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QuickSilver Pro benchmarks LLMs for coding and extraction tasks

By PulseAugur Editorial · [1 sources] ·

QuickSilver Pro has released a guide comparing several large language models for various job roles and budgets. The guide details benchmark results from 17 tasks, Claude Code runs, and tests on OpenCode and Crush, all conducted on October 20, 2026. For coding tasks, Claude Sonnet 5.5 is recommended for its performance and cost-effectiveness, while Claude Haiku 5.5 is suggested for cheaper, simpler tasks. The guide also evaluates open models like Kimi K3, GLM 5.3, and DeepSeek V4 Pro for coding, and highlights Haiku 5.5 for extraction tasks due to its accuracy and low cost. AI

IMPACT Provides practical guidance for users on selecting and optimizing LLM usage for specific tasks and budgets on the QuickSilver Pro platform.

RANK_REASON The article is a guide to using existing LLMs on a specific platform, not a release of a new model or technology.

Read on dev.to — LLM tag →

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

QuickSilver Pro benchmarks LLMs for coding and extraction tasks

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22 / 100
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Tool
The article is a guide to using existing LLMs on a specific platform, not a release of a new model or technology.
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product, model release
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · xiun xiao ·

    Which model should you use on QuickSilver Pro? A guide by job and budget

    <p><em>Originally published on the <a href="https://quicksilverpro.io/blog/which-llm-to-use/?utm_source=devto&amp;utm_medium=referral&amp;utm_campaign=which-llm" rel="noopener noreferrer">QuickSilver Pro blog</a>.</em></p> <p>QuickSilver Pro has Claude Sonnet 5.5, Claude Haiku 5.…

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