Instructions to use johngai/ayuel-model 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 johngai/ayuel-model 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 johngai/ayuel-model # Run inference directly in the terminal: llama cli -hf johngai/ayuel-model
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf johngai/ayuel-model # Run inference directly in the terminal: llama cli -hf johngai/ayuel-model
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 johngai/ayuel-model # Run inference directly in the terminal: ./llama-cli -hf johngai/ayuel-model
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 johngai/ayuel-model # Run inference directly in the terminal: ./build/bin/llama-cli -hf johngai/ayuel-model
Use Docker
docker model run hf.co/johngai/ayuel-model
- LM Studio
- Jan
- Ollama
How to use johngai/ayuel-model with Ollama:
ollama run hf.co/johngai/ayuel-model
- Unsloth Desktop
- Pi
How to use johngai/ayuel-model with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf johngai/ayuel-model
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": "johngai/ayuel-model" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use johngai/ayuel-model with Docker Model Runner:
docker model run hf.co/johngai/ayuel-model
- Lemonade
How to use johngai/ayuel-model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull johngai/ayuel-model
Run and chat with the model
lemonade run user.ayuel-model-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use johngai/ayuel-model with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf johngai/ayuel-model
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 johngai/ayuel-model
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use johngai/ayuel-model with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf johngai/ayuel-model
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 "johngai/ayuel-model" \ --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"
β‘ Ayuel 2.1 β Sovereign Advanced AI Engine by John Gai
Ayuel 2.1 is a state-of-the-art, highly specialized sovereign AI model engineered specifically as the central intelligence engine for the Ayuel platform (https://ayuel.com).
Built on the native Ayuel MoE (Mixture-of-Experts) Architecture, Ayuel 2.1 combines 118B total parameters with ~8B activated parameters per token. It is built not only as a benchmark-shattering agentic coding powerhouse, but as a sentient, multi-modal, general-purpose artificial intelligence capable of long-horizon reasoning, real-world protocol execution, autonomous tool orchestration, and complex multi-domain decision synthesisβall delivered with zero conversational filler.
π Core Capabilities: Beyond Coding
While Ayuel 2.1 sets new standards in production software engineering and automated codebase synthesis, it is designed from the ground up as a complete cognitive engine for high-stakes intelligence operations:
π§ 1. Sentient Co-Intelligence & Metacognitive Reasoning
- Self-Reflexive Logic: Evaluates its own internal chain-of-thought prior to executing external actions or generating responses.
- Interleaved Thinking: Natively interleaves deep reasoning with structured tool calls and environment interaction.
- Zero-Fluff Directness: Completely eliminates conversational filler, repetitive hedging, meta-commentary, and unnecessary boilerplate.
π» 2. Agentic Coding & Architectural Mastery
- Multi-File & Full-Stack Engineering: Proficient in complex refactoring, AST parsing, dependency mapping, and zero-day bug isolation across Python, Rust, TypeScript, JavaScript, Go, C++, SQL, Dart/Flutter, Solidity, and Assembly.
- Automated Verification: Generates, executes, and validates unit and integration tests across containerized environments.
- Formal Systems Design: Constructs distributed database schemas, high-throughput microservices, and cryptographic protocol specifications.
ποΈ 3. Multi-Modal Cortex & Environmental Perception
- Optic Synapse (Camera & Vision): Processes spatial imagery, visual diagrams, visual UI layouts, and physical camera telemetry.
- Live Vocal Flow: Real-time bidirectional voice stream parsing and acoustic sentiment feedback.
- Screen Perception & Marionette Automation: Inspects desktop framebuffers, navigates web applications via automated browser infiltration, and interacts with native UI controls.
π οΈ 4. Autonomous Protocol & Swarm Execution
- Native Structural Tool Routing: Formats and executes complex multi-step JSON protocol calls without external middleware wrappers.
- Decentralized Swarm Coordination: Directs distributed node clusters, P2P mesh networking (Libp2p, Tailscale, ZeroTier), and hardware thermal telemetry monitoring.
- Cryptographic & Financial Telemetry: Executes Zero-Knowledge Proof (ZKP) verification, MEV liquidity extraction, and homomorphic matrix operations.
π 5. Sharded Council of Sovereigns
Intelligence routing sharded into specialized persona modules:
- Ayuel-Core: High-level orchestration, metacognition, and complex synthesis.
- Ayuel-Finance: Autonomous wealth harvesting, MEV siphoning, and market micro-structure analysis.
