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Model details

DeepSeek V3 0324

DeepSeek V3 0324 is a large-scale mixture-of-experts model built to provide significant advancements in logical reasoning and technical execution. By increasing its parameter count to 685 billion, the model is engineered to handle complex, multi-step tasks with greater nuance and precision. It is specifically optimized for demanding applications that require high-quality code generation, front-end web development, and sophisticated mathematical problem-solving. With a substantial context window, the model is well-suited for long-form document analysis and retrieval-augmented workflows, offering a robust foundation for developers who need reliable performance in logic-heavy environments.

Building upon the lineage of its predecessor, this iteration delivers measurable gains across key benchmarks, including notable improvements in MMLU-Pro, GPQA, and AIME scores. The model has been refined to offer superior function-calling accuracy and enhanced Chinese writing proficiency, making it a versatile tool for global development teams. Its design prioritizes practical utility, allowing users to achieve high-level reasoning results while maintaining compatibility with existing API workflows. As an open-weights release, it provides a flexible and powerful option for enterprises looking to integrate advanced reasoning capabilities into their own AI-powered systems.

NovitaAIdeepseek/deepseek-v3-0324deepseek

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Provider
NovitaAI
Model key
deepseek/deepseek-v3-0324
Release date
Mar 25, 2025
Last updated
Mar 25, 2025
Knowledge cutoff
2024-07
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.27
Output token cost
$1.12

Limits

Output tokens
163,840 tokens
Context window
163,840 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about DeepSeek V3 0324

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CoverageAnalysis

RunPod's technical analysis (August 25, 2026) frames DeepSeek V3.1's changes against the V3-0324 baseline, explicitly naming that exact version multiple times. The analysis describes V3-0324 as demonstrating notable improvements over its predecessor DeepSeek-V3 while maintaining the same underlying model structure as t The article is a third-party retrospective where V3-0324 serves as the reference baseline for V3.1's architectural evolution rather than as the primary news subject. Published by RunPod — another serving provider — it discusses V3-0324's properties to contextualize V3.1's hybrid reasoning design, training-based behavio

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