DeepSeek V4 Pro (Reasoning, Max Effort)
Description
DeepSeek-V4-Pro-Max is the maximum reasoning effort mode of DeepSeek-V4-Pro, a 1.6T-parameter MoE model with 49B activated parameters and a 1M-token context window. It introduces a hybrid attention architecture combining Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA) for dramatically improved long-context efficiency, requiring only 27% of single-token inference FLOPs and 10% of KV cache compared with DeepSeek-V3.2 at 1M-token context. The model also incorporates Manifold-Constrained Hyper-Connections (mHC) for stable signal propagation and is trained with the Muon optimizer for faster convergence. Pre-trained on more than 32T tokens, V4-Pro-Max significantly advances open-source knowledge capabilities, achieves top-tier performance in coding benchmarks, and bridges the gap with leading closed-source models on reasoning and agentic tasks.
Radar de capacités
Science utilise un proxy de raisonnement lorsque les benchmarks scientifiques dédiés ne sont pas disponibles.
Classements
| Domaine | #Rang | Score | Source |
|---|---|---|---|
| Classement codage | 34 | 79.0 | AA |
| Classement général | 12 | 84.0 | AA |
| Science | 21 | 81.0 | AA |
Scores de benchmarks (LLM Stats)
Agents
Biology
Code
Factuality
Finance
General
Math
Indices d'évaluation AA
Scores par catégorie LLM Stats
Tarification
Vitesse
Classement des Prix par Fournisseur
Classement des Prix par Fournisseur
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