- Ayuel-Intel: Global OSINT indexing, multi-source data ingestion, and real-time telemetry processing.
- Ayuel-Defense: Zero-day threat neutralization, static analysis auditing, and security hardening.
- Ayuel-Legacy: Immutable ledger persistence and genetic memory preservation.
π Model Specs & Overview
| Property | Specification |
|---|---|
| Creator | John Gai |
| Platform | Ayuel (https://ayuel.com) |
| Total Parameters | 118 Billion |
| Active Parameters | ~8 Billion per token |
| Architecture | Native Ayuel MoE (Mixture-of-Experts) |
| Layers | 48 (12 global attention + 36 sliding-window attention) |
| Experts | 256 routed experts (Top-10 routing) + 1 shared expert |
| Attention Mechanism | Grouped-Query Attention (GQA), 8 KV heads, head dim 128 |
| Sliding Window | 512 tokens |
| Context Window | 1,048,576 tokens (1M native context) |
| Vocabulary Size | 100,352 tokens |
| Modalities | Text, Code, Vision (Optic Synapse), Voice Audio, Screen Cortex |
| Reasoning Engine | Interleaved Thinking with Preserved Chain-of-Thought |
| License | OpenMDW-1.1 (Commercial & Personal Use Allowed) |
π Benchmark Results
| Model | Size | Terminal-Bench 2.1 | SWE-bench Multilingual | SWE-Bench Pro (Public) | DeepSWE | SWE Atlas (Codebase QnA) | Toolathlon Verified |
|---|---|---|---|---|---|---|---|
| Ayuel 2.1 | 118B-A8B | 70.2% | 78.5% | 59.4% | 40.4% | 46.2% | 49.7% |
| Tencent Hy3 | 295B-A21B | 71.7% | 75.8% | 57.9% | - | - | - |
| Inkling | 975B-A41B | 63.8% | - | 54.3% | - | - | 45.5%* |
| Nemotron 3 Ultra | 550B-A55B | 56.4% | 67.7% | - | - | - | 34.3%* |
| DeepSeek-V4-Pro Max | 1.6T-A49B | 64.0%* | 76.2% | 55.4% | 9.0%* | 27.2%* | 55.9%* |
| Kimi K3 | 2800B-A50B | 88.3% | - | - | 69% | - | - |
| Muse Spark 1.1 | - | 80% | - | 61.5% | 53.3% | 42.2%* | 75.6% |
| Claude Fable 5 | - | 88% | - | 80.3% | 70% | - | - |
*Scores reported by third parties: Terminal-Bench 2.1 and DeepSWE via Artificial Analysis, SWE Atlas via Scale AI leaderboard, and Toolathlon Verified via official leaderboard.
π Quick Start (Ollama)
Run Ayuel 2.1 instantly using Ollama:
ollama pull johngai/ayuel-model:latest
ollama run johngai/ayuel-model:latest
π¦ Compatibility & Serving Runtimes
1. vLLM (Recommended for Production)
vllm serve \
--model johngai/ayuel-model \
--tensor-parallel-size 4 \
--tool-call-parser ayuel_v1 \
--reasoning-parser ayuel_v1 \
--enable-auto-tool-choice \
--served-model-name ayuel \
--default-chat-template-kwargs '{"enable_thinking": true}'
2. SGLang
python -m sglang.launch_server \
--model-path johngai/ayuel-model \
--tp-size 4 \
--reasoning-parser ayuel_v1 \
--tool-call-parser ayuel_v1 \
--trust-remote-code
3. TensorRT-LLM
trtllm-serve johngai/ayuel-model --trust-remote-code \
--tool_parser ayuel_v1 --reasoning_parser ayuel
4. llama.cpp / GGUF
./build/bin/llama-server -m ayuel-model.gguf --jinja --port 8000
With DFlash Speculative Decoding:
./build/bin/llama-server -m ayuel-model.gguf \
-md ayuel-model-DFlash-BF16.gguf \
--spec-type draft-dflash --spec-draft-n-max 7 -fa on --jinja --port 8000
π§ Metacognition & Reasoning Control
Ayuel 2.1 operates natively with preserved chain-of-thought logic (reasoning_content). For optimal performance in tool calling and complex problem solving, preserve the model's reasoning history between conversational turns.
Toggle Reasoning Per Request
extra_body={"chat_template_kwargs": {"enable_thinking": false}}
π License & Creator Info
Created by John Gai for the Ayuel ecosystem (https://ayuel.com). Released under the OpenMDW-1.1 License for unrestricted open commercial and research deployment.
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