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LLMxRay

See what your local AI is actually doing, step by step

Observability for developers running local LLMs on Ollama: stream output live, compare models side by side, benchmark with logprobs, and inspect reasoning chains.

Built by Ivan Stankovic · MCP · Free

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In category: #28 of 31 · MCP

LLMxRay is a Community listing on Launch Llama with 0 total upvotes, founded by Ivan Stankovic who joined in Oct 2026, compared against 6 alternatives.

Community listing

Listing status

0upvotes

Community score

Ivan Stankovic (Joined Oct 2026)

Founder

Launched on Launch Llama Oct 26, 2026 · #52 of 111 that day

LLMxRay

About

LLMxRay is a full observability interface for Ollama, covering chat, streaming output, reasoning traces, RAG workflows, introspection, and metrics. It launches with a single npx command and runs entirely on your own machine, so there are no cloud dependencies or usage fees. The project comes from a digital transformation advisor who frames it as an early layer toward human-AI understanding, and the interface is built with Vue 3, TypeScript, Vite, and D3.js.

Key Features

  • Streams model tokens in real time as they are generated
  • Delivers compares multiple local models side by side in one view
  • Delivers benchmarks models using real logprobs data
  • Delivers inspects reasoning chains to see how decisions are made
  • Runs fully locally against Ollama with no cloud costs
  • Tracks chat, RAG, and metrics through a Vue-based interface

Use Cases

  • Watching what VS Code Copilot, Open WebUI or Continue actually send to a local Ollama model, turn by turn, to find oversized prompts or broken cache reuse
  • Comparing the same prompt across several local models side by side and checking token probabilities and benchmark logprobs
  • Sending Ollama call traces as OpenTelemetry spans to Jaeger, Phoenix, Langfuse or Grafana to debug agent runs

Who it is for

  • Developers running local LLMs on Ollama who want visibility into their tools' requests
  • Engineers building or debugging AI agents that call a local Ollama model
  • Teams evaluating and benchmarking local models before choosing one

Pricing

LLMxRay is free to use. See the website for details.

View LLMxRay pricing →

Alternatives

AI Observability by OpenObserveFor AI teams: OpenObserve monitors LLM agents with 140x lower storage costs than competitors so you debug production issues without breaking budgets.OllamaFor Apple users: Ollama runs large language models locally on Apple Silicon with MLX for faster coding and agent workflows.SpanlensFor developers: Spanlens logs every LLM API call with cost, latency, and tokens so you optimize spend and catch performance issues instantly.Future AGIFor AI engineers: traceAI captures prompts, completions, and agent decisions across 35+ frameworks, routing to your existing observability stack in two lines of code.What's my local ai?For AI engineers: What's my local ai? detects your hardware and recommends local models so you run LLMs privately without cloud costs.Markstream VueFor AI developers: Markstream Vue renders streaming Markdown across Vue, React, Next.js, and Svelte so users see AI responses in real-time.

Tags

#ollama#local llm#streaming output#model comparison#logprobs benchmarking#reasoning traces#rag debugging#offline ai

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