opendunes

DeepSeek V4.1 Flash

by DeepSeekReleased 10 September 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.

TakesTextImages
GivesText

What it costs

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

≈ 0,11 DA per message3 000 DA buys about 26 000 messages

One message, the ordinary use

1 000 tokens sent× 16,97 DA per 1M0,017 DA
500 tokens back× 188,72 DA per 1M0,094 DA
Total≈ 0,11 DA

Every rate

Meter↑ you send↓ comes back
Text tokens16,97 DA188,72 DA
Cached tokens read5,99 DA

per 1M tokens

Read an invoice photo and pull out the total≈ 0,046 DA
Answer a quick question≈ 0,050 DA
Reply to a customer email≈ 0,086 DA
Explain a stack trace and suggest a fix≈ 0,14 DA
Review a 300-line pull request≈ 0,24 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

30 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
…
Baidu83 % off…
↑ Sent, per 1M
Was 99,8216,87 DA
↓ Back, per 1M
Was 399,4167,50 DA
Cache read
Was 2,010,34 DA
Latency
…
Throughput
…
WaferUnited States…
↑ Sent, per 1M
16,97 DA
↓ Back, per 1M
188,72 DA
Cache read
5,99 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
34,28 DA
↓ Back, per 1M
199,70 DA
Cache read
2,66 DA
Latency
…
Throughput
…
InferenceNet…
↑ Sent, per 1M
34,28 DA
↓ Back, per 1M
199,70 DA
Cache read
2,66 DA
Latency
…
Throughput
…
Reka20 % off…
↑ Sent, per 1M
Was 49,9339,94 DA
↓ Back, per 1M
Was 399,40319,52 DA
Cache read
Was 3,332,66 DA
Latency
…
Throughput
…
CoreWeaveUnited States…
↑ Sent, per 1M
43,27 DA
↓ Back, per 1M
216,34 DA
Cache read
0,67 DA
Latency
…
Throughput
…
AtlasCloud…
↑ Sent, per 1M
44,93 DA
↓ Back, per 1M
179,73 DA
Cache read
4,49 DA
Latency
…
Throughput
…
DeepInfra30 % offUnited States…
↑ Sent, per 1M
Was 66,5746,60 DA
↓ Back, per 1M
Was 199,70139,79 DA
Cache read
Was 2,001,40 DA
Latency
…
Throughput
…
StreamLake51 % off…
↑ Sent, per 1M
Was 99,8648,93 DA
↓ Back, per 1M
Was 399,41195,71 DA
Cache read
Was 2,000,98 DA
Latency
…
Throughput
…
Mancer 2…
↑ Sent, per 1M
49,93 DA
↓ Back, per 1M
166,42 DA
Cache read
49,93 DA
Latency
…
Throughput
…
PrimeIntellect…
↑ Sent, per 1M
51,92 DA
↓ Back, per 1M
399,40 DA
Cache read
1,60 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
…
Wafer…
↑ Sent, per 1M
63,24 DA
↓ Back, per 1M
216,34 DA
Cache read
3,99 DA
Latency
…
Throughput
…
Novita35 % off…
↑ Sent, per 1M
Was 99,8564,90 DA
↓ Back, per 1M
Was 399,40259,61 DA
Cache read
Was 2,001,30 DA
Latency
…
Throughput
…
Fireworks · Spot…
↑ Sent, per 1M
69,90 DA
↓ Back, per 1M
279,58 DA
Cache read
1,40 DA
Latency
…
Throughput
…
Phala30 % off…
↑ Sent, per 1M
Was 99,8669,90 DA
↓ Back, per 1M
Was 399,40279,58 DA
Cache read
Was 2,001,40 DA
Latency
…
Throughput
…
DigitalOcean…
↑ Sent, per 1M
74,89 DA
↓ Back, per 1M
299,55 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Makora…
↑ Sent, per 1M
86,54 DA
↓ Back, per 1M
389,42 DA
Cache read
1,93 DA
Latency
…
Throughput
…
Crusoe…
↑ Sent, per 1M
96,52 DA
↓ Back, per 1M
399,40 DA
Cache read
2,33 DA
Latency
…
Throughput
…
Google…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
9,99 DA
Latency
…
Throughput
…
Nebius…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
3,33 DA
Latency
…
Throughput
…
Cohere…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
1,00 DA
Latency
…
Throughput
…
BaseTenUnited States…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,33 DA
Latency
…
Throughput
…
Together…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
SiliconFlowUnited States…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
