Ornstein-3.5-9B-V1.5

Release line

• V1 — initial reasoning fine-tune.
• V1.5 — this release — refined supervised fine-tune on quality-gated reasoning data.
• V2 (in progress) — a much more rigorous post-training run involving reinforcement-learning (verifiable-reward) methods, targeting further gains in hard reasoning.

Benchmarks

Evaluated on the Gestalt Benchmark Suite (GBS, STANDARD-200) — a held-out, contamination-controlled reasoning + coding suite — paired against the base model on identical items with greedy decoding.

V1.5 lifts overall accuracy by +12.5 points, driven by large gains in multi-step and graduate-level scientific reasoning, while preserving coding ability.

Support This Work

I'm a PhD student in visual neuroscience at the University of Toronto who also happens to spend way too much time fine-tuning, merging, and quantizing open-weight models on rented H100s and a local DGX Spark. All training compute is self-funded — balancing GPU costs against a student budget. If my uploads have been useful to you, consider buying a PhD student a coffee. It goes a long way toward keeping these experiments running.

Support on Ko-fi

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Details

• Developed by: DJLougen / GestaltLabs
• Base model: Qwen/Qwen3.5-9B-Base
• Parameters: ~9.65B
• Precision: BF16
• Format: ChatML (conversational)
• License: Apache 2.0

Usage

python
Copy code
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "GestaltLabs/Ornstein-3.5-9B-V1.5"
tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, dtype=torch.bfloat16, device_map="auto")

messages = [{"role": "user", "content": "Derive the variance of a sum of two correlated random variables."}]
inputs = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
out = model.generate(inputs, max_new_tokens=1024)
print(tok.decode(out[0][inputs.shape[-1]:], skip_special_tokens=True))

Intended Use

Reasoning-heavy tasks, AI-research assistance, technical and scientific problem-solving, and general conversation.

License

Apache 2.0 — inherited from the Qwen 3.5 9B base release.