Ornith-1.0-35B-GGUF vs Ornith-1.0-9B-GGUF
Compare benchmark score, parameter size, model family, and practical tradeoffs between these two Hugging Face LLM models.
deepreinforce-ai/Ornith-1.0-9B-GGUF
Metric Comparison
The table keeps the core specs visible for quick evaluation.
| Metric | Ornith-1.0-35B-GGUF | Ornith-1.0-9B-GGUF | Difference |
|---|---|---|---|
| Benchmark average score | 98.50 | 98.50 | Equal |
| Parameter size | 35.00B | 9.00B | +26B (+288.9%) |
| Model family | Other | Other | Match |
Performance Verdict
Based on the available leaderboard data, deepreinforce-ai/Ornith-1.0-35B-GGUF has the stronger overall benchmark score.
- deepreinforce-ai/Ornith-1.0-35B-GGUF is the stronger performer, scoring 98.50 on average compared to deepreinforce-ai/Ornith-1.0-9B-GGUF's 98.50.
- deepreinforce-ai/Ornith-1.0-35B-GGUF is 288.9% larger in parameter capacity than deepreinforce-ai/Ornith-1.0-9B-GGUF (35.00B vs 9.00B parameters).
- deepreinforce-ai/Ornith-1.0-35B-GGUF has more parameter capacity, which may contribute to its stronger benchmark score.
Integration & Implementation Guide
Learn how to load and execute these models programmatically in Python using Hugging Face's transformers library.
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("deepreinforce-ai/Ornith-1.0-35B-GGUF")
model = AutoModelForCausalLM.from_pretrained("deepreinforce-ai/Ornith-1.0-35B-GGUF")
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("deepreinforce-ai/Ornith-1.0-9B-GGUF")
model = AutoModelForCausalLM.from_pretrained("deepreinforce-ai/Ornith-1.0-9B-GGUF")
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