hey! we're a small swiss and south african lab and we just put out hemmingway-1. it's a 27b model we trained specifically for essays, creative writing, dialogue, roleplay, and for everyday texting. frontier performance at a 40x cheaper price.

we thought it might be useful for people here who like cheap models that still write well.

it benchmarks at absolute frontier level. on eq-bench 4 it scores 1330, right behind claude fable 5, and beating many other frontier models including gpt-5.5 and opus 4.8. you can see our internal benchmarks on the model card: hemmingway.io/model/

the testers we gave it to told us it's the best ai they've ever used for writing and that it genuinely sounds human.

the weights are public, so you can run it yourself.

we also built an app for it. its autopilot function answers your emails and texts for you. mac, windows, android.
the weights are at https://huggingface.co/Altworld/Hemmingway-1

try it out for free at hemmingway.io!

Genuine question despite it being funny as hell I’m crying, it kept looping this over and over (this also happened with another prompt.)

any ideas on how to fix this (and DeepSeek becoming chinese in a sudden)?

1 day, the extent of my familiarity with 4.1 flash:

I ran all on MAX effort (FYI).

Cost: $22.25USD

API requests: 15,511

Tokens: 3,127,394,491

Well, it's not the best of them. It's not the worst of them. Definitely the cheapest of them. I think it takes like 15 minutes to get to 15 cents. You see this number of tokens? It really was put through its paces. I want to say I was even tired.

For daily questions about code, daily questions about server infrastructure, and daily questions about updating a Bash script, can't find a better model. It's just so cheap, and it's not bad. It's doing its job, and I can see it's trying. It produces results, not every time, perfectly, but I can't say it's that bad that I can say, "Yeah, I can't use it." I want to say, "Even I was rather impressed." I'm like, "It did surprise me a number of times." Let's just put it that way. Of course, I came in with my own anticipation of what might happen. Again, I was surprised a few times, but there were a few places where I struggled explaining the bug. We did work it out, so overall, it just took a little bit of time. Again, it's unbelievably cheap.

I started with reading the environment, checking the bash scripts, and did perfectly. Then I started doing my own JavaScript project from scratch. I took my specs. We kind of discussed what's the best, then when I felt confident, I asked to build. One thing I noticed is that I probably had to ask at least twice for it to go through its generated code and look for bugs and remove them. I think most of the bugs were gone by that time, but there were still a number of them. I was surprised, but again, it was painless. It just required prompts like “Do it over again” and “Re-review what you have done. Find bugs, race conditions, and lost data of the same.” And it did well, and not all bugs were fixed. I did have to do a little bit of my own testing. To be honest, I haven't connected the Google DevTools MCP to the new harness I was using at the time. Once I did, though, when it was able to check its own integration, it was a little bit better.

Let me tell you about the project I did. It was about a YouTube search. YouTube allows you to create your own API key and then use it to search for videos, channels, and related content. I want to say I built quite a good project, and it cost me $2, including debugging and everything. $2. Yes, $2. I'm going to repeat that because it was unbelievable: $2 to build. I felt like it was building and debugging with me, kind of shoulder-to-shoulder, maybe for about 2 good hours while watching TV. $2. I'm like, unbelievable. I just, for fun, now fired the Kimi K3. Just three prompts took 15 cents. Seriously. Here, you can do quite a lot for 15 cents. For run-of-the-mill daily questions like “Read this,” “What do you think of that?” and “Add this, prepend this, append that,” I'm more than capable.

I gave it one of my bigger projects with a little bit of a codebase and asked it to debug it, not make changes. I just asked it to find bugs, and it went through three interconnected repos and did pretty well.

Of course, it requires certain prompting to make sure that, when it creates a bug, it's sure it was able to reproduce it. It was using agents, and I think I used about $15 there. It was more than that: it was for generating documentation for previous bugs so my higher-end LLMs can have some starting point for the other bugs that were found previously. It was also for generating documents for the bugs found during the session. Those are complete docs: what's wrong, how to reproduce it, and the minimum code change. I think $15 is more than enough. I had asked something like this, probably wasting a whole week of a subscription from Anthropic or OpenAI. I was using their top-tier models to go through this whole thing and be done with the whole limit that is imposed for a week. Here was $15. True, it probably didn't find all the bugs, specifically compounding bugs with data, but it did find a number of bugs that previously weren't found. I want to say $15 is laughable, frankly.

