opendunes

DeepSeek V4.1 Flash 1017

New

by DeepSeekReleased 17 October 2026

#10 for 3D scenesThis is the 17 October 2026 snapshot of V4.1 Flash, the image-and-text model DeepSeek serves under its current Flash name. It keeps about a thousand pages in mind, replies up to about 393 pages, thinks first, uses your connected tools and fills in the exact form you give it. Pick it for agents and coding work that include screenshots, and when you want the newest Flash. The earlier DeepSeek V4.1 Flash is the snapshot before this one; V4 Pro 0813 is the larger model for hard reasoning.

TakesTextImages
GivesText

What it costs

You pay for what each request uses. No subscription, no minimum.

≈ 0,15 DA per message3 000 DA buys about 20 000 messages

One message, the ordinary use

1 000 tokens sent× 49,93 DA per 1M0,050 DA
500 tokens back× 199,70 DA per 1M0,10 DA
Total≈ 0,15 DA

Every rate

Meter↑ you send↓ comes back
Text tokens49,93 DA199,70 DA
Cached tokens read1,00 DA

per 1M tokens

Reasoned review of a long contract with tool calls to check clauses against your policy notes≈ 8,99 DA
Daily re-asking of the same large prompt with only the date and figures changed, billed at the cached rate≈ 25,36 DA
Summarise a full code repository with images and docs included, answered in one pass≈ 46,53 DA
When you pay
After the answer, from your balance. Nothing is held.
Why it varies
A longer question or a longer answer costs more.
After each one
The exact charge shows on the request.
DepositDeposits from 50 DA, with Edahabia or CIB.

Where your request runs

40 companies run this model. OpenDunes sends each request to one of them, picked by price and speed. If it fails, the next one takes it. DA per 1M tokens: ↑ what you send · ↓ what comes back.

