LSW142857/OPSD-PI-Qwen3.5-9B-Strong-Trailing-1024-A6000-Merged-Update16

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 2, 2026Architecture:Transformer Featherless Exclusive Cold

LSW142857/OPSD-PI-Qwen3.5-9B-Strong-Trailing-1024-A6000-Merged-Update16 is a 9 billion parameter Qwen3.5-based causal language model developed by LSW142857. This model is the result of 16 optimizer updates from an OPSD (Optimized Policy Search with Distillation) run, specifically utilizing a 1024-row Strong PI trailing user configuration. It is provided as a fully merged Hugging Face model, requiring no additional adapter or merge steps for deployment.

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Overview

LSW142857/OPSD-PI-Qwen3.5-9B-Strong-Trailing-1024-A6000-Merged-Update16 is a 9 billion parameter Qwen3.5-based model, representing the 16th optimizer update (zero-indexed training iteration 15) from an OPSD (Optimized Policy Search with Distillation) training run. This specific iteration was trained on an 8xRTX A6000 setup using a 1024-row Strong PI trailing_user configuration.

Key Characteristics

  • Fully Merged Model: The repository contains a directly loadable, fully merged Hugging Face model. It integrates the expert-SFT initialization, OPSD main-model LoRA update, MTP LoRA update, and all directly trained full-MTP tensors.
  • No Additional Steps: No adapter or additional merge steps are required for deployment, simplifying integration.
  • Training Details: The PI (Policy Improvement) was teacher-only during training. Users are advised to evaluate the student model without adding PI and to use held-out tasks, not the 1024 training rows, for evaluation.

Integrity and Provenance

  • The model's integrity can be verified using sha256sum -c SHA256SUMS after download, as all 775 output tensors were checked before upload.
  • The merge process prioritizes restoring full trained MTP tensors, then applies main-model and MTP LoRA deltas with a scaling of 2.0.
  • Detailed hashes, source identity, configuration, and finite metrics for this update are available in merge_manifest.json and training_config.json.