DeepSeek: DeepSeek V4 Flash 0731
deepseek-ai/deepseek-v4-flash-0731
Access DeepSeek V4 Flash 0731 from DeepSeek using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "deepseek-ai/deepseek-v4-flash-0731"
}).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", {
model: "deepseek-ai/deepseek-v4-flash-0731"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="deepseek-ai/deepseek-v4-flash-0731",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "deepseek-ai/deepseek-v4-flash-0731",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
DeepSeek V4 Flash 0731 is the July 31, 2026 dated snapshot of DeepSeek's V4 Flash, a sparse Mixture-of-Experts chat model with a 1,048,576-token context window, hosted here on Together AI's infrastructure.
It keeps the April preview's architecture but was re-post-trained with a pipeline focused on coding, reasoning, agents, and tool use. In DeepSeek's own benchmarks the agentic gains over the preview are large: Terminal Bench 2.1 rises from 61.8 to 82.7, Cybergym from 38.7 to 76.7, and DeepSWE from 7.3 to 54.4. On these vendor-reported numbers it also outscores the V4 Pro preview, though third-party reproduction was not available at release.
Pinning the dated 0731 route locks an application to this exact checkpoint, while a rolling deepseek-v4-flash route can move to newer versions. It fits high-volume coding assistants, chat systems, and agent workflows where cost and latency matter, and this route's 1M-token max output gives more headroom for long agent traces than the original preview route.
Context Window 1M
tokens
Max Output 1M
tokens
Input Cost $0.14
per million tokens
Output Cost $0.28
per million tokens
Input text
modalities
Tool Use Yes
Release Date Jul 31, 2026
Model Playground
Try DeepSeek V4 Flash 0731 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
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 V4 Flash 0731 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 V4 Flash 0731 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 | $0.14 |
| Output | $0.28 |
DeepSeek V4 Flash 0731 was created by DeepSeek and released on Jul 31, 2026.
DeepSeek V4 Flash 0731 supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
DeepSeek V4 Flash 0731 can generate up to 1M tokens in a single response.
DeepSeek V4 Flash 0731 accepts the following input types: text. It produces: text.
Yes, DeepSeek V4 Flash 0731 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 V4 Flash 0731 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.
Get started with Puter.js
Add DeepSeek V4 Flash 0731 to your app without worrying about API keys or setup.
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