Relace…
↑ Sent, per 1M
2,00 DA
↓ Back, per 1M
166,42 DA
Cache read
1,66 DA
Latency
…
Throughput
…
OpenInference…
↑ Sent, per 1M
5,82 DA
↓ Back, per 1M
199,70 DA
Cache read
1,33 DA
Latency
…
Throughput
…
MorphUnited States…
↑ Sent, per 1M
7,32 DA
↓ Back, per 1M
133,13 DA
Cache read
1,33 DA
Latency
…
Throughput
…
WaferUnited States…
↑ Sent, per 1M
12,65 DA
↓ Back, per 1M
166,42 DA
Cache read
3,33 DA
Latency
…
Throughput
…
Particle AIUnited States…
↑ Sent, per 1M
16,64 DA
↓ Back, per 1M
166,42 DA
Cache read
1,00 DA
Latency
…
Throughput
…
Wafer…
↑ Sent, per 1M
21,97 DA
↓ Back, per 1M
166,42 DA
Cache read
2,16 DA
Latency
…
Throughput
…
AlibabaAsia…
↑ Sent, per 1M
24,96 DA
↓ Back, per 1M
99,85 DA
Cache read
2,50 DA
Latency
…
Throughput
…
InferenceNetUnited States…
↑ Sent, per 1M
26,63 DA
↓ Back, per 1M
183,06 DA
Cache read
2,66 DA
Latency
…
Throughput
…
InferenceNet…
↑ Sent, per 1M
26,63 DA
↓ Back, per 1M
183,06 DA
Cache read
2,66 DA
Latency
…
Throughput
…
Baidu65 % off…
↑ Sent, per 1M
Was 93,1832,52 DA
↓ Back, per 1M
Was 376,10131,26 DA
Cache read
Was 2,010,70 DA
Latency
…
Throughput
…
DeepInfra51 % offUnited States…
↑ Sent, per 1M
Was 66,5732,62 DA
↓ Back, per 1M
Was 199,6997,85 DA
Cache read
Was 2,000,98 DA
Latency
…
Throughput
…
Cloudflare…
↑ Sent, per 1M
33,28 DA
↓ Back, per 1M
199,70 DA
Cache read
1,00 DA
Latency
…
Throughput
…
Sail ResearchUnited States…
↑ Sent, per 1M
33,62 DA
↓ Back, per 1M
49,93 DA
Cache read
2,24 DA
Latency
…
Throughput
…
PrimeIntellect…
↑ Sent, per 1M
36,35 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
StreamLake63 % off…
↑ Sent, per 1M
Was 99,8436,94 DA
↓ Back, per 1M
Was 399,41147,78 DA
Cache read
Was 2,000,74 DA
Latency
…
Throughput
…
Decart18 % offUnited States…
↑ Sent, per 1M
Was 49,9340,94 DA
↓ Back, per 1M
Was 199,71163,76 DA
Cache read
Was 1,000,82 DA
Latency
…
Throughput
…
StepFun55 % off…
↑ Sent, per 1M
Was 99,8444,93 DA
↓ Back, per 1M
Was 399,40179,73 DA
Cache read
Was 2,000,90 DA
Latency
…
Throughput
…
DeepSeek…
↑ Sent, per 1M
49,93 DA
↓ Back, per 1M
199,70 DA
Cache read
1,00 DA
Latency
…
Throughput
…
Makora…
↑ Sent, per 1M
49,93 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Sail Research…
↑ Sent, per 1M
50,42 DA
↓ Back, per 1M
74,89 DA
Cache read
3,36 DA
Latency
…
Throughput
…
Reka…
↑ Sent, per 1M
53,25 DA
↓ Back, per 1M
366,12 DA
Cache read
2,66 DA
Latency
…
Throughput
…
IonstreamUnited States…
↑ Sent, per 1M
54,92 DA
↓ Back, per 1M
164,75 DA
Cache read
3,49 DA
Latency
…
Throughput
…
Novita45 % off…
↑ Sent, per 1M
Was 99,8554,92 DA
↓ Back, per 1M
Was 399,40219,67 DA
Cache read
Was 2,001,10 DA
Latency
…
Throughput
…
ModelRunUnited States…
↑ Sent, per 1M
56,58 DA
↓ Back, per 1M
223,00 DA
Cache read
2,00 DA
Latency
…
Throughput
…
DekaLLMAsia…
↑ Sent, per 1M
59,91 DA
↓ Back, per 1M
226,33 DA
Cache read
2,00 DA
Latency
…
Throughput
…
DigitalOcean…
↑ Sent, per 1M
59,91 DA
↓ Back, per 1M
239,64 DA
Cache read
2,00 DA
Latency
…
Throughput
…
GMICloud40 % offUnited States…
↑ Sent, per 1M
Was 99,8559,91 DA
↓ Back, per 1M
Was 399,40239,64 DA
Cache read
Was 2,001,20 DA
Latency
…
Throughput
…
Cohere…
↑ Sent, per 1M
64,90 DA
↓ Back, per 1M
219,67 DA
Cache read
2,00 DA
Latency
…
Throughput
…
AtlasCloud…
↑ Sent, per 1M
64,90 DA
↓ Back, per 1M
259,61 DA
Cache read
1,30 DA
Latency
…
Throughput
…
Phala…
↑ Sent, per 1M
66,57 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Fireworks · Spot…
↑ Sent, per 1M
69,90 DA
