DeepSeek V3.1
VerifiedDeepSeek V3.1 processes extensive text contexts as an open-weight LLM.
About DeepSeek V3.1
DeepSeek V3.1 belongs to the family of transformer-based LLMs released with publicly available weights. Its architecture accommodates sequences up to 163840 tokens, allowing it to retain information across very long documents or conversations. The open-weight release enables researchers and developers to run or fine-tune the model locally.
Strengths center on efficient handling of large textual inputs without requiring proprietary APIs. Because parameter count details are not disclosed, users focus on its practical context capacity and accessibility. Typical usage includes document analysis, multi-turn dialogue, and any workflow that benefits from extended context retention.
Capabilities
How DeepSeek V3.1 compares
DeepSeek V3.1 (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · DeepSeek V3.1 ranks #32 of 66
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long Document Analysis
The model processes and reasons over very large inputs using its 163840-token context window for tasks such as summarizing lengthy reports or extracting insights from extended conversations.
Software Development Assistance
It generates, reviews, and debugs code across languages while maintaining logical consistency in complex programming projects.
Mathematical and Logical Problem Solving
The model applies mathematical reasoning and logical inference to solve multi-step problems in research or technical domains.
Strengths & limitations
Strengths
- +Strong coding and technical task performance
- +Effective use of extended context windows
- +Solid reasoning on structured problems
Limitations
- –Text-only modality with no vision support
- –General risk of hallucinations on facts
- –Performance can degrade on extremely long inputs
Cost calculator
Estimate what DeepSeek V3.1 would cost for your usage.
Based on DeepSeek V3.1's $0.21/1M input · $0.79/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "deepseek/deepseek-chat-v3.1",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: deepseek/deepseek-chat-v3.1
Editor's verdict
DeepSeek V3.1 is DeepSeek's open-weight language models with a 164K-token context window.
At $0.79 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to strong coding and technical task performance and effective use of extended context windows.
Frequently asked questions
DeepSeek V3.1 provides a context window of 163840 tokens.
User reviews
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Other DeepSeek models
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