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Gevva0 decision engine uses Gemma 2, achieves low latency

A developer has developed a cascading decision engine called Gevva0, which utilizes a combination of static rules, Absorbing Markov Chains with Gemma 2 embeddings, and a fast-path logits approach to achieve low-latency decision-making. Initially, a claim of 100% GTO parity in Blackjack was made, but this was later retracted due to a prompt-leakage bug, with corrected figures showing around 15-29% true zero-shot GTO parity. The system also demonstrated competitive performance against Claude Opus 4.6 on intelligence benchmarks and significantly outperformed dense models in terms of speed. AI

IMPACT Demonstrates a novel approach to low-latency decision-making by combining existing models and techniques, potentially applicable to real-time systems.

RANK_REASON The item describes a novel application of existing models and techniques for a specific task, rather than a new model release or fundamental research.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Gevva0 decision engine uses Gemma 2, achieves low latency

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4 / 100
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Tool
The item describes a novel application of existing models and techniques for a specific task, rather than a new model release or fundamental research.
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/inawhole ·

    Using Absorbing Markov Chains + EmbeddingGemma 2 as a Decision Engine: ~2ms inference with 100% GTO Parity on Vegas Blackjack

    <!-- SC_OFF --><div class="md"><p><strong>[UPDATE / RETRACTION: The &quot;100% GTO&quot; claim had a prompt-leakage bug]</strong></p> <p>We patched the repo to pass strictly neutral states, here are the real, honest numbers: • Latency: Still ~2ms (ONNX + Absorbing Markov Chain). …