2,00 DA
Latency
…
Throughput
…
Modal…
↑ Sent, per 1M
99,85 DA
↓ Back, per 1M
399,40 DA
Cache read
9,99 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
…
Fireworks…
↑ 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
…
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………
Baidu83 % offWas 99,8216,87 DAWas 399,4167,50 DAWas 2,010,34 DA………
WaferUnited States16,97 DA188,72 DA5,99 DA………
AlibabaAsia24,96 DA99,85 DA2,50 DA………
InferenceNetUnited States34,28 DA199,70 DA2,66 DA………
InferenceNet34,28 DA199,70 DA2,66 DA………
Reka20 % offWas 49,9339,94 DAWas 399,40319,52 DAWas 3,332,66 DA………
CoreWeaveUnited States43,27 DA216,34 DA0,67 DA………
AtlasCloud44,93 DA179,73 DA4,49 DA………
DeepInfra30 % offUnited StatesWas 66,5746,60 DAWas 199,70139,79 DAWas 2,001,40 DA………
StreamLake51 % offWas 99,8648,93 DAWas 399,41195,71 DAWas 2,000,98 DA………
Mancer 249,93 DA166,42 DA49,93 DA………
PrimeIntellect51,92 DA399,40 DA1,60 DA………
GMICloud40 % offUnited StatesWas 99,8559,91 DAWas 399,40239,64 DAWas 2,001,20 DA………
Wafer63,24 DA216,34 DA3,99 DA………
Novita35 % offWas 99,8564,90 DAWas 399,40259,61 DAWas 2,001,30 DA………
Fireworks · Spot69,90 DA279,58 DA1,40 DA………
Phala30 % offWas 99,8669,90 DAWas 399,40279,58 DAWas 2,001,40 DA………
DigitalOcean74,89 DA299,55 DA2,00 DA………
Makora86,54 DA389,42 DA1,93 DA………
Crusoe96,52 DA399,40 DA2,33 DA………
Google99,85 DA399,40 DA9,99 DA………
Nebius99,85 DA399,40 DA3,33 DA………
Cohere99,85 DA399,40 DA1,00 DA………
BaseTenUnited States99,85 DA399,40 DA2,33 DA………
Together99,85 DA399,40 DA2,00 DA………
SiliconFlowUnited States99,85 DA399,40 DA2,00 DA………
Modal99,85 DA399,40 DA9,99 DA………
BaseTen99,85 DA399,40 DA2,33 DA………
Parasail99,85 DA399,40 DA2,00 DA………
Fireworks99,85 DA399,40 DA2,00 DA………
VeniceUnited States99,85 DA399,40 DA2,50 DA………
FireworksUnited States149,78 DA599,10 DA3,00 DA………

You pay the price of the provider that served your request. Prices read 15:19 · 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
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",
    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_ptop_astopseedfrequency_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

Questions about DeepSeek V4.1 Flash

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

    About 0,11 DA per message. ↑ 16,97 DA · ↓ 188,72 DA per 1M tokens.

  • Is DeepSeek V4.1 Flash 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 best for?

    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.

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

    DeepSeek V4.1 Flash 1017 costs 0,040 DA more for the same message.

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

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

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

    DeepSeek names no languages for DeepSeek V4.1 Flash. 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 708 000 words at once.

  • Is DeepSeek V4.1 Flash open source?

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

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

    DeepSeek. Released 10 September 2026.

Other DeepSeek models, priced in dinars

See all DeepSeek models
DeepSeek V4.1 Flash 1017DeepSeek · Oct 17, 2026

#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.

Thinks firstUses your tools1 000 pages at once
≈0,15 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
≈0,070 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