prithivMLmods/Research-Reasoning-Qwen-F32-GGUF
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Research-Reasoning-Qwen-F32…/README.md
ModelHub XC 484778f7ad 初始化项目，由ModelHub XC社区提供模型 
Model: prithivMLmods/Research-Reasoning-Qwen-F32-GGUF
Source: Original Platform
2026-10-15 20:52:13 +08:00

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license, language, base_model, pipeline_tag, library_name, tags
license language base_model pipeline_tag library_name tags
apache-2.0
en
nvidia/Nemotron-Research-Reasoning-Qwen-1.5B
text-generation transformers
text-generation-inference
code
reasoning
research

Nemotron-Research-Reasoning-Qwen-1.5B-GGUF

Nemotron-Research-Reasoning-Qwen-1.5B is the world’s leading 1.5B open-weight model for complex reasoning tasks such as mathematical problems, coding challenges, scientific questions, and logic puzzles. It is trained using the ProRL algorithm on a diverse and comprehensive set of datasets. Our model has achieved impressive results, outperforming Deepseek’s 1.5B model by a large margin on a broad range of tasks, including math, coding, and GPQA.

Model Files

File Name Format Size Precision Use Case
Nemotron-Research-Reasoning-Qwen-1.5B.F32.gguf GGUF 7.11 GB F32 Highest precision, research use
Nemotron-Research-Reasoning-Qwen-1.5B.BF16.gguf GGUF 3.56 GB BF16 High precision, balanced performance
Nemotron-Research-Reasoning-Qwen-1.5B.F16.gguf GGUF 3.56 GB F16 High precision, memory efficient
Nemotron-Research-Reasoning-Qwen-1.5B.Q8_0.gguf GGUF 1.89 GB Q8_0 Good quality, moderate compression
Nemotron-Research-Reasoning-Qwen-1.5B.Q5_K_M.gguf GGUF 1.29 GB Q5_K_M Balanced quality/size (recommended)
Nemotron-Research-Reasoning-Qwen-1.5B.Q5_K_S.gguf GGUF 1.26 GB Q5_K_S Good quality, smaller size
Nemotron-Research-Reasoning-Qwen-1.5B.Q4_K_M.gguf GGUF 1.12 GB Q4_K_M Good balance for most users
Nemotron-Research-Reasoning-Qwen-1.5B.Q4_K_S.gguf GGUF 1.07 GB Q4_K_S Decent quality, compact size
Nemotron-Research-Reasoning-Qwen-1.5B.Q3_K_L.gguf GGUF 980 MB Q3_K_L Lower quality, very compact
Nemotron-Research-Reasoning-Qwen-1.5B.Q3_K_M.gguf GGUF 924 MB Q3_K_M Fast inference, limited quality
Nemotron-Research-Reasoning-Qwen-1.5B.Q3_K_S.gguf GGUF 861 MB Q3_K_S Fastest inference, basic quality
Nemotron-Research-Reasoning-Qwen-1.5B.Q2_K.gguf GGUF 753 MB Q2_K Minimal size, experimental use

Quick Selection Guide

  • For Research/Development: Use F32 or BF16 for maximum accuracy
  • For Production (Recommended): Use Q5_K_M for best quality/performance balance
  • For Resource-Constrained Environments: Use Q4_K_M or Q4_K_S
  • For Edge Devices: Use Q3_K_M or Q2_K for minimal footprint

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png