Pradheep1647/q0-gsm8k-1_5b-mopd

TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 13, 2026Architecture:Transformer Featherless Exclusive Cold

Pradheep1647/q0-gsm8k-1_5b-mopd is a 1.5 billion parameter language model based on Qwen2.5-1.5B-Instruct, fine-tuned using Multi-Teacher On-Policy Distillation (MOPD). This model is specifically optimized for mathematical reasoning tasks, demonstrating strong performance on the GSM8K benchmark with a pass@8 of 84.77%. It is designed for efficient deployment, with its LoRA adapter merged into the 16-bit base weights.

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Model Overview

Pradheep1647/q0-gsm8k-1_5b-mopd is a 1.5 billion parameter model derived from Qwen/Qwen2.5-1.5B-Instruct. Its primary distinction lies in its fine-tuning methodology: Multi-Teacher On-Policy Distillation (MOPD). This technique involved distilling knowledge from a q0 cyclic-trajectory GRPO mixture, utilizing two top-performing q0 snapshots (cycle02 + cycle03) as teachers.

Key Capabilities and Performance

This model is specifically engineered for mathematical reasoning. Its performance on relevant benchmarks highlights this specialization:

  • GSM8K Validation (256-example slice):
    • Pass@1: 49.07%
    • Pass@4: 76.29%
    • Pass@8: 84.77%
  • MATH-500 Test (500 problems):
    • Pass@1: 16.40%
    • Pass@4: 35.00%

Technical Details

The model was trained using 4-bit QLoRA (NF4, r=8, alpha=16) and the LoRA adapter has been merged into the 16-bit base weights, making it directly deployable. This training was conducted on an RTX 4060 Laptop (8 GB).