↓ Back, per 1M
279,58 DA
Cache read
1,40 DA
Latency
…
Throughput
…
PrimaLabs…
↑ Sent, per 1M
79,88 DA
↓ Back, per 1M
319,52 DA
Cache read
1,60 DA
Latency
…
Throughput
…
Modal…
↑ Sent, per 1M
83,21 DA
↓ Back, per 1M
332,84 DA
Cache read
1,66 DA
Latency
…
Throughput
…
Crusoe…
↑ Sent, per 1M
96,52 DA
↓ Back, per 1M
399,40 DA
Cache read
2,33 DA
Latency
…
Throughput
…
SiliconFlowUnited States…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
183,06 DA
Cache read
2,00 DA
Latency
…
Throughput
…
CoreWeaveUnited States…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Near AI…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
VeniceUnited States…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,50 DA
Latency
…
Throughput
…
Mistral…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,33 DA
Latency
…
Throughput
…
Nebius…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Together…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Fireworks…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
BaseTen…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,33 DA
Latency
…
Throughput
…
Parasail…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
FireworksUnited States…
↑ Sent, per 1M
149,78 DA
↓ Back, per 1M
599,10 DA
Cache read
3,00 DA
Latency
…
Throughput
…
Provider↑ Sent↓ BackCache readLatencyThroughputUptime
Relace2,00 DA166,42 DA1,66 DA………
OpenInference5,82 DA199,70 DA1,33 DA………
MorphUnited States7,32 DA133,13 DA1,33 DA………
WaferUnited States12,65 DA166,42 DA3,33 DA………
Particle AIUnited States16,64 DA166,42 DA1,00 DA………
Wafer21,97 DA166,42 DA2,16 DA………
AlibabaAsia24,96 DA99,85 DA2,50 DA………
InferenceNetUnited States26,63 DA183,06 DA2,66 DA………
InferenceNet26,63 DA183,06 DA2,66 DA………
Baidu65 % offWas 93,1832,52 DAWas 376,10131,26 DAWas 2,010,70 DA………
DeepInfra51 % offUnited StatesWas 66,5732,62 DAWas 199,6997,85 DAWas 2,000,98 DA………
Cloudflare33,28 DA199,70 DA1,00 DA………
Sail ResearchUnited States33,62 DA49,93 DA2,24 DA………
PrimeIntellect36,35 DA399,40 DA2,00 DA………
StreamLake63 % offWas 99,8436,94 DAWas 399,41147,78 DAWas 2,000,74 DA………
Decart18 % offUnited StatesWas 49,9340,94 DAWas 199,71163,76 DAWas 1,000,82 DA………
StepFun55 % offWas 99,8444,93 DAWas 399,40179,73 DAWas 2,000,90 DA………
DeepSeek49,93 DA199,70 DA1,00 DA………
Makora49,93 DA399,40 DA2,00 DA………
Sail Research50,42 DA74,89 DA3,36 DA………
Reka53,25 DA366,12 DA2,66 DA………
IonstreamUnited States54,92 DA164,75 DA3,49 DA………
Novita45 % offWas 99,8554,92 DAWas 399,40219,67 DAWas 2,001,10 DA………
ModelRunUnited States56,58 DA223,00 DA2,00 DA………
DekaLLMAsia59,91 DA226,33 DA2,00 DA………
DigitalOcean59,91 DA239,64 DA2,00 DA………
GMICloud40 % offUnited StatesWas 99,8559,91 DAWas 399,40239,64 DAWas 2,001,20 DA………
Cohere64,90 DA219,67 DA2,00 DA………
AtlasCloud64,90 DA259,61 DA1,30 DA………
Phala66,57 DA399,40 DA2,00 DA………
Fireworks · Spot69,90 DA279,58 DA1,40 DA………
PrimaLabs79,88 DA319,52 DA1,60 DA………
Modal83,21 DA332,84 DA1,66 DA………
Crusoe96,52 DA399,40 DA2,33 DA………
SiliconFlowUnited States99,85 DA183,06 DA2,00 DA………
CoreWeaveUnited States99,85 DA399,40 DA2,00 DA………
Near AI99,85 DA399,40 DA2,00 DA………
VeniceUnited States99,85 DA399,40 DA2,50 DA………
Mistral99,85 DA399,40 DA2,33 DA………
Nebius99,85 DA399,40 DA2,00 DA………
Together99,85 DA399,40 DA2,00 DA………
Fireworks99,85 DA399,40 DA2,00 DA………
BaseTen99,85 DA399,40 DA2,33 DA………
Parasail99,85 DA399,40 DA2,00 DA………
FireworksUnited States149,78 DA599,10 DA3,00 DA………

