Requesty
Doubleword

deepseek-v4-pro

DeepSeek V4-Pro is DeepSeek's flagship open-weights MoE model, with performance in the same class as Claude Sonnet 4.6 and stronger overall results than GLM-5.1.

Reasoning
Try deepseek-v4-proCompareDocs

Specifications

Context window1.0M tokens
Max output131K tokens
API typechat
AddedJun 23, 2026
Model IDdoubleword/deepseek-v4-pro
Data retentionYes
Used for trainingNo
Provider location🇬🇧 UK, 🌍 Global inference
Privacy policyDoubleword Data Usage Policy→

Benchmarks

Released 2026-04-24
Coding Indexcoding
59.4%

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

GPQA Diamondreasoning
88.8%

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

Intelligence Indexreasoning
44.3%

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

Input / 1M
$1.74
Output / 1M
$3.48
Cache write
N/A
Cache read
N/A
Estimated cost
100K input + 10K output$0.21
1M input + 100K output$2.09
10M input + 1M output$20.88

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 doubleword/deepseek-v4-pro.

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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="doubleword/deepseek-v4-pro",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Other Doubleword models

deepseek-v4-flash:flex
1.0M ctx$0.10/1M
Coding 56
deepseek-v4-flash
1.0M ctx$0.14/1M
Coding 56
deepseek-v4-pro:flex
1.0M ctx$1.31/1M
Coding 59
nvidia-nemotron-3-ultra:flex
262K ctx$0.37/1M
glm-5.2:flex
1.0M ctx$1.05/1M
Coding 69
nvidia-nemotron-3-ultra
262K ctx$0.50/1M

Frequently asked questions

How much does deepseek-v4-pro cost?
deepseek-v4-pro is priced at $1.74 per million input tokens and $3.48 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-v4-pro?
deepseek-v4-pro has a context window of 1.0M tokens, with a maximum output of 131K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
How does deepseek-v4-pro perform on benchmarks?
deepseek-v4-pro scores 96.2% on τ²-Bench, 88.8% on GPQA Diamond, 59.4% on Coding 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 do?
deepseek-v4-pro supports extended reasoning. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use deepseek-v4-pro 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 "doubleword/deepseek-v4-pro". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run deepseek-v4-pro through Requesty?
Yes. deepseek-v4-pro runs through Requesty's OpenAI-compatible API, served from Doubleword. You do not host the model yourself: point base_url at Requesty, set the model to "doubleword/deepseek-v4-pro", and requests are routed to the upstream provider with automatic failover. The same key gives you 400+ other models too.

Access deepseek-v4-pro through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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