OpenScienceReasoning-Qwen-e10-GGUF

OpenScienceReasoning-Qwen-e10 is a high-efficiency scientific reasoning model fine-tuned from Qwen3-1.7B using the nvidia/OpenScienceReasoning-2 dataset, encompassing 10,000 curated science and math entries that strengthen analytical problem-solving, chain-of-thought exploration, and code reasoning. The model excels at hybrid symbolic-AI thinking by performing structured logic, scientific derivations, multi-language coding, and generating outputs in formats such as LaTeX, Markdown, JSON, CSV, and YAML, making it ideal for research, education, and technical documentation on mid-range GPUs and edge clusters. Optimized for STEM applications, OpenScienceReasoning-Qwen-e10 delivers robust performance for tutoring, research assistance, and structured data generation while maintaining a lightweight deployment footprint.

Model Files

File Name Quant Type File Size
OpenScienceReasoning-Qwen-e10.BF16.gguf BF16 3.45 GB
OpenScienceReasoning-Qwen-e10.F16.gguf F16 3.45 GB
OpenScienceReasoning-Qwen-e10.F32.gguf F32 6.89 GB
OpenScienceReasoning-Qwen-e10.Q2_K.gguf Q2_K 778 MB
OpenScienceReasoning-Qwen-e10.Q3_K_L.gguf Q3_K_L 1 GB
OpenScienceReasoning-Qwen-e10.Q3_K_M.gguf Q3_K_M 940 MB
OpenScienceReasoning-Qwen-e10.Q3_K_S.gguf Q3_K_S 867 MB
OpenScienceReasoning-Qwen-e10.Q4_0.gguf Q4_0 1.05 GB
OpenScienceReasoning-Qwen-e10.Q4_1.gguf Q4_1 1.14 GB
OpenScienceReasoning-Qwen-e10.Q4_K.gguf Q4_K 1.11 GB
OpenScienceReasoning-Qwen-e10.Q4_K_M.gguf Q4_K_M 1.11 GB
OpenScienceReasoning-Qwen-e10.Q4_K_S.gguf Q4_K_S 1.06 GB
OpenScienceReasoning-Qwen-e10.Q5_0.gguf Q5_0 1.23 GB
OpenScienceReasoning-Qwen-e10.Q5_1.gguf Q5_1 1.32 GB
OpenScienceReasoning-Qwen-e10.Q5_K.gguf Q5_K 1.26 GB
OpenScienceReasoning-Qwen-e10.Q5_K_M.gguf Q5_K_M 1.26 GB
OpenScienceReasoning-Qwen-e10.Q5_K_S.gguf Q5_K_S 1.23 GB
OpenScienceReasoning-Qwen-e10.Q6_K.gguf Q6_K 1.42 GB
OpenScienceReasoning-Qwen-e10.Q8_0.gguf Q8_0 1.83 GB

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

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GGUF
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1.72B params
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qwen3
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