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Triton backend accelerates Falcon3-10B inference by 9.8x on RTX 5070

A developer has created a new Triton backend for the Falcon3-10B-1.58bit model, significantly boosting inference speed on an NVIDIA RTX 5070 GPU. The new backend achieved 97.5 tokens per second for decoding, a nearly 10x improvement over the stock Transformers BitLinear implementation. This optimization utilizes techniques like K-contiguous packed ternary weights, a packed-word DP4A decode path, and CUDA Graph replay, with the developer seeking further reproductions and benchmarks on different GPU architectures. AI

IMPACT Demonstrates significant potential for optimizing inference speed on consumer hardware through custom backends.

RANK_REASON Developer-created optimization for an existing model and hardware. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

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

Triton backend accelerates Falcon3-10B inference by 9.8x on RTX 5070

COVERAGE [1]

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

    I built a Triton backend for Falcon3-10B-1.58bit: 97.5 tok/s decode on an RTX 5070

    <!-- SC_OFF --><div class="md"><p>Hi <a href="/r/LocalLLaMA">r/LocalLLaMA</a> — I’m sharing an experimental GPU-only inference backend and looking for independent reproductions, not just stars.</p> <p>Model: tiiuae/Falcon3-10B-Instruct-1.58bit</p> <p>GPU: NVIDIA RTX 5070</p> <p>B…