPM-V 2.6 is primarily designed for multimodal tasks like image understanding and may not be optimized for coding-specific tasks.
MiniCPM-V 2.6 vs Llama 3.1 8B?
MiniCPM-V 2.6 has 2 billion parameters and is optimized for edge devices, while Llama 3.1 8B has 8 billion parameters and is more powerful but requires more resources.
Can I run MiniCPM-V 2.6 on a Mac?
Yes, MiniCPM-V 2.6 can run on a Mac with a compatible GPU and sufficient VRAM.
How much VRAM does MiniCPM-V 2.6 need?
MiniCPM-V 2.6 requires between 2.1 GB and 3.0 GB of VRAM, depending on the quantization level used.
Is MiniCPM-V 2.6 censored?
MiniCPM-V 2.6 is not inherently censored, but its outputs can be filtered or moderated based on the application and settings used.
Is MiniCPM-V 2.6 commercial-use allowed?
Yes, MiniCPM-V 2.6 is licensed under Apache-2.0, which allows commercial use without restrictions.
MiniCPM-V 2.6 context length?
The context length for MiniCPM-V 2.6 is 2048 tokens.
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