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Near AI Cloud enables private GitHub Copilot inference through VSCode extension

Developers who use GitHub Copilot can now run the assistant on models hosted by Near AI Cloud without sending their code to external servers. The service is accessed through the VS Code “More Providers” extension, which exposes an OpenAI‑compatible API and works with the IDE’s Bring Your Own Key (BYOK) feature that removed the GitHub sign‑in requirement for custom endpoints.

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Key points

  • Near AI Cloud offers an OpenAI‑compatible API that lets Copilot run models inside TEEs, protecting prompts, weights, and outputs.
  • Input pricing is about $0.15‑$0.50 per million tokens; users can stake NEAR tokens for inference credits while keeping the stake.
  • The integration uses VS Code’s “More Providers” extension and BYOK support, removing the GitHub sign‑in requirement for custom endpoints.

Near AI Cloud protects prompts, model weights, and outputs inside Trusted Execution Environments built on Intel TDX and NVIDIA confidential computing. Each request includes a hardware‑signed attestation, and users may enable client‑side encryption for extra assurance. Pricing is about $0.15‑$0.50 per million input tokens, with higher output rates, and developers can stake NEAR tokens to receive inference credits while keeping their stake. The platform, launched in December 2025, added the SayGm gateway in August 2026 and an OpenRouter integration in September 2026, expanding access options for developers and NEAR token holders.

Full story from cryptobriefing.com · by Diego Almada Lopez · via Search: GitHubOpen source ↗

NEAR AI Cloud brings private inference to GitHub Copilot through a VSCode extension

cryptobriefing.com · 1 October 2026

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This text was published by cryptobriefing.com and written by Diego Almada Lopez. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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