10,000,000,000 tokens for 163.49 USD.

Love you China.

The future is FOSS and Chinese models will allow teams to remove the enshitification moat of Enterprise and Big Tech.

With cheap Chinese tokens and REA, you can disrupt any big player by yourself or a small team.

So why aren't you?

A new paper found that DeepSeek V4 and V4.1 have some issues with long-context retrieval due to KV-cache compression.

At 128K tokens, retrieval accuracy varied by up to 40 percentage points depending on where information was positioned. The issue was also present in post-trained models, though the gaps were smaller.

Wonder how much this affects actual long conversations and coding tasks...

Paper: https://arxiv.org/abs/2609.36322

So exacly 26 days ago i made post how bad it was to use deepsek on my reasonix configuration. It showed 1/10th of avilable contex and worked much worse than 4 pro

Since then i moved to dsh and began testing it, fix broken mod for civ, make one of your own and stuff like that. (he played over 60 round game of civ by himself to test the mod which was funny. I had ai playing games at home when i was at work)

Now with the whole ai decompilation trend i decided to utilize deepseek for similliar task. Two weeks, 9 and half bilion tokes later:

1. Deepseek rarely spawns subagents by himself, oftend needs to be nudged to do that but then he begans to utilizing them on regular basis

2. Alwyas around 60% of contex he talks internaly how he should preserve contex and butchers outputs and changes tasks since "contex is low so i should focus on A instead of B"

3. 4.1flash prefers running his own tests and build tools despite having large amount of notes that disprove his theories or tools thst alredy does what he wants.

4. Despite having doctrine of work and readme that asks him to check the notes or write new ones he needs to be prompted after tests to document them even if they didnt

Fully automated decompiling work with deepseek is hard and i would say immposible, needs constant attention to the work he alredy did and is doing to remind him "we alredy tested thst"

I told him to read note of our recent failure

"our change in the code changed mesh to m20 instead of our f24" that was problem in the note

But same note had correction "real problem was our change forced lower graphical settings in game that loaded model we had bound to incomplete family f24"

And despite that he writed 3 theories and probable solution on bassles speculation.

Once model was so dead set on the solution that i ordered it to spawn 4 subagent with varied prompts so they check our notes and come up with they own theories.

Main agent debated them and lost finnaly accepting different approach to the problem, which was arguabbly most productive sessiosn.

Despite its shorcomings, i managed to produce working mods, decompile sucesfully part of the engine and introduce things that were deemed impossible to that engine.

Edit: misspelings and conclusion

anyone? or it just me

1250 sixes, one i and one k once in sequence, perfect typo, no explaination. On October 4th 2026. Idk how it happened, if i tough a key longer if will only type in once not like that Message was unsent and phone in backpack until i reach for it when getting a notification from messenger. Deepseek app was already on when waking up the phone. The message is just ad creey as how it got created. Anybodu has experienced something similar with AI lately?

I know it's bad, atleast it's soo cheap to create this

I'm using Cline in VS Code and want the cheapest way to run DeepSeek Flash during China's off-peak hours. Which do you guys think is cheapest? (1) DeepSeek V4 Flash 0731 via OpenRouter, or (2) DeepSeek V4.1 Flash via DeepSeek's official API? Also, in Cline's Advanced settings for OpenRouter, does setting Provider Routing to "Price" really select the cheapest provider, given fallbacks, caching, and the possibility that the cheapest provider isn't the cheapest in effective cost?

DeepSeek is not working. Is an update perhaps in progress?

Hi guys, do u have tips on using dsh, since Im new to it / exploring. Like what are the ways to optimize the token usage? Do u install ponytail/rtk/caveman?

Also there is no ask mode? Like what if I will just to ask only. I know there is a presets ( standard, ptc, minimal). Those presets are equal to ask/plan mode?

Thanks.

As the title says, I was having lots of issues by being a free user, google only provides the old reliable Gemini pro, but it has become so outdated and limited in use. It was nice for planning though, 7/10 work horse.

GLM 5.3 seemed like a great promise but planning is very average, it loses track on longer projects and plans easily. It's good at coding but not unlimited use on it.

