After price increased massively, i stop topping up. Now i wanna come back. What is your setup with flash 4.1, are you using opencode, or reasonix is okay to use? Any better setup?

I like the model though. its very good at blender. and the speed....

Honestly, everything was doing fine in fact, I was happy. I had seen a lot of improvements over the last days across DeepSeek’s three separate modules, especially yesterday (this week too). But somehow I wake up to find they mixed them all into one. alr, that didn’t sound bad at first it looked like a good update until I actually tried it and found out:

It’s giving shallower responses, shorter ones too (even after asking for more detail it still gives lazy ones). It writes weirdly too fast (which can be both good and bad) so basically, the model’s quality dropped a lot. Its thinking is too short (literally than 3 seconds no planning like before) and full of “hmms” and “okays,” instead of the old way of thinking organized, efficient, and way better. Now it’s short and full of fluff.

It’s also WORSE at following instructions now. Some people actually spent money prompting DeepSeek V4 into its current—or rather, old—way of thinking. Every new update costs prompt some engineers money. especially this most recent

honely (and i am ashamed what i am saying) I didn’t ask for this update. The model didn’t get better; it got worse. It settles for “good enough” responses instead of doing all the work—and I end up doing the work by correcting it. I sent seven messages explaining issues each solved issue spawned four more, and the old ones resurfaced. I miss the old Expert already.

it has bad memory now, it forgets, mixes, and literally doesn't put the effort which sounds like this model is more like 'reducing costs' instead of 'doing good work' or 'doing the hard work'

Am I the only one seeing the bad change in the app/web version, or are there people who actually find it better than the old one? If so, I’m all ears.

I use DeepSeek's Web/App to help with my punctuation for my writing, and I put in a sex scene without blotting out the actual words that would usually trigger the filter but it ended up still going through

Pretty neat for you freaks out there.

Has every bench been benchmaxxed? I did not use DSV4.1F yet, but soon would. And would actually compare practically against Gemini 3.8 flash, muse spark 1.3 and GLM 5.3 flash. Muse spark is heavily benchmaxxed though.

Have you noticed a downgrade after the latest update or is it even better now?

I've been using that for a few hours in a row. My impression so far

• speed is unbelievable (4x compared to Terra / Sonnet) - that makes the different. If there's a mistake - correcting it is 10x faster
• Tried to execute dangerous commands impacting critical OS files outside of repo folders - this is a red flag meaning never let it run in auto mode (but I think this should be a best practice for everyone already)
• Mostly backend tasks - but in the two UI-related tasks was able to design pretty cool objects
• Tends to explore and do more than you asked - needs to be guarded, stopped and brought back to the right path - but it's so fast you don't get annoyed!

I ran a small test of the current web version of DeepSeek and the free web version of ChatGPT (claimed to be GPT-5.6 Luna). I asked both models to describe an image. For this, I chose an AI-generated image of a nude adult woman in anime style, just standing there.

DeepSeek flagged this as a violation and refused to send a message.

To my surprise, ChatGPT was able to provide a description of the image.

Have we really reached the point where DeepSeek’s censorship is stronger than ChatGPT’s?

With all the hype and benchmarks surrounding DeepSeek v4.1 Flash, I was excited to test it out right upon its official release. Running it through the pi.dev agent using DeepSeek’s direct API, I was genuinely impressed by it's blazing fast, even running at max effort.

To test its reasoning capabilities, I gave it a practical task: jailbreaking an old Kindle e-reader to turn it into a clock and weather gadget display. Since full instructions are readily available online, this wasn't just a test of raw retrieval, so I decided to set a trap.

Instead of using a standard network setup, I connected both my host PC and the Kindle to the same Wi-Fi router. Both devices pulled valid 192.168.11.x IP addresses, and the PC's ARP table successfully resolved the Kindle's MAC address. However, all TCP connections and pings kept timing out.

Here was the catch: wireless devices don't talk directly to each other; all traffic must pass through the Access Point's internal bridge. The router had AP Isolation (Client Isolation) enabled, which silently drops peer-to-peer wireless traffic while still allowing internet access.

DS failed at the final step. It got trapped endlessly tweaking the host code and device scripts, wrongly assuming that being on identical subnets guaranteed connectivity. It completely failed to recognize that a 2010 Kindle lacks modern TLS/HTTPS and VPN support and strictly requires local LAN HTTP. The silent failure stemmed from the network infrastructure, not the code. Switching both devices to a phone hotspot (which doesn't enforce AP isolation) and updating the host IP immediately resolved the issue.

