NEAR AI
@near_ai
Confidential, verifiable AI infrastructure for a user-owned AI economy.
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Qwen 3.8 27B Abliterated is live on NEAR AI Cloud.
Refusals removed, for red teaming and security research, with vision. It runs in a TEE, so your findings stay private.
$0.04/M input, $1.35/M output, 256K context.
Try it free:
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Uncensored AI is changing the balance of power in cybersecurity.
We're building to shift it toward defenders.
NEAR AI RED is a new program for security teams, with private, uncensored AI to work with.
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Private, uncensored AI for security work.
It runs in secure enclaves, so your vulnerabilities stay yours.
Live today on NEAR AI Cloud.
Kimi K3.1 Pro is live on NEAR AI Cloud.
Moonshot AI says it improves on its predecessor in coding, 3D creation and financial research, with a 1M-token context window.
$2/M input, $10/M output.
Try it free in the playground:
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Zero data retention isn't zero.
Your prompts stay readable by the provider while they run, with exceptions in the fine print and no way to check who saw them.
Here's why ZDR isn't enough, and what to use instead.
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Sage is now live on NEAR AI's confidential infrastucture.
Intel TDX and NVIDIA confidential computing, plus cryptographic attestation, give teams a verifiable boundary for classifying and deciding on sensitive enterprise data.
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Can private AI survive quantum computers?
Our lead engineer @Pierre_Le_Guen took that question on stage at @Ledger Op3n.
One minute, worth it 👇
NEAR AI Cloud's confidential inference is now live on @say_gm_'s confidential tier.
SayGm reaches dozens of models through one API key, and runs its own routing inside an Intel TDX enclave rather than on ordinary servers.
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Attestation reports on NEAR AI Cloud are verified against Intel's and NVIDIA's own services, at no cost, on every request. NEAR AI is not in the verification path.
Evaluating AI infrastructure for regulated datasets? Book a demo with our team of experts:
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Mathematician Tristan Buckmaster spent the better part of a year getting an AI to help him chase one of math's hardest problems.
Then he had to ask if he'd handed someone else the answer.
A policy page tries to build trust, but falls short. The infrastructure has to.
On NEAR AI Cloud, models run on secure hardware that proves nobody, not the model's maker or us ever sees or trains on your prompts.
You shouldn't have to ask and hope for an honest answer. You should be able to check.
And you can:
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