You pay the price of the provider that served your request. Prices read 15:06 · speed over the last 30 minutes · uptime over 3 days.

See it in action

Real requests, real replies. Try any of them yourself — one click, pre-filled.

Understands images
You send

What's the total on this invoice, and when is it due?

invoice-scan.jpg · photo
It replied

The total is 42 300,00 DA, due 5 September 2026. Worth a double-check: the handwritten day could read as 8 instead of 3.

Try in Chat Lab
Structured output
You send

Turn this customer email into JSON with intent, urgency and order_id.

customer-email.txt
It replied

{ "intent": "refund", "urgency": "high", "order_id": "OD-58421" }

Try in Chat Lab

Try your own request — same model, pre-selected.

Open Chat Lab

Call it in code

Swap the base URL and the key. Your OpenAI code runs unchanged.

POST /v1/chat/completions
Base URL
https://opendunes.com/v1
Model ID
deepseek/deepseek-v4.1-flash-1017
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://opendunes.com/v1",
    api_key=os.environ["OPENDUNES_API_KEY"],
)

resp = client.chat.completions.create(
    model="deepseek/deepseek-v4.1-flash-1017",
    messages=[{"role": "user", "content": "Two lines to welcome a shop in Oran."}],
)

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

Runs this request once on your balance.

Parameters you can send

Standard OpenAI fields, grouped by what they control. Anything not listed is accepted and ignored.

Shaping the reply

How long, how varied, where to stop.

max_tokenstemperaturetop_ptop_kmin_pstopseedfrequency_penaltypresence_penaltyrepetition_penaltylogit_biaslogprobstop_logprobs

Reasoning

Let it think before answering — and see the thinking.

reasoningreasoning_effortinclude_reasoning

Structured output

Get JSON you can parse instead of prose.

response_formatstructured_outputs

Tools

Let the model call your functions.

toolstool_choiceparallel_tool_calls

Other

Also accepted by this model.

max_completion_tokens

Questions about DeepSeek V4.1 Flash 1017

  • How much does DeepSeek V4.1 Flash 1017 cost in dinars?

    About 0,15 DA per message. ↑ 49,93 DA · ↓ 199,70 DA per 1M tokens.

  • Is DeepSeek V4.1 Flash 1017 free? Can I try it?

    No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.

  • What is DeepSeek V4.1 Flash 1017 best for?

    #10 for 3D scenes · This is the 17 October 2026 snapshot of V4.1 Flash, the image-and-text model DeepSeek serves under its current Flash name. It keeps about a thousand pages in mind, replies up to about 393 pages, thinks first, uses your connected tools and fills in the exact form you give it. Pick it for agents and coding work that include screenshots, and when you want the newest Flash. The earlier DeepSeek V4.1 Flash is the snapshot before this one; V4 Pro 0813 is the larger model for hard reasoning.

  • DeepSeek V4.1 Flash 1017 or DeepSeek V4.1 Flash?

    DeepSeek V4.1 Flash costs 0,040 DA less for the same message.

  • How do I pay for DeepSeek V4.1 Flash 1017 without an international card?

    Deposit dinars with your Edahabia or CIB card. Every model, DeepSeek V4.1 Flash 1017 included, is paid from that balance. No foreign card, no conversion.

  • Does DeepSeek V4.1 Flash 1017 work in Arabic, French or Darja?

    DeepSeek names no languages for DeepSeek V4.1 Flash 1017. Arabic, French and Darja: not stated.

  • Can it read PDFs, images or a whole book?

    It reads text and images. Up to 1M tokens in one request, about 1 000 pages. It writes up to 295 000 words at once.

  • Is DeepSeek V4.1 Flash 1017 open source?

    Yes, its weights are public. Open weights on Hugging Face

  • Who makes DeepSeek V4.1 Flash 1017, and when was it released?

    DeepSeek. Released 17 October 2026.

Other DeepSeek models, priced in dinars

See all DeepSeek models
DeepSeek V4.1 FlashDeepSeek · Sep 10, 2026

DeepSeek V4.1 Flash is the first DeepSeek model built on a new design, and it reads images as well as text, keeping about a thousand pages in mind. It thinks before answering, uses your connected tools and fills in the exact form you give it. Use it as the fast, everyday model for coding agents that also need to look at screenshots or diagrams.

Thinks firstUses your tools1 000 pages at once
≈0,11 DAper message
View model
DeepSeek V4 Flash 0731DeepSeek · Jul 31, 2026

DeepSeek's generally available V4 Flash, re-post-trained for coding, reasoning and agent work on the same 284B mixture-of-experts with 13B active, with tools, structured output and switchable reasoning

#27 of 119 for codingThinks firstUses your tools
≈0,065 DAper message
View model
DeepSeek V4 Flash 0423DeepSeek · Apr 24, 2026

DeepSeek V4 Flash is the first V4 release of the Flash size, built for fast answers over very long text. It reads about a thousand pages at once, thinks before answering when asked, uses your connected tools and fills in the exact form or table you give it. Pick it to run an agent or summarise a whole codebase quickly. DeepSeek V4 Flash 0731 is the retrained revision for coding and agents; V4 Pro is the larger model.

Thinks firstUses your tools1 000 pages at once
≈0,061 DAper message
View model
DeepSeek V4 Pro 0813DeepSeek · Aug 12, 2026

DeepSeek V4 Pro 0813 is the general-availability release of V4 Pro, the large model for hard reasoning, coding and long agent runs. It reads about a thousand pages of text, replies up to about 384 pages, uses your connected tools and fills in the exact form you give it, with three thinking levels (low, high and max) so you choose how much it reasons.

#28 of 119 for codingThinks firstUses your tools
≈0,81 DAper message
View model