DeepSeek: DeepSeek Chat
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DeepSeek Chat is the general-purpose conversational alias that points to the latest DeepSeek V3 chat model, a 671B parameter Mixture-of-Experts LLM optimized for everyday conversations, coding assistance, and general tasks. It supports 128K context and provides fast, direct responses without explicit reasoning chains.
Context Window 128K
tokens
Max Output 8K
tokens
Input Cost $0.56
per million tokens
Output Cost $1.68
per million tokens
Input text
modalities
Tool Use Yes
Knowledge Cutoff Jul 2024
Release Date Dec 26, 2024
Code Example
Add AI to your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From DeepSeek
DeepSeek V4 Flash
DeepSeek V4 Flash is a lightweight, efficiency-focused Mixture-of-Experts model from DeepSeek, with 284B total parameters and 13B activated per token. It supports a 1M-token context window and configurable reasoning modes (standard, high, and max thinking effort). Designed as the fast and economical option in the V4 family, Flash delivers reasoning capabilities that closely approach the larger V4 Pro, and performs on par with it on simpler agentic tasks. In its max reasoning mode, it achieves comparable reasoning scores to Pro when given a larger thinking budget. At $0.14/M input and $0.28/M output tokens, it's one of the cheapest frontier-tier models available — well suited for high-throughput workloads like coding assistants, chat systems, and agent pipelines where latency and cost matter most.
ChatDeepSeek V4 Pro
DeepSeek V4 Pro is a 1.6T-parameter Mixture-of-Experts model from DeepSeek with 49B parameters activated per token, supporting a 1M-token context window. It is positioned as the strongest open-weight model currently available. V4 Pro leads all open-source models in math, coding, and STEM reasoning. On LiveCodeBench it scores 93.5, ahead of Gemini 3.1 Pro (91.7) and Claude Opus 4.6 (88.8). Its Codeforces rating of 3206 also tops GPT-5.4 (3168). On agentic tool-use benchmarks like MCPAtlas, it reaches near-parity with Opus 4.6. DeepSeek acknowledges it trails GPT-5.4 and Gemini 3.1 Pro overall by roughly 3–6 months of frontier development. Priced at $1.74/M input and $3.48/M output — a fraction of comparable closed-source models — it's a strong pick for complex reasoning, agentic coding, and knowledge-intensive tasks.
ChatDeepSeek V3.2
DeepSeek V3.2 is the December 2025 flagship model featuring DeepSeek Sparse Attention for efficiency and massive reinforcement learning post-training, achieving GPT-5-level performance. It's the first DeepSeek model to integrate thinking directly into tool-use and excels at agentic AI tasks.
Frequently Asked Questions
You can access DeepSeek Chat by DeepSeek through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add DeepSeek Chat to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.56 |
| Output | $1.68 |
DeepSeek Chat was created by DeepSeek and released on Dec 26, 2024.
DeepSeek Chat supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
DeepSeek Chat can generate up to 8K tokens in a single response.
DeepSeek Chat has a knowledge cutoff date of Jul 2024. This means the model was trained on data available up to that date.
DeepSeek Chat accepts the following input types: text. It produces: text.
Yes, DeepSeek Chat supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the DeepSeek Chat API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
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