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Darwin-398B-JGOS — Darwin V9 Platform · 397B MoE · GPQA 90.9 % · MMLU-Pro 88.08 % (Pure Greedy)

Largest Darwin model · Qwen 3.5 397B base + Darwin V9 FFN transplant · 397B MoE (~17B active) · BF16 GPQA Diamond: 90.9 % — pure greedy, single-sample, NO test-time engine

Overview

Darwin-398B-JGOS is the largest and highest-scoring member of the Darwin family. Built on Qwen 3.5 397B as the base, it transplants the FFN (expert) strengths of multiple high-performance models through the Darwin V9 platform, producing a 397B-parameter Mixture-of-Experts model with ~17B active parameters per token.

It reaches 90.9 % on GPQA Diamond with pure greedy decoding (single sample) — surpassing Darwin-28B-REASON (89.39 %, achieved with the Darwin-DELPHI test-time engine) without using any test-time engine at all. This is the highest GPQA Diamond score in the Darwin family to date.

🧬 Darwin Platform & Research

Darwin is VIDRAFT's measuring-result-driven reasoning model family — approximately 20 official models plus 400+ community derivatives, ranking among the top open models on GPQA.

Darwin V9 platform — evolutionary FFN/expert transplant and trust-weighted merging onto large-scale MoE backbones.
FINAL Bench — VIDRAFT's evaluation framework.
4-layer Pre-AGI roadmap — Darwin → AETHER → PROMETHEUS → HEPHAESTUS.

🧬 Model Lineage

Role	Model	Contribution
Base	`Qwen 3.5 397B (A17B)`	397B Mixture-of-Experts backbone (~17B active).
FFN transplant	Darwin V9 platform (proprietary)	Transplants the FFN (expert) strengths of multiple high-performance models onto the base.
Result	`Darwin-398B-JGOS` (this model)	397B MoE → 90.9 % GPQA Diamond, pure greedy.

The full Darwin V9 merge recipe — source models, weighting, and density — is proprietary and not disclosed (trade secret).

⚙️ Technical Specifications

Component	Value
Architecture	`Qwen3_5MoeForConditionalGeneration` (Qwen 3.5 generation MoE)
Parameters	~397 B total / ~17 B active (Mixture-of-Experts)
Base	Qwen 3.5 397B (A17B)
Precision	bfloat16
License	apache-2.0

🔬 Core Technique — Darwin V9 Platform

Darwin V9 transplants the FFN (expert) strengths of multiple high-performance models onto a Qwen 3.5 397B MoE base, then applies trust-weighted evolutionary merging.

The source models, merge weights, and density schedule are proprietary and constitute a trade secret; they are not published.

🏆 Benchmark — GPQA Diamond (198 questions)

GPQA Diamond is a 198-question, PhD-level graduate science reasoning benchmark.

Model	Engine	Accuracy
Darwin-28B-Opus	Standard	88.89 % (176 / 198)
Darwin-28B-REASON	Darwin-DELPHI (test-time)	89.39 % (177 / 198)
Darwin-398B-JGOS	Greedy (single-sample, no engine)	🥇 90.9 % (180 / 198)

Reproducible evaluation settings:

Greedy decoding (temperature = 0), single sample — no voting / self-consistency / test-time engine
Max generation: 16,384 tokens
Answer options shuffled (seed = 42)
Hardware: NVIDIA B200 (tensor-parallel 2 × pipeline-parallel 3, 6 GPUs)
Inference engine: vLLM, bfloat16, max_model_len = 18432

Darwin-398B-JGOS achieves the family's top GPQA Diamond score using nothing but greedy decoding — no Darwin-DELPHI, no majority voting.

📊 Benchmark — MMLU-Pro (12,032 questions)

MMLU-Pro is a substantially harder successor to MMLU — 10 answer choices (vs 4) and 12,032 reasoning-focused questions across 14 domains.

Darwin-398B-JGOS scores 88.08 % (10,598 / 12,032) with 5-shot Chain-of-Thought and pure greedy decoding (temperature = 0, single sample) — top-tier territory.

Category	Accuracy	Category	Accuracy
Math	95.9 %	Computer Science	88.5 %
Biology	94.7 %	Psychology	87.7 %
Physics	92.6 %	Philosophy	86.6 %
Chemistry	92.3 %	Engineering	85.3 %
Business	92.0 %	Other	83.4 %
Economics	89.3 %	Health	81.8 %
History	80.1 %	Law	75.3 %
		Overall	🥇 88.08 %

Reproducible evaluation settings:

5-shot Chain-of-Thought, greedy decoding (temperature = 0), single sample — no voting / self-consistency / test-time engine
Max generation: 14,000 tokens
Hardware: NVIDIA B200 (tensor-parallel 2 × pipeline-parallel 3, 6 GPUs)
Inference engine: vLLM, bfloat16, max_model_len = 18432

Strongest in STEM — Math 95.9 %, Biology 94.7 %, Physics 92.6 %, Chemistry 92.3 %.

🚀 Usage (vLLM)

vllm serve FINAL-Bench/Darwin-398B-JGOS --tensor-parallel-size 2 --pipeline-parallel-size 3 --dtype bfloat16 --trust-remote-code

🎯 Recommended Use-Cases

Graduate-level STEM reasoning (GPQA / science qualifying exams)
Mathematical problem solving
Complex multi-step chain-of-thought
Code generation and debugging
Bilingual reasoning (strong English + Korean; also Chinese / Japanese)

⚠️ Limitations

397B MoE in bfloat16 requires multi-GPU serving (e.g. B200 ×6 with TP2×PP3).
The 90.9 % figure is a single-run greedy measurement on GPQA Diamond (198 items).
Reasoning traces can be verbose — control with max tokens.

📚 Citation

bibtex

@misc{darwin397b_jgos_2026,
  title  = {Darwin-398B-JGOS: Darwin V9 Platform FFN Transplant on a 397B MoE Base},
  author = {FINAL-Bench / Darwin Research Team},
  year   = {2026},
  howpublished = {https://huggingface.co/FINAL-Bench/Darwin-398B-JGOS},
  note   = {Darwin V9 - 90.9 percent GPQA Diamond (greedy, single-sample)}
}

🔗 Related Darwin Models

Darwin-28B-REASON — RTD + Darwin-DELPHI, GPQA 89.39 %
Darwin-28B-Opus — base, GPQA 88.89 % (HF-official GPQA top tier)
Darwin-36B-Opus — MoE 36B, GPQA 88.4 %
Darwin-27B-Opus — 27B dense, GPQA 86.9 %
Darwin-9B-NEG — 9B Negentropy, GPQA 84.3 %

Darwin-398B-JGOS · Darwin V9 Platform · 90.9 % GPQA Diamond (pure greedy) · FINAL-Bench

FINAL-Bench/Darwin-398B-JGOS

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