---
license: mit
base_model: microsoft/Phi-4-multimodal-instruct
tags:
  - phi4mm
  - gguf
  - quantized
  - q4_k_m
  - cpu
  - ollama
  - llama-cpp
language:
  - multilingual
  - ar
  - zh
  - cs
  - da
  - nl
  - en
  - fi
  - fr
  - de
  - he
  - hu
  - it
  - ja
  - ko
  - "no"
  - pl
  - pt
  - ru
  - es
  - sv
  - th
  - tr
  - uk
pipeline_tag: text-generation
---

# Phi-4 Multimodal Instruct — GGUF Quantizations

CPU-optimised GGUF quantizations of [microsoft/Phi-4-multimodal-instruct](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) produced with [llama.cpp](https://github.com/ggerganov/llama.cpp).

## Model Summary

Phi-4-multimodal-instruct is a **5.6 B parameter** lightweight multimodal foundation model by Microsoft that processes text, image, and audio inputs. The backbone LLM is **Phi-4-Mini** (3.8 B). This repository contains GGUF quantizations for local CPU and GPU deployment.

- **Context length:** 128 K tokens (131 072)
- **Architecture:** `phi3` (GGUF)  
- **License:** [MIT](https://huggingface.co/microsoft/Phi-4-multimodal-instruct/blob/main/LICENSE) — © Microsoft Corporation

## Available Files

| File | Quant | Size | BPW | Best for |
|------|-------|------|-----|----------|
| `phi4-mm-Q4_K_M.gguf` | Q4_K_M | 2.37 GB | 5.18 | CPU inference, 8 GB RAM systems |
| `phi4-mm-Q8_0.gguf`   | Q8_0   | 3.90 GB | 8.00 | GPU/high-RAM systems, near-lossless |
| `phi4-mm-f16.gguf`    | F16    | 7.17 GB  | 16.00 | Source / re-quantization base |

## Quantization Method

Quantized using `llama-quantize` from [ggerganov/llama.cpp](https://github.com/ggerganov/llama.cpp) (build 8334).

```bash
llama-quantize phi4-mm-f16.gguf phi4-mm-Q4_K_M.gguf Q4_K_M 16
```

Source weights converted from the original safetensors using `convert_hf_to_gguf.py`.

## Recommended Usage

### Ollama (CPU — Intel NUC / low-power hardware)

```bash
# Pull and run (once uploaded to Ollama registry)
ollama run phi4-mm-nuc

# Or import from GGUF directly with a Modelfile:
ollama create phi4-mm-nuc -f Modelfile
ollama run phi4-mm-nuc
```

**Modelfile for 8 GB RAM / no GPU:**

```
FROM phi4-mm-Q4_K_M.gguf
PARAMETER num_ctx 8192
PARAMETER num_thread 8
PARAMETER num_gpu 0
PARAMETER flash_attn false
PARAMETER temperature 0.7
PARAMETER repeat_penalty 1.1
SYSTEM "You are a helpful, accurate, and concise AI assistant."
```

### llama.cpp CLI (GPU, full quality)

```bash
./build/bin/llama-cli \
  -m phi4-mm-Q8_0.gguf \
  --ctx-size 65536 \
  --flash-attn on \
  --kv-offload \
  -ngl 99 \
  --threads 16
```

### OpenClaw Integration

In `~/.openclaw/openclaw.json`:

```json
{
  "agent": {
    "model": "ollama/phi4-mm-nuc"
  },
  "modelConfigs": {
    "ollama/phi4-mm-nuc": {
      "provider": "ollama",
      "model": "phi4-mm-nuc",
      "baseUrl": "http://localhost:11434"
    }
  }
}
```

## Hardware Notes

| Hardware | Recommended quant | Context | Notes |
|---|---|---|---|
| Intel NUC 11th Gen, 8 GB RAM | Q4_K_M | 8 192 | CPU-only, `num_gpu 0` |
| Laptop / desktop, 16 GB RAM | Q5_K_M or Q8_0 | 16 384 | CPU or iGPU |
| GPU with ≥ 8 GB VRAM | Q8_0 or F16 | 32 768–65 536 | Full `-ngl 99` offload |

## License

This repository redistributes quantized weights derived from [microsoft/Phi-4-multimodal-instruct](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) under the original **MIT License**.

```
MIT License
Copyright (c) Microsoft Corporation.
```

Quantization tooling (llama.cpp) is also MIT licensed. See [llama.cpp LICENSE](https://github.com/ggerganov/llama.cpp/blob/master/LICENSE).

## Attribution

- Original model: Microsoft Research  
- Quantization: produced with [llama.cpp](https://github.com/ggerganov/llama.cpp) by Georgi Gerganov et al.  
- Technical report: [arXiv:2503.01743](https://arxiv.org/abs/2503.01743)