Instructions to use dcostenco/prism-coder-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use dcostenco/prism-coder-14b 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 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

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -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

Llama new
LM Studio
Jan

vLLM

How to use dcostenco/prism-coder-14b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dcostenco/prism-coder-14b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dcostenco/prism-coder-14b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dcostenco/prism-coder-14b

Ollama
How to use dcostenco/prism-coder-14b with Ollama:
```
ollama run hf.co/dcostenco/prism-coder-14b
```
Unsloth Desktop

How to use dcostenco/prism-coder-14b with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf dcostenco/prism-coder-14b

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "dcostenco/prism-coder-14b"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use dcostenco/prism-coder-14b with Docker Model Runner:
```
docker model run hf.co/dcostenco/prism-coder-14b
```

Lemonade

How to use dcostenco/prism-coder-14b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull dcostenco/prism-coder-14b

Run and chat with the model

lemonade run user.prism-coder-14b-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use dcostenco/prism-coder-14b with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf dcostenco/prism-coder-14b

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default dcostenco/prism-coder-14b

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use dcostenco/prism-coder-14b with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf dcostenco/prism-coder-14b

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "dcostenco/prism-coder-14b" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

dcostenco commited on Jun 14

Commit

8def481

verified ·

1 Parent(s): 3f44862

Add fleet position table (June 2026 update)

Browse files

Files changed (1) hide show

README.md +14 -0

README.md CHANGED Viewed

@@ -158,3 +158,17 @@ text. ABSTAIN for general programming questions, CS concepts, greetings, and cap
 | 4B | `dcostenco/prism-coder:4b` | Mid-tier verify |
 | **14B** | **`dcostenco/prism-coder:14b`** | **Production routing** |
 | 32B | `dcostenco/prism-coder:32b` | Top-tier / complex reasoning |

 | 4B | `dcostenco/prism-coder:4b` | Mid-tier verify |
 | **14B** | **`dcostenco/prism-coder:14b`** | **Production routing** |
 | 32B | `dcostenco/prism-coder:32b` | Top-tier / complex reasoning |
+---
+## Fleet Position (June 2026)
+| Model | Ollama tag | Size | BFCL | Role |
+|---|---|---|---|---|
+| Qwen3.5-4B Q3_K_M | `prism-coder:2b` | 2.3 GB | 99.1% | iPhone / mobile |
+| Qwen3.5-4B Q4_K_M | `prism-coder:4b` | 3.4 GB | 100% | Verifier / 8 GB+ |
+| **prism-coder:14b** | **`prism-coder:14b`** | **8.4 GB** | **100%** | **Mac default** |
+| prism-coder:32b | `prism-coder:32b` | 16 GB | 100% | Complex tasks |
+The 1.7B and 8B models have been retired. The 2B/4B slots now use Qwen3.5-4B at different quantization levels.