crazyape777/mir-unconst-affine-5czsc2fc98-r861-vera-odpo

TEXT GENERATIONPricing:Input $0.4 / Cached $0.07 / Output $4Concurrent Unit Cost:3Model Size:35.1BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 19, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The crazyape777/mir-unconst-affine-5czsc2fc98-r861-vera-odpo model is a 35.1 billion parameter Affine SN120 challenger, fine-tuned using offline DPO on Reason-ranked duel pairs. It is specifically optimized for improving 'Reason v4' performance by preferring thoughts that enhance teacher-side reasoning. This model is intended for specialized use in Affine mining submissions and evalsrv Reason v4 duels, rather than general chat applications.

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Model Overview

This model, crazyape777/mir-unconst-affine-5czsc2fc98-r861-vera-odpo, is an Affine SN120 challenger derived from the vera6/affine-5g4yy75zuz-t6 base model. It was trained using an offline DPO (Direct Preference Optimization) method, specifically optimizing for preferences that increase 'Reason v4' scores by committing to a teacher next-action mode.

Key Training Details

  • Methodology: Offline DPO on Reason-ranked duel pairs, distinct from SFT or online GRPO.
  • Optimization Target: Enhanced preference for thoughts that elevate teacher-side Reason scores, utilizing a tempered multi-sample log-mean-exp over k=3 teacher references.
  • Data: Filtered duel preference pairs from dpo_duel_reason.jsonl with specific Soft Mid Mid Soft × SoftCtx filtering.
  • Hyperparameters: Notable settings include LoRA r=32 (MidRank), α=128 (HiAlpha), β=0.1 (MidBeta), and a very low learning rate (lr=5e-7, UltraLoLR).
  • Context Length: Trained with a maximum sequence length of 12288 tokens (SoftCtx).
  • Performance: Achieved a positive margin of +0.003665 against the live king reign36 under wvk=7, leading to its Stage-5 licensing.

Intended Use

This model is not a general chat model. Its primary purpose is for:

  • Affine SN120 miner submissions.
  • Evalsrv Reason v4 duels.

It is highly specialized for its intended optimization target and specific evaluation framework.