yongchanskii/qwen3-4b-opd-zsre-merge_student_ce_0.02_step_5_traj_len_4096_bf10_ckpt_10000

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 17, 2026Architecture:Transformer Featherless Exclusive Cold

The yongchanskii/qwen3-4b-opd-zsre-merge_student_ce_0.02_step_5_traj_len_4096_bf10_ckpt_10000 is a 4 billion parameter language model with a 32768 token context length. This model is shared by yongchanskii and is part of the Qwen3 family. It is designed for general language understanding and generation tasks, offering a balance between performance and computational efficiency.

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Model Overview

This model, yongchanskii/qwen3-4b-opd-zsre-merge_student_ce_0.02_step_5_traj_len_4096_bf10_ckpt_10000, is a 4 billion parameter language model. It is based on the Qwen3 architecture and features a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text.

Key Characteristics

  • Parameter Count: 4 billion parameters, offering a balance between model complexity and inference speed.
  • Context Length: Supports a 32768 token context window, enabling the model to handle extensive input and generate coherent, long-form responses.
  • Model Family: Part of the Qwen3 series, known for its general-purpose language capabilities.

Potential Use Cases

Given its parameter size and context window, this model is suitable for a variety of natural language processing tasks, including:

  • Text Generation: Creating articles, summaries, creative writing, and conversational responses.
  • Long-form Content Understanding: Processing and extracting information from lengthy documents or dialogues.
  • General-purpose Language Tasks: Applications requiring robust language understanding and generation where a larger context is beneficial.