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Open-weight model · Text generation

Darwin-397B-JGOS

by FINAL_Bench FINAL-Bench/Darwin-397B-JGOS

Darwin-397B-JGOS is an open-weight model for text generation from FINAL_Bench, released under Apache License 2.0. It has 403.4B parameters and a 262,144-token context. At 16-bit it needs about 968.2 GB of GPU memory, which fits on 4x MI325X from $8.00 an hour; at 4-bit, 242 GB on 1x MI325X from $2.00, at the lowest prices in the SAVRN Index. It draws 22 downloads a month.

Darwin-397B-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…

Parameters403.4B
Context262,144
Weights806.8 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads22

Runs On

What it takes to serve Darwin-397B-JGOS (403.4B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 806.8 GB 968.2 GB 4x MI325X (256 GB)
Vultr
$8.00 4x MI355X $10.36 · 6x MI300X $11.10
8-bit 403.4 GB 484.1 GB 2x MI325X (256 GB)
Vultr
$4.00 2x MI355X $5.18 · 3x MI300X $5.55
4-bit 201.7 GB 242.0 GB 1x MI325X (256 GB)
Vultr
$2.00 1x MI355X $2.59 · 2x MI300X $3.70

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 23, 2026.

Darwin-397B-JGOS on every accelerator the SAVRN Index prices, at every precision

Model Card

By FINAL_Bench, published under apache-2.0, revision 6a950918ee42.

Darwin-397B-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 is VIDRAFT's measuring-result-driven reasoning model family — approximately 20 official models…

Read FINAL_Bench's full model card

Darwin-397B-JGOS — Darwin V9 Platform · 397B MoE · GPQA 90.9 % (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-397B-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-397B-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 | other |


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-397B-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-397B-JGOS achieves the family's top GPQA Diamond score using nothing but greedy decoding — no Darwin-DELPHI, no majority voting.


Usage (vLLM)


vllm serve FINAL-Bench/Darwin-397B-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


@misc{darwin397b_jgos_2026,

  title  = {Darwin-397B-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-397B-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-397B-JGOS · Darwin V9 Platform · 90.9 % GPQA Diamond (pure greedy) · FINAL-Bench

Configuration

Architecture
Qwen3_5MoeForConditionalGeneration
Context length (tokens)
262,144
Layers
60
Hidden size
4,096
Attention heads
32
Key/value heads
2
Head dimension
256
Vocabulary size
248,320
Experts
512
Experts active per token
10
Model type
qwen3_5_moe

Identity and Version

Repository
FINAL-Bench/Darwin-397B-JGOS
Publisher
FINAL_Bench
Task
Text generation
Modality
Text
Library
transformers
Parameters
403.4B parameters
Languages
en, ko, zh, ja
Revision
6a950918ee42b59bed3d82fd89a109e2579639b2
First published
2026-06-14
Last updated
2026-09-20

Files and Weights

105 files, 806.8 GB in total. The weights are 94 files totalling 806.8 GB in safetensors.

Weights94 files · 806.8 GB
Configuration5 files · 308.6 KB
Tokenizer4 files · 22.9 MB
Documentation1 file · 7.0 KB
Repository1 file · 1.6 KB
Every file
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config.jsonConfiguration4.2 KB
generation_config.jsonConfiguration244 B
model.safetensors.index.jsonConfiguration303.4 KB
preprocessor_config.jsonConfiguration390 B
video_preprocessor_config.jsonConfiguration385 B
README.mdDocumentation7.0 KB
.gitattributesRepository1.6 KB
merges.txtTokenizer3.4 MB
tokenizer.jsonTokenizer12.8 MB 5f9e4d4901a9
tokenizer_config.jsonTokenizer16.7 KB
vocab.jsonTokenizer6.7 MB

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
806.8 GB
Download from FINAL_Bench

Released by FINAL_Bench through its official repository on Hugging Face. Read the license.

Built From

  • Derived from Qwen/Qwen3.5-397B-A17B
  • Merged from Qwen/Qwen3.5-397B-A17B

Memory Requirements

PrecisionWeights in memory
As published806.8 GB
16-bit806.8 GB
8-bit403.4 GB
4-bit201.7 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About Darwin-397B-JGOS

How much GPU memory does Darwin-397B-JGOS need?

About 968.2 GB at 16-bit and 242 GB at 4-bit: the weights (403.4B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Darwin-397B-JGOS on?

At 16-bit, 4x MI325X from $8.00 an hour; at 4-bit, 1x MI325X from $2.00 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use Darwin-397B-JGOS commercially?

Yes. Darwin-397B-JGOS is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is Darwin-397B-JGOS's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

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