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deepseek-ai/DeepSeek-V4-Flash

DeepInfra Inc./🇺🇸 US/chat10% off

DeepSeek V4 Flash is an efficiency-focused MoE model with 284B total parameters (13B active) and a 1M-token context window. It's tuned for fast inference and high-throughput use cases while still holding up on reasoning and coding tasks.More

Which id to call

deepinfra/deepseek-ai/DeepSeek-V4-Flash

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

Input /1M

$0.09

$0.10 list

$0.02 cached

Output /1M

$0.18

$0.20 list

2.0x input

Context

1.0M

tokens

Paid /1M

$0.04

measured, cache included

Capabilities 4/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-ai/DeepSeek-V4-Flash costs

Provider prices per 1M tokens, updated August 25, 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 $0.10 per 1M input and $0.20 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

$0.09

$0.10 list

Output /1M

$0.18

$0.20 list

Cache write /1M

-

Cache read /1M

$0.02

What a workload costs

100K input + 10K output
$0.0108
1M input + 100K output
$0.11
10M input + 1M output
$1.08

At the rates above, before caching. A cache read costs $0.02 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-ai/DeepSeek-V4-Flash

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-ai/DeepSeek-V4-Flash", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Live from production

DeepInfra Inc. on deepseek-ai/DeepSeek-V4-Flash, measured

What this provider was measured doing on deepseek-ai/DeepSeek-V4-Flash across Requesty traffic.more

Whole-window figures, because that is the grain published per provider. They cover DeepInfra Inc. serving this model in every region it serves it from, so a region-pinned deployment shares them with its siblings. A figure is absent where no qualifying sample exists.

First token

1.95s

median

p95 wait

6.31s

slowest 5%

Output speed

43/s

median tokens

Paid /1M

$0.04

blended, cache included

Cache hit

81.2%

of input tokens

Compare these against the other 4 providers serving deepseek-v4-flash.

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 output-
API typechat
AddedApr 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇺🇸 US

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 DeepInfra Inc.

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

Reference

deepseek-ai/DeepSeek-V4-Flash questions

How much does deepseek-ai/DeepSeek-V4-Flash cost?

deepseek-ai/DeepSeek-V4-Flash is priced at $0.09 per million input tokens and $0.18 per million output tokens when accessed via Requesty. Those figures include a 10% discount on this endpoint, off a list rate of $0.10 per million input tokens and $0.20 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-ai/DeepSeek-V4-Flash?

deepseek-ai/DeepSeek-V4-Flash has a context window of 1.0M tokens. That's roughly 1,398 words of input you can fit in a single prompt.

How does deepseek-ai/DeepSeek-V4-Flash perform on benchmarks?

deepseek-ai/DeepSeek-V4-Flash 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-ai/DeepSeek-V4-Flash do?

deepseek-ai/DeepSeek-V4-Flash 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-ai/DeepSeek-V4-Flash 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-V4-Flash". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-ai/DeepSeek-V4-Flash through Requesty?

Yes. deepseek-ai/DeepSeek-V4-Flash 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-V4-Flash", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call deepseek-ai/DeepSeek-V4-Flash through one endpoint

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