GCIRS-Reasoning-1.5B-R1 is a research-grade reasoning model fine-tuned from Qwen2.5-1.5B-Instruct, focused on non-fictional reasoning, factual consistency, and scientific depth. Trained with reinforcement learning using the Big Reasoning Traces dataset from DeepSeek, this model is tailored for complex analytical tasks and scientific rigor in high-stakes or research environments.

Model Files

File Name	Format	Size	Precision	Use Case
`GCIRS-Reasoning-1.5B-R1.F32.gguf`	GGUF	7.11 GB	F32	Highest precision, research use
`GCIRS-Reasoning-1.5B-R1.BF16.gguf`	GGUF	3.56 GB	BF16	High precision, balanced performance
`GCIRS-Reasoning-1.5B-R1.F16.gguf`	GGUF	3.56 GB	F16	High precision, memory efficient
`GCIRS-Reasoning-1.5B-R1.Q8_0.gguf`	GGUF	1.89 GB	Q8_0	Excellent quality, moderate compression
`GCIRS-Reasoning-1.5B-R1.Q6_K.gguf`	GGUF	1.46 GB	Q6_K	Very good quality, good compression
`GCIRS-Reasoning-1.5B-R1.Q5_K_M.gguf`	GGUF	1.29 GB	Q5_K_M	Balanced quality/size (recommended)
`GCIRS-Reasoning-1.5B-R1.Q5_K_S.gguf`	GGUF	1.26 GB	Q5_K_S	Good quality, smaller size
`GCIRS-Reasoning-1.5B-R1.Q4_K_M.gguf`	GGUF	1.12 GB	Q4_K_M	Good balance for most users
`GCIRS-Reasoning-1.5B-R1.Q4_K_S.gguf`	GGUF	1.07 GB	Q4_K_S	Decent quality, compact size
`GCIRS-Reasoning-1.5B-R1.Q3_K_L.gguf`	GGUF	980 MB	Q3_K_L	Lower quality, very compact
`GCIRS-Reasoning-1.5B-R1.Q3_K_M.gguf`	GGUF	924 MB	Q3_K_M	Fast inference, limited quality
`GCIRS-Reasoning-1.5B-R1.Q3_K_S.gguf`	GGUF	861 MB	Q3_K_S	Fastest inference, basic quality
`GCIRS-Reasoning-1.5B-R1.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 or Q6_K for best quality/performance balance
For General Use: Use Q4_K_M or Q4_K_S for good performance
For Resource-Constrained Environments: Use Q3_K_M or Q3_K_L
For Edge Devices: Use 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):

prithivMLmods/GCIRS-Reasoning-1.5B-R1-GGUF

GCIRS-Reasoning-1.5B-R1-GGUF

Model Files

Quick Selection Guide

Quants Usage

prithivMLmods/
GCIRS-Reasoning-1.5B-R1-GGUF