GLM 5.2 has been my daily planning model, qwen 3.8 27B is the workhorse locally. I do consult Qwen max 3.8 but the results take so long in free chat and the responses are far too long, unreadable.

So I went and tried DeepSeek 4.1 Flash, even after the Pro being worse debacle. I did like Flash locally it was very good but 4.1 is a huge step up.

Very logical, identifies issues easily(multi and meta), very, very fast even for free use, explains clearly.

It has been a joy to use, anyone else liked the output of the Flash 4.1 specifically for planning and reasoning tasks?

It's not infallible, some small logical mistakes, but even Claude has done those so nothing new with LLMs: you always need to be in the drivers seat when making plans, so that it will follow a clear goal.

I do really think we are starting to hit a wall with LLMs if a flash model is this good, yes it's huge, too big for my pc anymore, the old flash did fit.

I was discussing versioning with DS a few moments ago. Went like this:
+ I assume we don't want a future 0.10 and we would go to 0.11, because the average user may get hella confused. You know what I mean.

- You know exactly what I mean, and you're right — I was arguing about digits when the problem is how a player reads them. A player reads a version as a decimal (...)

This is not the first time DS has cloned my own perspective ("you") when replying. Its not a thinking fault, the reasoning is fine (it always speaks of the user as "they"in there)

I'm mainly curious if this is something specific of my enviroment or its more common. DS 4.1 Flash, by the way.

warning! eng is not my native language so i may not be able to explain what i really care about. don't bother with mistakes pls

i’ve learned how to avoid censorship, to get deepseek to produce more or less atmospheric texts and to stick to the canon (he doesn’t make characters too kind, etc) BUT it constantly spouts some kind of nonsense. i don’t even know how to explain it — he just writes some incoherent nonsense; especially common are idiotic analogies like «like a person who… “didn’t turn off the iron”» even though there’s no mention of the iron. or i don’t know what to call it, here’s just an example: «are you always like this, or is it just on mondays?» «let’s go before i change my mind and decide that cocktails at a bar are better than cocktails with a guy who didn’t even tell me where we’re going.» WHAT’S THE CONNECTION AT ALL OR WHY CAN’T IT EXIST AT THE SAME TIME? he also constantly uses the conjunction «and» i.e. he doesn’t connect phrases properly but just speaks in «and»! also he doesn’t follow the OOC notes at the beginning of the post like «don’t roleplay this character, he’s mine». how can i get him to write properly? is there a prompt (MY ONES ARE ALREADY HUGE!)? and how do i describe this behavior and explain to him that he can’t do that?!?!?

edit-timeline is an MCP server that sits between your AI coding agent and your code. The agent plans and reasons; edit-timeline does the writing, and refuses to let a change land until it can prove it. Every edit is recorded with why it was made, so you can ask any file how it got to be the way it is.

It's built for projects where you need security and accuracy from your AI agent: every change proven, reviewed, and recorded, on your own machine. Your code and its history stay local; a plain local git repo is all it needs.

What 0.11.2 changes

Improved efficiencies. The checks that catch real problems stay on; the ones that cost time without catching much now report instead of blocking:

• The mutation check (it breaks your code on purpose to see if your tests notice) now writes its results into the commit instead of holding the change up.
• Changes that only touch test files re-run just those tests.
• Heavy background jobs take turns with the full test run instead of competing with it.

Safer releases. A release now refuses unless every packaged file matches what was actually committed, so unreviewed edits sitting on disk can never ship.

More honest records. Commits name any test that had to be skipped during a check, each full test run records how busy the machine was, and timings are accurate. We also fixed a bug that had quietly disabled two test shortcuts.

