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Nemotron, Nemo, and Qwen models compared across benchmarks

By PulseAugur Editorial · [1 sources] ·

A comparison of several large language models, including Nemotron 3.5 Bolt, Nemo 3.5 Super, and Qwen 3.8 (both 27B and FN variants), highlights their performance across various benchmarks. The Qwen 3.8 FN model notably excels in benchmarks like DeepSWE and LiveCodeBench v6, while Nemo 3.5 Super shows strong performance in others. The data, pulled from model cards, suggests varying strengths among these models depending on the specific task. AI

IMPACT Provides comparative data on the capabilities of different open-source models for developers.

RANK_REASON Comparison of model performance on benchmarks. [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 →

Nemotron, Nemo, and Qwen models compared across benchmarks

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3 / 100
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Tool
Comparison of model performance on benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]
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model release
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 Nederlands(NL) · /u/Nota_ReAlperson ·

    Nemotron 3.5 Bolt vs Nemo 3.5 Super vs Qwen 3.8 27B/FN

    <!-- SC_OFF --><div class="md"><p>Pulling the benchmarks from the model cards.</p> <p>Benchmarks might not be exactly comparable, as some models do not specify the version.</p> <table><thead> <tr> <th align="left">Benchmark</th> <th align="left">3.5 Bolt</th> <th align="left">3.5…

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