autotune
PulseGate's liveness check found it on 14 Sep 2026; it has been in the index since 1 Jul 2026. How this is checked
autotune is a local AI optimization tool for code that sends requests to Ollama. It sits between user code and Ollama as a transparent proxy and applies automatic adjustments to memory use and request handling, with the stated goal of making local AI faster while keeping code unchanged and avoiding config changes.
Inferred · not functionally tested
Overview
6 featuresPurpose: Improving the speed and reliability of running large language models locally by optimizing resource usage.
Inferred · not functionally tested
Audience: developers running local LLMs
Inferred · not functionally tested
Functions: monitoring
Inferred · not functionally tested
Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)
Recorded constraints: pricing: open_source · license: MIT · platforms: CLI, WEB · deployment: browser, cli, self_hosted
Constraint provenance is unknown; confirm requirements with the publisher.
Record sources: autotunellm.com. These links do not verify the individual claims.
autotune is an Inference & model serving project. Inferred · not functionally tested: It focuses on improving the speed and reliability of running large language models locally by optimizing resource usage. Inferred · not functionally tested: autotune is an open-source project aimed at developers running local LLMs. Basis unknown · not verified: autotune is open source under the MIT license. Basis unknown · not verified: It ships for the web and the command line, and it can be self-hosted.
autotune first shipped in 2026. The project is developed in the open on GitHub with 30 stars and 101 commits in the last 90 days. Inferred · not functionally tested: Key capabilities include memory optimization, response time reduction, and Drop-in Ollama wrapper.
Summary written by a language model from the project’s public pages.
Tasks: Inferred · not functionally tested
- Memory optimization
- Response time reduction
- Drop-in Ollama wrapper
- System prompt caching
- Context management
- No configuration required
Topics: Inferred · not functionally tested
Built with & integrations
- Next.js
- x-nextjs-prerender header · /_next/static/ in the HTML · __next_f in the HTML
- Vercel
- x-vercel-id header · x-vercel-cache header
- multiple
- bLangChain in the HTML · bLlamaIndex in the HTML
- local_oss
- bollama in the HTML
- meta_llama
- llama- in the HTML
Trust & compliance
Indexing history
What PulseGate has recorded for this listing
Frequently asked questions about autotune
- What is autotune?
- Inferred · not functionally tested: Autotune focuses on improving the speed and reliability of running large language models locally by optimizing resource usage. It is catalogued under Inference & model serving on PulseGate.
- Who is autotune for?
- Inferred · not functionally tested: autotune is an open-source project built for developers running local LLMs.
- Does autotune have a free plan?
- Basis unknown · not verified: Yes — autotune is open source under the MIT license and free to use.
- What platforms does autotune run on?
- Basis unknown · not verified: autotune runs on the web and the command line. It can also be self-hosted.
- Is autotune still active?
- PulseGate's liveness check found it on 14 Sep 2026. Its GitHub repository shows 101 commits in the last 90 days.
- How long has autotune been around?
- autotune first shipped in 2026.
- Is autotune open source?
- Basis unknown · not verified: Yes — autotune is open source under the MIT license.
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