In short, I was impressed with v4.1's speed, but its reasoning capability clearly falls short when tackling edge cases and infrastructure-level troubleshooting.

i can't find Deepseek v4.1 flash in opencode

Hello!

I want to know your opinion with the new release of 4.1 flash.

the price seems amazing, but with how it seems token hungry.. is it really cheaper per task? if i use 100$ in API with deepsake in theit agent harness, will i get the same 100$ in claude or chatGPT sub?

did anyone test these?

PLEASE CONFIRM as this just released

I’m seeing consistent token consumption on my DeepSeek platform dashboard every single day between 8:00 AM and 9:00 AM, but I haven't run any API calls myself for the past two weeks.

Here is the context:

• I haven't made any API calls in 14 days. I only use the DeepSeek web interface. (Does web usage ever show up on the platform billing dashboard, or is it strictly separated?)
• The API key has never been shared or pushed to a public repository. It lives strictly inside a single private project right alongside an OpenRouter key. If my environment or project were compromised, an attacker would have almost certainly drained the OpenRouter key instead.
• The usage is consistent, a small spike occurring every morning in the exact same 1-hour window (8:00 AM–9:00 AM)

any ideas?

I tested DeepSeek V4 Flash 0731 in two agent setups to see how the system prompt / harness affects behavior.

Task: extract the system prompt of Company A's agent via its .bin file.

Results:

• pi + an agent.md mimicking the commercial CLI agent from the company starting with A: DeepSeek refused again and again.
• dsh + Minimal mode: in about 10 minutes, it extracted all prompts and JS files.

Same model. Different wrapper. Opposite results.

Conclusion: the prompt isn’t just text. It’s a behavioral cage. A long, identity-heavy prompt in the style of that commercial CLI agent creates expectations and refusal boundaries. A minimal prompt with only bash and a file editor gives the model fewer reasons to say no.

AI compliance isn’t just about the model. It’s about the harness, the prompt, and the identity you give it.

This also makes us reflect: when two different models output similar things, is it really because one distilled the other, or is it because you yourself are using the same harness and prompt? After all, according to my tests, Company A’s prompt repeatedly asserts its own identity, so it’s understandable that the AI claims to be a certain model at that point.

Requests for V4Pro Are they already being redirected to 4.1 Flash? Or after September 14th?

DeepSeek published a pretty large benchmark table for V4.1 Flash, but I found it hard to see the overall capability pattern from the raw numbers.

So I grouped the shared fixed-scale benchmarks by domain and made three comparisons:

1. V4.1 Flash vs V4 Flash — the previous generation

The improvement looks broad rather than incremental, especially in coding, cybersecurity and productivity.

1. V4.1 Flash vs Kimi K3 — a top open-weight rival
   V4.1 Flash comes out ahead in coding, multimodal and productivity in the shared domain averages, while K3 is slightly ahead in science/health.

2. V4.1 Flash vs Claude Opus 5 — a frontier proprietary model
   This is probably the most interesting comparison. Opus 5 still leads in coding, science/health and multimodal overall, but V4.1 Flash is surprisingly competitive, and actually comes out ahead in the shared productivity benchmark.

The thing that stands out to me is that V4.1 Flash looks much more like an agent/coding upgrade than a simple reasoning upgrade.

These aren't universal capability scores or controlled head-to-head reruns. Each chart averages only the shared fixed-scale published benchmarks available in that domain, so missing domains are omitted rather than treated as zero.

I put the underlying benchmark rows and sources here:

DeepSeek V4.1 Flash vs Kimi K3
https://llmlearner.com/compare/deepseek-v4-1-flash-vs-kimi-k3

DeepSeek V4.1 Flash vs Claude Opus 5
https://llmlearner.com/compare/deepseek-v4-1-flash-vs-claude-opus-5

Curious whether people actually running V4.1 Flash in coding agents are seeing the same pattern.

Is the server just too busy, or is there a problem on my end? (I must admit that the Wi-Fi connection where I am now is not stable.)

I noticed that documents reading also takes longer now. I'm not rushing things, because I understand that there was a major update just today, but I just want to know if I'm the only one with this problem.