DeepSeek: DeepSeek Reasoner
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Model Card
DeepSeek Reasoner is the API alias for DeepSeek's reasoning models (R1 series), which use chain-of-thought reasoning to solve complex math, coding, and logic problems. It displays its thinking process before arriving at answers and achieves performance comparable to OpenAI o1.
Context Window 128K
tokens
Max Output 64K
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 Jan 20, 2025
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 V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 is DeepSeek's October 17, 2026 update to its V4.1 Flash chat model. DeepSeek calls it a minor update that finishes tasks faster and with shorter outputs, with unchanged API usage and pricing. In DeepSeek's own tests it improved on the September V4.1 Flash release on DeepSWE v1.1 (77.0 vs 74.2), Terminal-Bench 4.0 (42.3 vs 31.2), HLE without tools (42.6 vs 36.8), and ProgramBench (29.1 vs 20.3). It accepts text and image input, supports tool calling and a reasoning effort parameter, and has a context window of about 1M tokens. DeepSeek recommends its Harness agent framework at version 0.2.1-rc.1 or later. At $0.30/M input and $1.20/M output tokens on OpenRouter, it suits coding agents, tool-calling pipelines, and long-context workloads.
ChatDeepSeek V4.1 Flash
DeepSeek V4.1 Flash is DeepSeek's fast, low-cost chat model, a 552B-parameter Mixture-of-Experts system using a new causal encoder-decoder design that activates 8B parameters while reading a prompt and 16B while generating a response. It succeeds DeepSeek V4 Flash, keeping a 1,000,000-token context window and adding a continuously adjustable reasoning effort setting (1-100). DeepSeek reports it beating the larger V4 Pro on performance, cost, speed, and total runtime. In DeepSeek's own tests it scored 90.6 on Terminal-Bench 2.1, ahead of Claude Opus 5 (89.1) and GPT-5.6 Sol (88.8), 88.1 on CyberGym versus 84.5 for GPT-5.6 Sol and GLM 5.3, and 74.2 on DeepSWE v1.1 versus 74.0 for Claude Opus 5. It supports tool calling, and DeepSeek says its KV cache footprint is about a quarter of V4 Flash's for cheaper long-context serving. At $0.11/M input and $0.45/M output tokens, it fits high-throughput coding agents, tool-calling pipelines, and long-context workloads.
ChatDeepSeek V4 Flash Vision Experimental
DeepSeek V4 Flash Vision Experimental is an experimental multimodal version of DeepSeek's V4 Flash model, released by DeepSeek in August 2026. It is a sparse Mixture-of-Experts model with 284B total parameters and 13B activated per token, and it accepts images (JPEG, PNG, GIF, WebP) alongside text through the same API used for V4 Flash. DeepSeek reports that it matches V4 Flash on text tasks including agentic reasoning and world knowledge, while adding image understanding for document and chart parsing, visual question answering, and agent workflows that interleave text and images. On multimodal agent benchmarks, DeepSeek's own numbers show gains over the text-only V4 Flash, with Terminal Bench 2.1 rising from 82.7 to 83.9, ApexBench from 26.2 to 36.5, and Agents' Last Exam from 25.2 to 27.3, approaching Anthropic's Opus 4.8 (85.0 on Terminal Bench 2.1). On NL2Repo it trails Opus 4.8, 57.7 versus 69.7.
Frequently Asked Questions
DeepSeek Reasoner is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.56 |
| Output | $1.68 |
DeepSeek Reasoner was created by DeepSeek and released on Jan 20, 2025.
DeepSeek Reasoner supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
DeepSeek Reasoner can generate up to 64K tokens in a single response.
DeepSeek Reasoner has a knowledge cutoff date of Jul 2024. This means the model was trained on data available up to that date.
DeepSeek Reasoner accepts the following input types: text. It produces: text.
Yes, DeepSeek Reasoner 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 Reasoner 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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