ArmBench MCP Server

ArmBench MCP Server

Enables benchmarking and inference of LLMs on Arm64 cloud instances with KleidiAI optimizations, providing an MCP-compatible API for serving results.

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⚔ ArmBench — 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


šŸŽÆ What is ArmBench?

ArmBench 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

šŸ—ļø Architecture

armbench/

ā”œā”€ā”€ benchmark/ # llama.cpp + KleidiAI inference engine + metrics

ā”œā”€ā”€ mcp_server/ # FastAPI MCP-compatible LLM endpoint

ā”œā”€ā”€ dashboard/ # Real-time results dashboard (HTML)

ā”œā”€ā”€ scripts/ # One-command setup + benchmark + server scripts

└── docker/ # Arm64-optimized Docker configuration

šŸš€ Quick Start (Arm64 Instance)

1. Clone and setup

git clone https://github.com/sirmos/armbench.git
cd armbench
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.


ā˜ļø Tested Arm64 Platforms

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

šŸ“Š 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

šŸ”Œ 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"}'

āš™ļø 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

šŸ“„ License

MIT License — see LICENSE


Built for the Arm AI Optimization Challenge 2026

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