Instructions to use Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 # Run inference directly in the terminal: llama cli -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 # Run inference directly in the terminal: llama cli -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 # Run inference directly in the terminal: ./llama-cli -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
Use Docker
docker model run hf.co/Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
- LM Studio
- Jan
- Ollama
How to use Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 with Ollama:
ollama run hf.co/Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
- Unsloth Studio
How to use Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 to start chatting
- Docker Model Runner
How to use Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 with Docker Model Runner:
docker model run hf.co/Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
- Lemonade
How to use Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Lucebox/DeepSeek-V4-Flash-0731-ROCmFP3
Run and chat with the model
lemonade run user.DeepSeek-V4-Flash-0731-ROCmFP3-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
File size: 1,950 Bytes
eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 eeba8f3 39745d3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | ---
license: mit
base_model: deepseek-ai/DeepSeek-V4-Flash-0731
tags: [gguf, rocmfpx, strix-halo, mixed-precision, quantization]
---
# DeepSeek-V4-Flash-0731 for Strix Halo
**82/92 quality in one 98.29 GB GGUF file.**
Built for 128 GB AMD Strix Halo systems. It loads unsplit on the Radeon 8060S
iGPU and needs no sidecar files.
## Quality
| Test | Score |
|---|---:|
| Full 92-question evaluation | **82/92** |
| COMPSEC-17 | **17/17** |
The full score matches the published reference. This file averages 2.766 bits
per model weight, about 4% less than the 2.88-bit reference.
None of the 92 test questions were used while preparing this file. The
published reference used 75 of them during its own preparation. Both results
used the same grader and reasoning allowance.
## Quality or speed
| Mode | Options | Decode speed | COMPSEC-17 |
|---|---|---:|---:|
| **Quality** (default) | No extra flags | 18.1 tok/s | **17/17** |
| **Faster** | `--ds4-expert-top-k 4 --ds4-fused-decode` | **22.3 tok/s** | 16/17 |
Quality mode is the recommended setting. Faster mode is 23% quicker but misses
one additional COMPSEC question. The full 82/92 evaluation was run only in
quality mode.
The current DSpark helper model makes this file slower overall, so it is not
recommended yet.
## Download
`DeepSeek-V4-Flash-0731-ROCMFPX-MIX-STRIX.gguf`
- Size: 98,294,917,184 bytes
- One file, no sidecars
- SHA-256: `7c0789d190fdd2acad93255825822ca276f29d13f9410f2ac65f5f7a542b0a38`
## Run
```bash
dflash_server DeepSeek-V4-Flash-0731-ROCMFPX-MIX-STRIX.gguf \
--target-device hip:0 \
--max-ctx 8192
```
Use the normal automatic memory settings on Strix Halo. If the machine also
has a discrete GPU, expose only the iGPU with `HIP_VISIBLE_DEVICES`.
Until support reaches the main dflash release, use the
`feat/qtype106-down-surface` branch of `GeometricAGI/lucebox-hub`.
Artifact and evaluation by Geometric-AI. Mirrored byte-for-byte by Lucebox.
|