DeepSeek
DeepSeek V4.1 Flash
deepseek-v4.1-flash
Total Context
1M
Max Output
384K
Released
N/A
Input$0.2857 / M tokens
Output$1.1429 / M tokens
DeepSeek V3
deepseek-v3DeepSeek V3 is the general-purpose MoE foundation model behind the V3 family, commonly described with 671B total parameters and 37B activated parameters. Its technical reports emphasize MLA, DeepSeekMoE, efficient training, and strong general language and coding performance. In a model catalog, it should be positioned as the balanced DeepSeek chat/coding baseline rather than a specialized reasoning-only model.
Context Window
128K tokens
Maximum Output
16K tokens
Release Date
Dec 26, 2024
Modalities
DeepSeek V3 Pricing
| Input Price | Output Price | Cache Read |
|---|---|---|
| $0.2857/M | $1.1429/M | $0.1143/M |
DeepSeek V3 API Capabilities
Reasoning
Not supported
Tool calling
Not supported
Temperature parameter
Not supported
Attachments
Not supported
Knowledge Base
—
Endpoint Protocols
Completions APIMessages API
DeepSeek V3 Model Highlights
DeepSeek V3 combines an efficient mixture-of-experts architecture with broad language, reasoning and coding capabilities.
Efficient MoE Architecture
Activates 37 billion of 671 billion parameters per token, combining model capacity with more efficient inference.
Broad Problem Solving
Handles knowledge, mathematics, code and natural-language tasks within one general-purpose text model.
Long-Context Processing
A 128K-token context window supports analysis of substantial documents, conversations and source-code collections.
DeepSeek V3 Use Cases
Practical workloads for DeepSeek V3 include software assistance, document analysis and general-purpose knowledge applications.
Software Development
Generates, explains and revises code to help developers implement features and resolve programming problems.
Document Analysis
Reviews long text, extracts important information and produces summaries or structured findings.
Knowledge Assistance
Answers questions, explains concepts and transforms supplied information into clear, task-focused responses.
How to Use DeepSeek V3 via the TokenHub API
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)DeepSeek V3 FAQ
DeepSeek V3: capabilities, use cases, limits, and TokenHub guidance.
What role does DeepSeek V3 play?+
DeepSeek V3 is a DeepSeek model for open-weight general text, code, and reasoning work.
What should I try first with DeepSeek V3?+
Best for general conversation, complex coding and self-hosted deployment, especially when deployment control is the priority.
Why choose DeepSeek V3?+
Key strength: open weights and an efficient Mixture-of-Experts design.
What tradeoff comes with DeepSeek V3?+
It belongs to an older generation and may lack newer capabilities. For the latest capabilities matter, consider DeepSeek V4 Pro.
How should I start in TokenHub?+
Use TokenHub's exact ID; hosted behavior may differ from self-hosting.
Ready to use DeepSeek V3?
Use one API key to access DeepSeek V3 and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Reddit
YouTube