deepseek-v4.1-flash-1017:priority
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. Priority service tier at 1.5x standard pricing.MoreLess
Which id to call
deepinfra/deepseek-v4.1-flash-1017:priorityThis exact deployment on DeepInfra, with no routing and no failover. Send it as the model field.
Input /1M
$0.15
$0.30 list
$0.0044 cached
Output /1M
$0.44
$0.90 list
3.0x input
Context
1.0M
tokens
Added
Oct 2026
chat
Capabilities 5/8
Provider rates
What deepseek-v4.1-flash-1017:priority costs
Provider prices per 1M tokens, updated October 19, 2026.moreless
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.
This endpoint is discounted. List is $0.30 per 1M input and $0.90 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
$0.15
$0.30 list
Output /1M
$0.44
$0.90 list
Cache write /1M
-
Cache read /1M
$0.0044
What a workload costs
- 100K input + 10K output
- $0.0191
- 1M input + 100K output
- $0.19
- 10M input + 1M output
- $1.91
At the rates above, before caching. A cache read costs $0.0044 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:priorityThis 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.
123456789101112131415from 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:priority", 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.
Released 2026-10-17
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
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.
Reference
deepseek-v4.1-flash-1017:priority questions
How much does deepseek-v4.1-flash-1017:priority cost?
deepseek-v4.1-flash-1017:priority is priced at $0.15 per million input tokens and $0.44 per million output tokens when accessed via Requesty. Those figures include a 51% discount on this endpoint, off a list rate of $0.30 per million input tokens and $0.90 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:priority?
deepseek-v4.1-flash-1017:priority 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:priority perform on benchmarks?
deepseek-v4.1-flash-1017:priority scores 55.9% on SciCode, 45.1% on Intelligence Index, 43.3% 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:priority do?
deepseek-v4.1-flash-1017:priority 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:priority 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:priority". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run deepseek-v4.1-flash-1017:priority through Requesty?
Yes. deepseek-v4.1-flash-1017:priority 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:priority", 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:priority through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.