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deepseek-v4.1-flash-1017

DeepInfra/🇺🇸 US/chat51% off

DeepSeek V4.1 Flash 1017 is a minor update to DeepSeek V4.1 Flash with substantial gains in reasoning, coding, agentic tasks and visual benchmarks, plus shorter outputs and faster task completion. 552B parameter Mixture of Experts with native vision, 1M token context, thinking and non thinking modes, tool calling, structured JSON output and prompt caching. Served on DeepInfra in FP8 with zero retention. Open weights on Hugging Face.More
Compare 4 providersAll models →

Which id to call

deepinfra/deepseek-v4.1-flash-1017

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

Input /1M

$0.10

$0.20 list

$0.0029 cached

Output /1M

$0.29

$0.60 list

3.0x input

Context

1.0M

tokens

Added

Oct 2026

chat

Capabilities 5/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-v4.1-flash-1017 costs

Provider prices per 1M tokens, updated October 17, 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.

51% off

This endpoint is discounted. List is $0.20 per 1M input and $0.60 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

$0.10

$0.20 list

Output /1M

$0.29

$0.60 list

Cache write /1M

-

Cache read /1M

$0.0029

What a workload costs

100K input + 10K output
$0.0127
1M input + 100K output
$0.13
10M input + 1M output
$1.27

At the rates above, before caching. A cache read costs $0.0029 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-v4.1-flash-1017

This exact deployment on DeepInfra, 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-v4.1-flash-1017",
    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 output-
API typechat
AddedOct 2026
Model id
Hugging Facedeepseek-ai/DeepSeek-V4.1-Flash-1017 →
Data retentionNone
Used for trainingNo
Served from🇺🇸 US
Privacy policyDeepInfra 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 DeepInfra

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

step-5-preview

1.0M ctx/$1.00/1M

mimo-v2.6-flash

1.0M ctx/$0.14/1M

mimo-v2.6-pro

1.0M ctx/$0.43/1M

deepseek-v4.1-flash

1.0M ctx/$0.20/1M

deepseek-v4.1-flash:flex

1.0M ctx/$0.16/1M

glm-5.3-flash

1.0M ctx/$0.15/1M

Reference

deepseek-v4.1-flash-1017 questions

How much does deepseek-v4.1-flash-1017 cost?

deepseek-v4.1-flash-1017 is priced at $0.10 per million input tokens and $0.29 per million output tokens when accessed via Requesty. Those figures include a 51% discount on this endpoint, off a list rate of $0.20 per million input tokens and $0.60 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-v4.1-flash-1017?

deepseek-v4.1-flash-1017 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-v4.1-flash-1017 perform on benchmarks?

deepseek-v4.1-flash-1017 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-1017 do?

deepseek-v4.1-flash-1017 supports vision input, 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-v4.1-flash-1017 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-v4.1-flash-1017". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-v4.1-flash-1017 through Requesty?

Yes. deepseek-v4.1-flash-1017 runs through Requesty's OpenAI-compatible API, served from DeepInfra. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/deepseek-v4.1-flash-1017", 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-1017 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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