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Hardware & Compute3 min read

Zagita tool doubles RTX 30/40 GPU compute, driving used prices up

A new open-source Linux tool called Zagita has unlocked the full BF16/FP16 compute rates on NVIDIA's RTX 30 and RTX 40 series GPUs. By using a kernel module that applies specific speed selectors before the driver binds, the tool doubles the instruction issuing speed for FP/BF16 FMA operations on GA102, GA103, GA104, and GA106 chips without requiring vBIOS flashing or hardware mods. Users report…

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Key points

  • Zagita tool doubles BF16/FP16 compute on RTX 30/40 GPUs via Linux kernel module.
  • RTX 3090 Ti BF16 performance increases from 87.5 TFLOPs to 157 TFLOPs.
  • Used RTX 3090 prices have surged past $2,000 due to increased AI demand.

In practical AI LLM workloads, the unlock delivers a 33-36% faster prefill speed and reduces time-to-first-token latency by 25%, though decode performance remains unchanged. One user reportedly achieved 381 tokens per second on a Qwen3.8-27B model using an RTX 3090, a significant increase from the baseline 82 TPS. The tool currently supports only Linux, with Windows support not yet available.

This performance uplift has triggered a sharp rise in the used market. The RTX 3090 24 GB, previously around $1,000, has climbed past $2,000, while the RTX 3090 Ti approaches $3,000. RTX 3080 models are now selling for $900-$1,100 on eBay. While the tool makes older cards viable for AI inference and fine-tuning, it is making them less accessible for gamers due to the price surge driven by AI demand.

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Full story from wccftech.com · by Hassan Mujtaba · via Reddit AI communitiesOpen source ↗

CMP170HX inspiration unlocks 30x/40x also, up to 2X Prefill speedup --> NVIDIA RTX 30 & RTX 40 GPUs Get Impressively Fast In AI LLMs As Compute Doubles With New Unlock Tool But Prices Surge Too

wccftech.com · 24 October 2026

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This text was published by wccftech.com and written by Hassan Mujtaba. 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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