Requesty

deepseek-v4-flash-0731

Runware Inc./🇬🇧 UK/chat

DeepSeek V4 Flash (0731) is DeepSeek's fast, cost-focused frontier model for coding, reasoning, and agent workflows, with thinking and non-thinking modes, a 1M token context window, and up to 384K output tokens. Served via Runware.More

Which id to call

runware/deepseek-v4-flash-0731

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

Input /1M

$0.08

Runware Inc.

Output /1M

$0.15

2.0x input

Context

1.0M

384K output

Added

Jul 2026

chat

Capabilities 0/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-v4-flash-0731 costs

Provider prices per 1M tokens, updated August 30, 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.

Input /1M

$0.08

Output /1M

$0.15

Cache write /1M

-

Cache read /1M

-

What a workload costs

100K input + 10K output
$0.0091
1M input + 100K output
$0.0913
10M input + 1M output
$0.91

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

model=

Which id to call

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

runware/deepseek-v4-flash-0731

This exact deployment on Runware 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="runware/deepseek-v4-flash-0731", 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 output384K tokens
API typechat
AddedJul 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇬🇧 UK

Released 2026-07-31

Benchmark scores

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

Coding Indexcoding
69.1%

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

GPQA Diamondreasoning
90.8%

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

Intelligence Indexreasoning
51.8%

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 Runware Inc.

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

Reference

deepseek-v4-flash-0731 questions

How much does deepseek-v4-flash-0731 cost?

deepseek-v4-flash-0731 is priced at $0.08 per million input tokens and $0.15 per million output tokens when accessed via Requesty. 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-flash-0731?

deepseek-v4-flash-0731 has a context window of 1.0M tokens, with a maximum output of 384K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.

How does deepseek-v4-flash-0731 perform on benchmarks?

deepseek-v4-flash-0731 scores 90.8% on GPQA Diamond, 69.1% on Coding Index, 51.8% 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-flash-0731 do?

deepseek-v4-flash-0731 is a text-generation model you can call through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use deepseek-v4-flash-0731 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 "runware/deepseek-v4-flash-0731". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-v4-flash-0731 through Requesty?

Yes. deepseek-v4-flash-0731 runs through Requesty's OpenAI-compatible API, served from Runware Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "runware/deepseek-v4-flash-0731", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call deepseek-v4-flash-0731 through one endpoint

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

All Runware Inc. models