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title: Arm Pulse emoji: ⚡ colorFrom: blue colorTo: indigo sdk: docker pinned: false

⚡ Arm Pulse - Arm64 LLM Inference Benchmark Suite + MCP Server

KleidiAI-optimized LLM benchmarking and inference server for Arm64 cloud infrastructure. Built for the Arm AI Optimization Challenge 2026.

License Platform Python

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🎯 What is Arm Pulse?

Arm Pulse is a one-command benchmarking tool that:

1. Deploys LLMs (Llama 3.2) on Arm64 cloud instances using llama.cpp + KleidiAI
2. Measures real performance tokens/sec, time-to-first-token, memory usage across quantization levels (Q4_K_M vs Q8_0)
3. Serves results via an MCP-compatible FastAPI server any agent framework can call
4. Visualizes everything in a clean real time dashboard

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🏗️ Architecture

arm-pulse/

├── benchmark/ # llama.cpp + KleidiAI inference engine + metrics

├── mcp_server/ # FastAPI MCP-compatible LLM endpoint

├── dashboard/ # Real-time results dashboard (HTML)

├── scripts/ # One-command setup + benchmark + server scripts

└── docker/ # Arm64-optimized Docker configuration

🚀 Quick Start (Arm64 Instance)

1. Clone and setup

git clone https://github.com/sirmos/arm-pulse.git
cd arm-pulse
bash scripts/setup.sh

2. Run benchmark

bash scripts/run_benchmark.sh

3. Start MCP server

bash scripts/start_mcp.sh

4. Open dashboard

Navigate to http://your-instance-ip:8000 in your browser.

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☁️ Tested Arm64 Platforms

Platform	Instance	Arm CPU
Oracle Cloud	VM.Standard.A1.Flex	Ampere Altra
AWS	c7g.large	Graviton3
GCP	c4a-standard-4	Axion

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📊 What We Benchmark

Metric	Description
Tokens/sec	Inference throughput
Time to First Token	Latency from prompt to first output token
Memory (MB)	RAM consumed during inference
Model size (GB)	Disk footprint per quantization level

Models

Model	Quant	Size	Use case
Llama-3.2-3B-Instruct	Q4_K_M	1.9 GB	Speed-optimized
Llama-3.2-3B-Instruct	Q8_0	3.4 GB	Quality-optimized

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🔌 MCP Server API

Endpoint	Method	Description
/	GET	Server info
/health	GET	Health + platform info
/models	GET	List available models
/generate	POST	Run inference
/benchmark	POST	Full benchmark suite
/mcp/tools	GET	MCP-compatible tools listing
/docs	GET	Interactive API docs

Example: Generate

curl -X POST http://localhost:8000/generate \
  -H "Content-Type: application/json" \
  -d '{"prompt": "What is KleidiAI?", "model": "Llama-3.2-3B-Q4_K_M"}'

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⚙️ Arm-Specific Optimizations

• KleidiAI: Arm's optimized kernel library for ML workloads
• llama.cpp Arm SVE: Scalable Vector Extension support enabled at build time
• Native CPU tuning: -DLLAMA_NATIVE=ON compiles for exact CPU microarchitecture
• Thread optimization: Automatically uses all available Arm cores

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📄 License

MIT License - see LICENSE

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Built for the Arm AI Optimization Challenge 2026