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DeepSeek: DeepSeek V3.2 Speciale

This model is no longer available.

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Model Card

DeepSeek V3.2-Speciale is a high-compute variant designed exclusively for maximum reasoning accuracy, achieving gold-medal performance in IMO 2025, IOI 2025, and ICPC World Finals. It rivals Gemini 3.0 Pro but requires higher token usage and doesn't support tool calling.

Context Window 164K

tokens

Max Output 164K

tokens

Input Cost $0.29

per million tokens

Output Cost $0.43

per million tokens

Release Date Dec 1, 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

Find other DeepSeek models →

Chat

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.

Chat

DeepSeek 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.

Chat

DeepSeek 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

How do I use DeepSeek V3.2 Speciale?

DeepSeek V3.2 Speciale is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for DeepSeek V3.2 Speciale?
DeepSeek V3.2 Speciale costs $0.29 per 1M input tokens and $0.43 per 1M output tokens.
Price per 1M tokens
Input$0.29
Output$0.43
Who created DeepSeek V3.2 Speciale?

DeepSeek V3.2 Speciale was created by DeepSeek and released on Dec 1, 2025.

What is the context window of DeepSeek V3.2 Speciale?

DeepSeek V3.2 Speciale supports a context window of 164K tokens. For reference, that is roughly equivalent to 328 pages of text.

What is the max output length of DeepSeek V3.2 Speciale?

DeepSeek V3.2 Speciale can generate up to 164K tokens in a single response.

How does DeepSeek V3.2 Speciale perform on benchmarks?

DeepSeek V3.2 Speciale scores 14.5 on the Artificial Analysis Intelligence Index, outperforming 55% of tracked models. On math, it scores 96.7 (outperforms 98% of models).

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the DeepSeek V3.2 Speciale 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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