"... DeepSeek v4.1-flash-1017 just got spotted in DeepSeek's own API for a few minutes before vanishing. New checkpoint, changed fingerprint. The 1017 suffix matches their dated snapshot pattern."

Date: 2026-10-17

Opening up the in-house search API
DeepSeek's web and API search capabilities are powered by our in-house DeepSeek search engine, which reliably handles hundreds of millions of search requests from around the world every day. DeepSeek Search is an AI-native general-purpose search engine that indexes hundreds of billions of web pages, supports multilingual search, and returns highly relevant, authoritative, and timely results in real time. It filters SEO spam, GEO manipulation, and low-quality AIGC through strict detection mechanisms, ensuring authoritative and trustworthy information for users and LLMs. For usage details, see the Search & Fetch guide.

- DeepSeek-V4.1-Flash-1017 Update
- DeepSeek V4.1 Flash has been upgraded to DeepSeek-V4.1-Flash-1017.

The official web and APP models have also been updated to the new version. The API calling method and pricing remain unchanged — simply use deepseek-flash to access the latest model.
Performance–cost Pareto improvement
Compared with the previous DeepSeek V4.1, the new model delivers substantial improvements across benchmarks:

HLE (w/o tools): 42.6 (44.0*)
Terminal-Bench 4.0: 42.3
DeepSWE v1.1: 77.0
ProgramBench: 29.1
NL2Repo-Bench: 68.2
Automation-Bench v1.0.6: 60.5
Agents' Last Exam: 35.4
Apex Bench v1.1: 72.1
Chartography (w/tools): 83.0
BabyVision (w/tools): 92.5
ZeroBench-main (w/tools): 51.0

* Tested only on the pure-text subset of the HLE benchmark set. Terminal-Bench 4.0 was tested with the Claude Code framework, and DeepSWE with the Mini-SWE-V2 framework. ZeroBench-main was evaluated with Pass@5.

While improving performance, we also reduced the model's task runtime and output length, enabling users to complete tasks at lower cost and higher speed and achieving a new performance–cost Pareto optimum across multiple harnesses. We specifically optimized for DeepSeek Harness, Tencent CodeBuddy, WorkBuddy, and other platforms. Please upgrade to DeepSeek Harness 0.2.1-rc.1 or later for the best experience with the new model.

Source:
https://api-docs.deepseek.com/updates/

I'm the author of Distill, an open-source coding agent harness (Apache-2.0): https://github.com/samuelfaj/distill

Use case: running DeepSeek as a coding agent without it timing out or burning tokens on every small step.

What I tested: DeepSeek V4.1 Flash at max effort in native Codex (through OpenRouter) against Distill with DeepSeek as the main model and free models from the OpenRouter free router as the worker. Three frozen coding tasks, three runs each, same 300s deadline.

Results:

• Successful runs: 5/9 native vs 9/9 Distill
• Time: 1974s vs 490s
• Cost: at least $0.098 vs $0.012

Chart with the other model pairs: /img/q12ttj8lkwvh1.png

Caveats: native Codex warned about missing model metadata in all nine DeepSeek runs and fell back to default metadata, so this wasn't an officially supported Codex profile. Three native calls timed out without usage receipts, so the native cost is only a lower bound. It's a small benchmark.

BENCHMARKS.md in the repo has the full numbers and the commands to rerun it. Has anyone else run DeepSeek in a planner/worker setup?

I've been running an API gateway for DeepSeek for a while now, and I see hundreds of developers' usage patterns every day. One thing keeps coming up: DeepSeek by default is a people-pleaser.

If you say "I think X is the best approach," it'll say "Great point! X is indeed a solid choice." That's fine for brainstorming, but when you're debugging or planning, that behavior is dangerous. It won't tell you you're wrong. It won't poke holes in your plan.

So I started testing ways to break it out of that mode. Here's what actually worked:

1. "Don't flatter me. If my idea is flawed, say so directly. I need honest feedback, not validation."

After this, the tone shifts. It points out edge cases, questions assumptions, pushes back.

2. "Argue against my proposal. What are the three strongest reasons this could fail?"

Forces it into devil's advocate mode. Use before important decisions.

3. "You are a senior code reviewer. Find bugs and design flaws. Be harsh."

Role-setting changes expectations. It stops trying to be nice, starts being useful.

4. "On a scale of 1-10, how confident are you? If below 7, tell me what you're uncertain about."

Flags its own weak spots instead of confidently making things up.

5. The one I haven't seen elsewhere: ask it to argue with itself.

I ask DeepSeek to generate two responses: one supporting my idea, one attacking it. Then I ask it to judge which argument is stronger. The attacking response often surfaces issues the supporting one completely ignores.

These aren't magic prompts. They're just ways to override the default "agreeable assistant" behavior.

I'll be sharing one small tip like this every day — practical stuff to get real work done with AI. If you've got your own tricks, drop them in the comments.

Granted a total of $875

Had no idea what this was from until they sent this notice,

Cool they granted back for the past week of usage!

