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Ministral3: cascade pruning and pretrained distillation

Contribution grade

Compact language-model training · Human-designed research method or resource

Reference score55,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Derived progressively smaller dense models by pruning and continued logit distillation through an intermediate teacher cascade, then post-trained visual instruction and reasoning variants.

Scientific scope

Derived progressively smaller dense models by pruning and continued logit distillation through an intermediate teacher cascade, then post-trained visual instruction and reasoning variants. Inherits pruning, knowledge distillation, GRPO and online DPO. Savings relative to child training from scratch exclude inherited parent-training cost. One family, not nine inventions. December2025 model release and January2026 method report are distinct dates.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits pruning, knowledge distillation, GRPO and online DPO. Savings relative to child training from scratch exclude inherited parent-training cost. One family, not nine inventions. December2025 model release and January2026 method report are distinct dates.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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