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deepseek-v4-pro-0813

DeepInfra Inc./🇺🇸 US/chat10% off

DeepSeek-V4-Pro-0813 is the official release of DeepSeek-V4-Pro, superseding the preview version, with greatly enhanced agentic capabilities and performance improvements that are especially pronounced in production environments. It is built on the DeepSeek-V4-Pro (Preview) model structure, with a DSpark speculative decoding module attached.More

Which id to call

deepinfra/deepseek-v4-pro-0813

This exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.

Input /1M

$1.17

$1.30 list

$0.09 cached

Output /1M

$2.34

$2.60 list

2.0x input

Context

1.0M

1.0M output

Added

Aug 2026

chat

Capabilities 4/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-v4-pro-0813 costs

Provider prices per 1M tokens, updated August 20, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

10% off

This endpoint is discounted. List is $1.30 per 1M input and $2.60 per 1M output, and the rates below are what you pay. The discount applies to every request on this endpoint, with nothing to claim or enter.

Input /1M

$1.17

$1.30 list

Output /1M

$2.34

$2.60 list

Cache write /1M

-

Cache read /1M

$0.09

What a workload costs

100K input + 10K output
$0.14
1M input + 100K output
$1.40
10M input + 1M output
$14.04

At the rates above, before caching. A cache read costs $0.09 per 1M, so repeated context lands under these figures.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

deepinfra/deepseek-v4-pro-0813

This exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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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-v4-pro-0813", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window1.0M tokens
Max output1.0M tokens
API typechat
AddedAug 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇺🇸 US

Released 2026-08-13

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

Coding Indexcoding
68.8%

Artificial Analysis Coding Index: a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
92.8%

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

Intelligence Indexreasoning
53.2%

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

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

Same provider

More from DeepInfra Inc.

Newest first, on the same provider and the same key.

Reference

deepseek-v4-pro-0813 questions

How much does deepseek-v4-pro-0813 cost?

deepseek-v4-pro-0813 is priced at $1.17 per million input tokens and $2.34 per million output tokens when accessed via Requesty. Those figures include a 10% discount on this endpoint, off a list rate of $1.30 per million input tokens and $2.60 per million output tokens. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of deepseek-v4-pro-0813?

deepseek-v4-pro-0813 has a context window of 1.0M tokens, with a maximum output of 1.0M tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.

How does deepseek-v4-pro-0813 perform on benchmarks?

deepseek-v4-pro-0813 scores 92.8% on GPQA Diamond, 68.8% on Coding Index, 53.2% on Intelligence Index. 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-v4-pro-0813 do?

deepseek-v4-pro-0813 supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use deepseek-v4-pro-0813 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-v4-pro-0813". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-v4-pro-0813 through Requesty?

Yes. deepseek-v4-pro-0813 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-v4-pro-0813", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call deepseek-v4-pro-0813 through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.