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AI Coding Assistants

FlashAgentAI tool

Use a compatible local llama.cpp model for coding tasks without a paid API call.

Free local application · model/hardware costs separate

The MIT terminal agent can use local llama.cpp inference. The model is not bundled: choose compatible weights and review their license separately. Cloud providers, including examples in the project demo, can add usage charges. No weights are bundled. The official Ollama qwen2.5-coder:7b listing states Apache-2.0 and 4.7GB; verify compatibility and model licensing separately. Local hardware, storage, download, and electricity still have costs. Optional remote inference can be billed.

Pricing checked .

Check official pricing
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FlashAgent product interface
FlashAgent · Project terminal demo GIF; the shown OpenRouter/model setup may involve separate API charges.
Product image: flashback7766 · MIT · Original image; layout scaled to fit. Project terminal demo GIF; the shown OpenRouter/model setup may involve separate API charges. Full notice.Logo: flashback7766 · MIT · Original image; layout scaled to fit. Provider asset identifies flashagent; no endorsement is implied. Full notice.

About FlashAgent

A terminal coding agent with a local llama.cpp route as well as optional hosted providers. Local setup reduces dependence on per-call API pricing, with hardware and model tradeoffs. A self-hosting option is recorded for this project. Review the official deployment instructions and maintenance requirements before running it yourself.

Release status

Official README and root license checked against this revision on 2026-11-01. Local model and provider costs are recorded separately; AltStack did not execute the project or its installers.

Availability checked 1 Nov 2026. Check the provider’s release or installation information

Installation and setup

Install on your computer · Instructions checked 2026-11-01

  1. Read the official README for the current CLI requirements and supported local inference backend.
  2. Install FlashAgent using only the official repository instructions.
  3. Start the documented local llama.cpp-compatible inference service and select a model supported by that service.
  4. Try a small disposable repository before allowing the agent to read or modify important project files.

Local inference avoids a paid model API when configured as documented. Model weights, hardware, disk space, and electricity are separate.

Self-hosting & quickstart specs

License
MIT
Deployment
Local desktop application
Free edition / costs
Free local application · model/hardware costs separate. The MIT terminal agent can use local llama.cpp inference. The model is not bundled: choose compatible weights and review their license separately. Cloud providers, including examples in the project demo, can add usage charges. No weights are bundled. The official Ollama qwen2.5-coder:7b listing states Apache-2.0 and 4.7GB; verify compatibility and model licensing separately. Local hardware, storage, download, and electricity still have costs. Optional remote inference can be billed. Pricing evidence.
Devices / hardware
Local inference avoids a paid model API when configured as documented. Model weights, hardware, disk space, and electricity are separate.

No one-line command has been verified for FlashAgent; follow its official installation instructions instead of guessing a Docker image or installer.

FlashAgent provider setup documentation

Explore the project

Technology stack

Technologies recorded in the catalog snapshot.

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