How to use from
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 dcostenco/prism-coder-14b
# Run inference directly in the terminal:
llama cli -hf dcostenco/prism-coder-14b
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dcostenco/prism-coder-14b
# Run inference directly in the terminal:
llama cli -hf dcostenco/prism-coder-14b
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 dcostenco/prism-coder-14b
# Run inference directly in the terminal:
./llama-cli -hf dcostenco/prism-coder-14b
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 dcostenco/prism-coder-14b
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dcostenco/prism-coder-14b
Use Docker
docker model run hf.co/dcostenco/prism-coder-14b
Quick Links

⚠️ DEPRECATED — Use prism-coder:9b instead

This model has been replaced by prism-coder-9b (Qwen3.5-9B).

Metric 14B (this, Qwen 3) 9B (replacement, Qwen 3.5)
BFCL Overall 90.3% 100.0%
Model Size 9.0 GB 5.8 GB (36% smaller)
Hallucinations 0 0
# Use this instead:
ollama pull dcostenco/prism-coder:9b

Current Fleet

Model Ollama tag Size BFCL Role
Qwen3.5-2B Q3_K_M dcostenco/prism-coder:2b 2.3 GB 99.1% iPhone / mobile
Qwen3.5-4B Q4_K_M dcostenco/prism-coder:4b 3.4 GB 100% Verifier / 8 GB+
Qwen3.5-9B Q4_K_M dcostenco/prism-coder:9b 5.8 GB 100% Default router
prism-coder:32b dcostenco/prism-coder:32b 19 GB 100% Complex tasks
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