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DeepSeek-V4.1-Flash-1017 Coder model pruned to 763B parameters

ISTA has released a new version of its DeepSeek-V4.1-Flash-1017 model, specifically a Coder build that has been compressed using GSQ and RCO techniques. This optimized version removes half of the model's routed experts, reducing its parameter count to 763.2 billion, with 551.9 billion in the transformer. The pruned model retains a high percentage of its original performance, achieving 98.7% on LiveCodeBench v6 and 94.8% on SWE-bench Verified, demonstrating its effectiveness in coding tasks. AI

IMPACT This release showcases advanced model compression techniques, potentially enabling more efficient deployment of large language models.

RANK_REASON Release of a specific model variant with performance metrics and details on compression techniques. [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 →

DeepSeek-V4.1-Flash-1017 Coder model pruned to 763B parameters

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Release of a specific model variant with performance metrics and details on compression techniques. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

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

    [Release] ISTA DeepSeek-V4.1-Flash-1017 GSQ-RCO Coder: a 763B model at 1 bit per parameter

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xlys6k/release_ista_deepseekv41flash1017_gsqrco_coder_a/"> <img alt="[Release] ISTA DeepSeek-V4.1-Flash-1017 GSQ-RCO Coder: a 763B model at 1 bit per parameter" src="https://preview.redd.it/g3qx4abmm7zh1.png?…