DeepSeek V3 0324
DeepSeek V3 0324 is DeepSeek's open-source 671B Mixture-of-Experts language model released December 26, 2024. It achieves 3x the inference throughput of DeepSeek-V2 while matching closed-source models in published benchmark evaluations.
import { streamText } from 'ai'
const result = streamText({ model: 'deepseek/deepseek-v3', prompt: 'Why is the sky blue?'})What To Consider When Choosing a Provider
Zero Data Retention
AI Gateway supports Zero Data Retention for this model via direct gateway requests (BYOK is not included). To configure this, check the documentation.Authentication
AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
DeepSeek V3 0324's context window of 163.8K tokens supports long-document tasks. Plan output token budgets carefully for summarization and report generation, which can produce lengthy completions.
When to Use DeepSeek V3 0324
Best For
General-purpose language tasks:
Summarization, question answering, code generation, and translation where broad capability matters more than specialization
High-throughput production pipelines:
Fast token generation lowers latency and cost compared to slower alternatives of comparable quality (see live metrics on this page)
Long-document workflows:
The context window of 163.8K tokens processes contracts, research papers, or large codebases in a single request
Upgrading from DeepSeek V2:
API backward compatibility minimizes integration work when migrating
Consider Alternatives When
Deep multi-step reasoning:
Use DeepSeek-R1 for extended chain-of-thought and math/code reasoning workloads
Hybrid thinking and tools:
DeepSeek-V3.1 or later adds thinking and tool-use support on top of V3's foundation
Extremely long outputs:
Tasks requiring output beyond the model's per-request limit need a larger-output alternative
Newer V3 capabilities:
Newer V3 iterations may better suit rapidly evolving requirements beyond what V3 offers
Conclusion
DeepSeek V3 0324 set the baseline for open-source language models that compete with closed releases on published benchmarks. It remains DeepSeek's V3 baseline for general-purpose production when you need backward compatibility, open weights, and API parity with earlier DeepSeek integrations.
FAQ
A sparse Mixture-of-Experts (MoE) model with 671B total parameters, activating 37B per forward pass. The context window is 163.8K tokens.
Roughly 3x faster than DeepSeek-V2. Live throughput metrics on this page update based on real traffic.
DeepSeek V3 0324 is a general-purpose chat and instruction model. DeepSeek-R1 is a reasoning specialist trained with reinforcement learning to generate extended chain-of-thought for math, code, and formal reasoning tasks.
Yes. Model weights and the research paper are openly published.
Yes. It maintains backward API compatibility, so upgrading from V2 requires minimal migration effort.
163.8K tokens, validated through Needle In A Haystack evaluations across the full range.