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deepseek-ai/DeepSeek-V3.1:flex

DeepSeek-V3.1 by DeepSeek-AI is a state-of-the-art, hybrid-inference artificial intelligence model that allows users to toggle between fast conversational responses and deep logical reasoning modes within a single architecture.

Tool callingJSON schema
CompareDocs

Specifications

Context window164K tokens
Max outputN/A
API typechat
AddedAug 14, 2026
Model ID
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US
Privacy policyDeepInfra Privacy Policy→

Benchmarks

Released 2025-08-21
GPQA Diamondreasoning
73.5%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
21.4%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Prices updated August 15, 2026
Input / 1M
$0.20
Output / 1M
$0.76
Cache write
N/A
Cache read
N/A
Estimated cost
100K input + 10K output$0.0276
1M input + 100K output$0.28
10M input + 1M output$2.76

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to deepinfra/deepseek-ai/DeepSeek-V3.1:flex.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="deepinfra/deepseek-ai/DeepSeek-V3.1:flex",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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deepseek-ai/DeepSeek-V4-Flash:flex
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Frequently asked questions

How much does deepseek-ai/DeepSeek-V3.1:flex cost?
deepseek-ai/DeepSeek-V3.1:flex is priced at $0.20 per million input tokens and $0.76 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of deepseek-ai/DeepSeek-V3.1:flex?
deepseek-ai/DeepSeek-V3.1:flex has a context window of 164K tokens. That's roughly 218 words of input you can fit in a single prompt.
How does deepseek-ai/DeepSeek-V3.1:flex perform on benchmarks?
deepseek-ai/DeepSeek-V3.1:flex scores 83.3% on MMLU Pro, 73.5% on GPQA Diamond, 57.7% on LiveCodeBench. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can deepseek-ai/DeepSeek-V3.1:flex do?
deepseek-ai/DeepSeek-V3.1:flex supports tool calling, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use deepseek-ai/DeepSeek-V3.1:flex with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/deepseek-ai/DeepSeek-V3.1:flex". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run deepseek-ai/DeepSeek-V3.1:flex through Requesty?
Yes. deepseek-ai/DeepSeek-V3.1:flex runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/deepseek-ai/DeepSeek-V3.1:flex", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access deepseek-ai/DeepSeek-V3.1:flex through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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