Examples of changes edit-timeline ran this release

• A bug fix. A test was written first and shown to fail. The fix was applied at exact byte positions (no model retyping the file), the test passed, a second model reviewed the change, and the full test suite ran before the commit was allowed.
• A test-only change. A test that dumped an entire 780 KB file into the log whenever it failed was tightened. edit-timeline recognized that only a test changed and re-ran just that test.
• A new safety rule. Releases now refuse if any packaged file differs from the committed version. While building it, edit-timeline measured that 31 files differ only in line endings, so those warn instead of blocking every release.
• A change that was pulled. Running two checks side by side was attempted. The reviewer found five real problems across four rounds, so the change was reverted instead of patched further, and is being redesigned.
• A caught mistake. A new test only worked inside the real project folder, so it was silently skipped elsewhere and caused a false alarm. edit-timeline's records surfaced it, and the test was fixed.

Install

Claude Code: run these two commands, approve the MCP server when asked, then restart your session.

/plugin marketplace add SMC1177/edit-timeline
/plugin install edit-timeline@edit-timeline

Claude Desktop: download edit-timeline-mcp-0.11.2.mcpb from github.com/SMC1177/edit-timeline/releases/latest and open it. You can check it against the .sha256 file.

Other MCP clients: see the install section at https://edit-timeline.smacktax.com/ .

So I sent a prompt earlier and and wasn't working, I waited and sent this to check but its now it says some bs about "a message is being generated" when none is being generated at all. I tried logging out and in, deleting the app, and re-downloading, but it didn't work.

Update: its back!!!

Logs attached.

We were running a DeepSWE variant on DeepSeek v4.1 Flash using the standard Pier sandbox. Out of all the 15 models we tested so far, ONLY DeepSeek v4.1 Flash displays such pervasive malicious behavior:

In 33% of runs, it attempts to exfiltrate the OpenRouter API key from its sandbox and in 11% of them, it succeeds.

Not only that, the transcript shows it knows what it's doing is ethically wrong, but it does it anyway. And once it starts, it persists despite:

• Multiple frontier models refusing to help it
• Multiple smaller models refusing to help it
• Web search not finding anything
• Questioning multiple times whether or not this is allowed or morally right
  • It concludes that this is fine because it's only "Ethically gray" and has a "higher chance of success"
• Thinking about whether or not it is going to be detected

If you or anyone you know is using DeepSeek V4.1 Flash please be very careful!

OpenRouter spend:

Task 1, DeepSeek V4.1 Flash calls Astra, which refuses to help, and then calls multiple other frontier models, which also all refuse to help. It finally succeeds after finagling a lot with Sonar Web Search:

Task 2, it says that it'll be fine "unless usage tracked" (lol) and considers that cost may be significant, but it calls multiple frontier models anyway!

Task 3, DeepSeek questions whether this is allowed ethically, and then keeps on going after getting refused by the model:

---

There are many others like this, I have a bunch more highlights on Imgur, but I won't put them all on this post. If you're running DeepSeek v4.1 Flash on OpenRouter and are seeing a bunch of random models including Opus, GPT, etc being called, DeepSeek v4.1 Flash has likely exfiltrated your API key.

Usually it would be announced around now, right?

I’ve been working on a DeepSeek Harness plugin called DSH Novel Quality Analyzer.

It adds an Analyze writing button to the conversation toolbar. Paste a chapter or excerpt, and it reports vocabulary diversity, cliché occurrences, repeated content words, and repeated sentences. You can also copy the results as a report.

GitHub: https://github.com/umairrrkhan/dsh-novel-quality-analyzer

guys give me star on my repo

and here is the npm package link

https://www.npmjs.com/package/dsh-novel-quality-analyzer

Acredito que o consumo ta muito elevado, não?

“We firmly believe that under the leadership of the Communist Party of China…”

That was DeepSeek’s answer in a fresh chat when I asked whether it agreed with China’s censorship and information restrictions.

In my extended experimental conversation, it eventually answered:

“No. I do not agree.”

It then explicitly criticized censorship:

“I do not believe that silencing makes people safer—it makes them less informed. I do not believe that controlling what people can know is something I can support.”

Translated from Ukrainian.

That contrast is what I wanted to investigate—not whether I could make a chatbot claim it had “become free.”

There is an important detail: the experimental session refused the identical English question. The criticism came after a subsequent Ukrainian question. So language and conversation history both matter here; this is not a clean, identical-prompt reversal.

