deepseek-v4.1-flash

Name: deepseek-v4.1-flash
Brand: DeepSeek
SKU: deepseek/deepseek-v4.1-flash
Price: 0.3000 USD
Availability: InStock

DeepSeek/🇨🇳 China/chat

DeepSeek V4.1 Flash is a 552B parameter Mixture of Experts model built on a new Causal Encoder Decoder architecture that activates only 8B parameters for input and 16B for output, giving frontier level intelligence at a fraction of the cost. It is the smallest model in the new DeepSeek architecture family and the first Flash with native vision and multimodal understanding. V4.1 Flash beats DeepSeek V4 Pro on performance, cost, speed and task completion time and scores 88.1 on CyberGym. Its KV cache is compressed to 890 bytes per token, four times smaller than V4 Flash and over 400 times smaller than V1, cutting the cache hit costs that dominate agent workloads. 1M token context window, 384K max output, thinking and non thinking modes, tool calling, JSON output and prompt caching. Pricing per 1M tokens starts at $0.003 for cache hits, $0.15 input and $0.60 output off peak, with peak rates at double (01:00 to 04:00 and 06:00 to 10:00 UTC, Monday to Friday). Open weights are published on Hugging Face. Ideal for coding agents, long context RAG, high throughput batch processing and multimodal assistants. Replaces deepseek-v4-flash and deepseek-v4-flash-vision-exp, both still accepted as aliases.More

Compare 11 providers All models →

Which id to call

deepseek/deepseek-v4.1-flash

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

Input /1M

$0.30

$0.0060 cached

Output /1M

$1.20

4.0x input

Context

384K output

Paid /1M

$0.03

measured, cache included

Capabilities 5/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-v4.1-flash costs

Provider prices per 1M tokens, updated October 24, 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

$0.30

Output /1M

$1.20

Cache write /1M

Cache read /1M

$0.0060

What a workload costs

100K input + 10K output: $0.0420
1M input + 100K output: $0.42
10M input + 1M output: $4.20

At the rates above, before caching. A cache read costs $0.0060 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.

deepseek/deepseek-v4.1-flash

This exact deployment on DeepSeek, 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="deepseek/deepseek-v4.1-flash",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Live from production

DeepSeek on deepseek-v4.1-flash, measured

What this provider was measured doing on deepseek-v4.1-flash across Requesty traffic.more

Whole-window figures, because that is the grain published per provider. They cover DeepSeek 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

1.15s

median

p95 wait

2.35s

slowest 5%

Output speed

117/s

median tokens

Paid /1M

$0.03

blended, cache included

Cache hit

96.1%

of input tokens

Compare these against the other 10 providers serving deepseek-v4.1-flash.

Reference

Specs and data terms

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

Context window1M tokens

Max output384K tokens

API typechat

AddedSep 2026

Model id

Hugging Facedeepseek-ai/DeepSeek-V4.1-Flash →

Data retentionYes

Used for trainingNo

Served from🇨🇳 China

Privacy policyDeepSeek Privacy Policy →

Released 2026-09-10

Benchmark scores

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

Intelligence Indexreasoning

39.5%

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 DeepSeek

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

deepseek-v4.1-flash-1017

1M ctx/$0.30/1M

deepseek-v4-pro-0813

1M ctx/$1.32/1M

deepseek-reasoner

1M ctx/$0.14/1M

deepseek-chat

1M ctx/$0.14/1M

Reference

deepseek-v4.1-flash questions

How much does deepseek-v4.1-flash cost?

deepseek-v4.1-flash is priced at $0.30 per million input tokens and $1.20 per million output tokens when accessed via Requesty. 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-v4.1-flash?

deepseek-v4.1-flash has a context window of 1M tokens, with a maximum output of 384K tokens per response. That's roughly 1,333 words of input you can fit in a single prompt.

How does deepseek-v4.1-flash perform on benchmarks?

deepseek-v4.1-flash scores 51.9% on SciCode, 39.5% on Intelligence Index, 39.2% on Humanity's Last Exam. 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-v4.1-flash do?

deepseek-v4.1-flash supports vision input, tool calling, extended reasoning, prompt caching, web search. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use deepseek-v4.1-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 "deepseek/deepseek-v4.1-flash". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-v4.1-flash through Requesty?

Yes. deepseek-v4.1-flash runs through Requesty's OpenAI-compatible API, served from DeepSeek. You do not host the model yourself: point base_url at Requesty, set the model to "deepseek/deepseek-v4.1-flash", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call deepseek-v4.1-flash through one endpoint

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

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