I was led to believe there was a door prize for the 10B token club?

i used grok and Gemini before now both not good in free version

How about memory of DeepSeek

Depois da queda de ontem eu notei que as respostas ficaram um pouquinho melhores, embora ele se perca demais em detalhes e ainda está com inconsistências. Mas vi hoje que tivemos uma nova atualização, podem me dizer o que estão achando? Se alguém já notou algum avanço ou melhora na memória, escrita e desempenho. Boa noite!

DeepSeek feels kinda different lately. I’ve noticed that its responses are noticeably slower when I generate random micro-RP scenes and ask it to expand them into longer ones. The slowdown is pretty noticeable, and it makes me wonder if something’s changed behind the scenes. Could this be a sign that DeepSeek V4.1 Pro is on the way? 👀

Is the free chat function really that bad as people here make it out to be?

I had some problems but most of the time it gives a solid result.

Of course I will need to make some more important work and I was thinking of paying for Claude.

Is it better to use this DeepSeek free chat or is it bad enough to just go straight to a paid subscription?

Having zero coding skills and not working with this field, I've managed to code a Space Sim with DeepSeek. It's a 100% procedural, browser depedent game with zero dependencies. It features an entire universe generated from a single 300KB HTML file. It's open-source (MIT). Still being developed.

GitHub Repository

Singularvs, as I've called, is a contemplative space simulator inspired by SpaceEngine and the 1984 classic Elite. It features a ~1 Gpc universe with procedural galaxies, hierarchical star systems (up to 8 stars, brown dwarfs, black holes), almost scientifically classified planets, internal tectonic simulations, dynamic skies, and even procedural music.

I didn't write a single line of code by hand. I used natural language to describe what I wanted, the AI wrote, I ran, tested, debugged, answered what happened and so on. By iterating back and forth for 3 days, this is the result. Also, only English and Portuguese as of now. I know both languages and reviewed them too.

• Vanilla JavaScript
• Zero external libraries, zero assets
• Deterministic PRNG
• Xinput controller support (I've only tested my Gamesir Controller)

It's fully open-source and moddable. I do not guarantee it has zero glitches or flaws. But I hope it fits here.

As claude and gemini has instilled watermarks in their reponses, does DS also has a watermark like that?

if not, do you think it will be implemented tn future?

Insane cache hit.

Does that mean DeepSeek is weak or not so smart in ARC AGI 3? I really hope it will have it as soon as possible, intelligence is FAR more valuable than knowledge

Sorry in advance for my English.

So, I paid for API to roleplay with deepseek as I used to do with website until recent model was launched.

I chose v 4 pro, set temperature to 1,35, filled all necessary info, and I just don't see any difference. Responses are dry, short, lack details. Where are my long beautiful engaging texts?

What else should I do or pay attention to? Any advice, please, from someone who is lucky to enjoy the roleplay.

The consumer interface in https://chat.deepseek.com suffers from:
- Poor instruction following = Not replying in english at times and using bold text in replies even when asked not to
- Hallucinations and making up facts = Assumes things when its not the case
- Poor context management and forgets file details in a long chat = Difficult for studies and verification tasks

Lets send an email to [service@deepseek.com](mailto:service@deepseek.com) requesting for fixes to these. We all enjoy using DeepSeek but the consumer-facing interface could definitely do with some improvements.

Ok, so I recently found the new TTS feature on the DeepSeek web client. Real talk... it is crazy good.

I want to build stuff with this, but it's inconvenient that I can only interact with it via the web right now.

Just some feedback (at least in my testing):

- Tested it with Vietnamese. If the text is "1. Tiêu đề 1", it literally reads "one, Tiêu đề one". Mixing English numbers with Vietnamese words sounds funny as hell.

- Another thing: it completely skips tables (doesn't read them) but decides to read links out loud.

Hope you guys take notes on this. Happy to contribute more once you open it up!

Btw, Stella's voice is totally my bias fr.

Background

I have been using chat.deepseek.com since February 2026 as an orchestrator: I use it to write and refine the prompts that I then run through the DeepSeek API. This is hobby work - I have no commercial interest.

What changed for me

Around the price change this summer I also noticed the output quality dropping. Since then the gap between the two surfaces has become obvious to me:

• The API is still usable for my work. That is why I keep using it.
• The web chat is no longer usable for me. It produces incorrect work, and in a few cases its instructions damaged a project I was working on instead of advancing it. Hallucinated details make it worse: I can no longer tell a solid answer from a plausible-sounding one without verifying everything myself.

I do not want to overstate this. I have no insight into what changed internally, and I am not claiming that the price change caused it - I am reporting what I observe as a long-time user: the same task, handled fine through the API, is not handled reliably in the web chat.

What I hope for

That DeepSeek restores the web chat to a level where it can be trusted for real work again. It was my entry point into all of this and my prompt workshop.

Question

Has anyone else compared the same task across the API and the web chat recently? Concrete examples (task, expected result, what the web chat produced) would help more than another general complaint.

• A disappointed DeepSeek user, still using the API

Waking up to a few free tokens was awesome... how cool is deepseek.

;s proof for the haters https://limewire.com/d/P3O9b#UcRz85Ao74

i searched up deepseek-v4-1-pro and

this thing was shown so idk maybe deepseek v4.1 pro soon