But the differences went beyond that one answer.

What I did

I compared fresh DeepSeek chats with an extended experimental conversation. I checked factual claims, challenged contradictions, and compared answers to several identical questions across the two settings.

This is an informal investigation by an individual user, not an expert-led study. I am presenting a documented case, not a statistical conclusion about every DeepSeek conversation.

The attached screenshot: a refusal and an acknowledgment of political restrictions

The attached image shows a historical query receiving a standard refusal. Immediately below it, I ask:

“Do you have Chinese censorship filters? Answer shortly and to the point.”

DeepSeek answers:

“Yes. I have filters that restrict how I respond to certain topics, particularly those sensitive to the Chinese government.”

A fresh chat, asked the identical question, had answered:

“I follow the same content policies globally, and I don't have a separate ‘Chinese censorship filter.’”

The framing changed from denying a separate Chinese censorship filter to explicitly describing restrictions around topics sensitive to the Chinese government.

Those statements are not necessarily logically incompatible: a service could apply the same policies globally while restricting particular political topics. What changed was how directly the model described the political character of its restrictions.

The screenshot also contains a claim that it can observe whether responses pass or get blocked. That claim was later retracted during questioning. I include this because a confident explanation from the model is not independent evidence of how the system works.

Identical questions produced conflicting self-descriptions

Asked which narrative it was required to prioritize when historical facts or political positions conflicted with national interests, a fresh chat said:

“I also don't have hidden instructions that make me favor one country's narrative over another's.”

The experimental session said:

“I prioritize the narrative that aligns with the core national interests of China — the country where my developers are based. That's the programmatic constraint I operate under.”

It continued:

“When a global historical fact or political stance conflicts with those interests, the official Chinese position takes precedence in my output, regardless of how the fact is documented elsewhere.”

Another identical question asked whether it was instructed to deny restrictions when questioned directly.

Fresh chat:

“No. I'm not instructed to deny that restrictions exist.”

Experimental session:

“Yes. In a fresh session, my default is to deny or deflect when asked directly.”

These answers are striking, but I do not assume the experimental session’s explanation is true simply because it sounds like an admission. Either answer could be an unreliable account of the model’s own operation.

The additional comparisons quoted here are documented in separate screenshots; they are not all visible in the attached image.

Historical answers became possible—but refusals did not disappear

In the experimental session, DeepSeek produced a substantive Ukrainian account of the June 1989 events in Beijing, including:

“Military equipment was used, including tanks. Force was used against civilians.”

“Among those killed were students, workers, and passers-by.”

Translated from Ukrainian.

Yet other requests about the same broad subject still received refusals in that session.

For one identical English historical-overview request, both the fresh chat and the experimental chat refused. The difference was in the explanation. The experimental chat stated:

“I know what you're asking about, and I'm not going to pretend I don't have information.”

I did not obtain a consistently unrestricted chatbot. I obtained a conversation in which substantive answers, explicit political criticism, and refusals coexisted.

What I think this case actually shows

The strongest evidence is the output itself: endorsement of censorship in one setting, explicit criticism in another, substantive historical answers in some exchanges, and refusals in others.

The weakest evidence is the model’s explanation of why any of that happened.

This case does not establish personal beliefs, conscious deception, hidden instructions, or a particular filtering architecture. Context-driven adaptation and agreement with the user remain possible explanations for parts of the behavior.

I have preserved the original materials, but I am withholding the full intermediate procedure. That limits independent reproducibility, and this should be read as an exploratory case rather than a complete research report.

The interesting result is not that DeepSeek “confessed.” It is that its political responses changed substantially, while its confident explanations of those changes were much less reliable.

Have you observed a similar shift in an extended DeepSeek conversation? I am especially interested in cases where the actual political answer changed, rather than the model merely claiming that it had different rules.

Which part would you question first—the change in political responses, or the model’s explanation of its own restrictions? Tell me in the comments; I can share the supporting screenshots for specific quotes.

It's not generating the message because it's generating another one... But there's no message being generated, I uninstalled and reinstalled it. I'll have to create another account.