How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
# Run inference directly in the terminal:
llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
# Run inference directly in the terminal:
llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
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 HuggingFaceBio/Carbon-500M-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
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 HuggingFaceBio/Carbon-500M-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
Use Docker
docker model run hf.co/HuggingFaceBio/Carbon-500M-GGUF:BF16
Quick Links

Carbon-500M GGUF

GGUF (bf16) conversion of HuggingFaceBio/Carbon-500M for use with llama.cpp.

Carbon is a hybrid DNA / English language model that switches between Qwen3-4B-Base byte-level BPE for natural text and fixed 6-mer chunking for DNA inside <dna>...</dna> tags.

Requires a recent llama.cpp

HybridDNATokenizer support was merged in ggml-org/llama.cpp#23410, so any build from master after that works:

git clone https://github.com/ggml-org/llama.cpp
cd llama.cpp && cmake -B build && cmake --build build -j

Files

File Quant Size
carbon-500m-bf16.gguf bf16 (lossless from source) 983 MB

Usage

Download

hf download HuggingFaceBio/Carbon-500M-GGUF carbon-500m-bf16.gguf --local-dir .

Basic DNA completion

./build/bin/llama-completion -m carbon-500m-bf16.gguf \
    -p '<dna>ATGCGCTAGCTACGATCGATCGTAGCTAGCTAGCTAGCTACG' \
    -n 64 --temp 0 -no-cnv

As a draft model for speculative decoding

Carbon-500M shares the HybridDNA vocab with the larger models, so it makes an excellent draft model:

# 8B target + 500M draft -> ~2x speedup at temp=0
./build/bin/llama-speculative \
    -m  carbon-8b-bf16.gguf \
    -md carbon-500m-bf16.gguf \
    -p '<dna>ATGCGCTAGCTACGATCGATCGTAGCTAGCTAGCTAGCTACG' \
    -n 256 --temp 0

See also

License

Apache-2.0, inherited from the source model.

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