GCIRS-Reasoning-1.5B-R1-GGUF

GCIRS-Reasoning-1.5B-R1-GGUF

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

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):