Enhance the performance of Qwen3-8B by merging powerful reasoning models without compromising the effectiveness of the \no_think tag!

Model Highlights:

  • merge method: arcee_fusion nuslerp della

  • precision: dtype: float32 out_dtype: bfloat16

  • Context length: 40960

Parameter Settings:

Thinking Mode:

Temperature=0.6, TopP=0.95, TopK=20,MinP=0.

Non-Thinking Mode:

Temperature=0.7, TopP=0.8, TopK=20,MinP=0.

Step1: Merge Two Hybrid Models

  • Leverage the advantages of the two hybrid models.
models:
  - model: AXCXEPT/Qwen3-EZO-8B-beta
merge_method: arcee_fusion
base_model: Qwen/Qwen3-8B
dtype: float32
out_dtype: bfloat16
tokenizer_source: base
name: Qwen3-8B-fusion

Step2: Merge High-Performance Reasoning Models with Hybrid Models

  • Maximize the proportion of reasoning models on the premise that the \no_think tag remains effective.
models:
  - model: Qwen3-8B-fusion
    parameters:
      weight: 0.55
  - model: deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
    parameters:
      weight: 0.45
merge_method: nuslerp
tokenizer_source: Qwen/Qwen3-8B
dtype: float32
out_dtype: bfloat16
name: Qwen3-8B-nuslerp1
models:
  - model: Qwen3-8B-fusion
    parameters:
      weight: 0.75
  - model: Kwai-Klear/Klear-Reasoner-8B
    parameters:
      weight: 0.25
merge_method: nuslerp
tokenizer_source: Qwen/Qwen3-8B
dtype: float32
out_dtype: bfloat16
name: Qwen3-8B-nuslerp2

Step3: Unify the Enhanced Hybrid Modes

  • Merge the two models into the base model using the della merging method to make the model more versatile and stable.
  • We use the chat template of Qwen3-8B.
models:
  - model: Qwen3-8B-nuslerp1
    parameters:
      density: 1
      weight: 1
      lambda: 0.9
  - model: Qwen3-8B-nuslerp2
    parameters:
      density: 1
      weight: 1
      lambda: 0.9
merge_method: della
base_model: Qwen/Qwen3-8B-Base
dtype: float32
out_dtype: bfloat16
name: Qwen3-8B-YOYO-V2-Hybrid
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