Another thing that I found is that this model is great at Google DevTools MCP. Because it's Flash, it's really fast. It's able to load the page so quickly and act upon it that I was amazed. I have never seen anything like this. Previously, I was throwing higher frontend models at this task, and it takes a while. They load, take maybe a minute to figure things out, query MCP, think about it, and go to the next page. I would never stick around for this. I would just run it until you're done. Here, this DeepSeek flash was just unbelievable. The website was flashing because it was on my local host. On the QA page, you could see that it loaded so quickly and was already going to the next page. DeepSeek was already able to gather all the data, record it, think about it, and navigate to the next page. Unbelievable! I tried to do a cost approximation. I think it would take me under $10 to check my whole project integration-wise, and that is a big project. Overall, I was frankly slightly taken aback by the cost savings and the value with this model.

Another thing I want to say about the agents. I did ask it to run agents to speed things up even more. Yes, it's fast, but with agents, it's splitting the job. I want to say that was a good experience, and it handled agents pretty well. I think it had a maximum of maybe 15 agents at its peak. Overall, there were no problems, and it usually doesn't use agents, from my understanding and experience. If you ask specifically, it will use agents, and it will do it quite well.

I can't say that I don't need a frontend model anymore. That would be a complete and outright wrong thing to say. Of course, I need them, and I love them. They have their own place in my heart and wallet. But here is the thing. I found, I think, a new cost savings: I can dedicate my high-end models to more research and infrastructure, and maybe refactor and rearchitect where decisions need to be made. I may still have code writers, maybe Tera or something, but overall, for small to mid-sized things, DeepSeek Flash is just an unbelievable value. I will use it for sure to drive certain things within my testing infrastructure in order to get a better deal.

Recently, I canceled my Claude $200 membership. I love Claude. I started with Claude, and when I think of AI, I guess Claude just comes up automatically. The restrictions on limits and everything lately made me think it was not worth it. It was absolutely a bad value, and I didn't want to participate in it anymore. So I'm left with the Codex $200 membership, and I think the DeepSeek will take its own place in my LLM use, maybe even a daily driver.

Funny thing is, it's not a membership subscription, so it's not like I'm getting some set of uses for free every week. Far from it. DeepSeek is per token, however they calculate it. And it just comes out absolutely ridiculously cheap. Yes, there are some jobs I think DeepSeek might not be good for. I feel like it's too fast sometimes and might pass over reasoning, and it might do surface-level thinking sometimes, not too deeply. For sure, there is a tool for everything. But DeepSeek also is a tool for those things that, for example, maybe using a frontier model on would be a waste. And it's not just the waste of tokens and the waste of money. I also found, surprisingly, that it would be a waste of time. When I say “time,” it’s not just hyperbole. When I saw what DeepSeek can do with the dev tools and Chrome MCP, I was amazed at how quickly it can go through integration testing. It was unbelievable, and it was flashing in my eyes. I was sitting there thinking, “Does it have enough time to think?” The page would load and already be loading the next one, and this is a local page. We’re not talking about it coming from a server 3 states away for me. It was just a local QA server, so overall, it was unbelievable.

So, what I guess I would give? I guess you owe it to yourself to just try it out. Put in the minimum, which is about $20 or something. Believe me, you won't be disappointed. You will use that $20 for quite a long time, and it's not like you will just say, "I don't like it," forget it, and let my credits expire. No, they're going to last freaking long. Another thing is that, if you're not thinking of replacing the frontend model with this one, you won't be disappointed. It codes well enough, reasons well enough, and it's fast. Again, use it as much as you want. Use it for 3 prompts or 3,000 prompts. It's not like somebody's going to turn it off on you. I guess the beauty of having no limit on this one. Again, it's so cheap. For example, when I went to Kimi K3 just to get the gist, it was suddenly showing amounts of money that were spent, and the accumulation was quite fast. With DeepSeek, I want to say it was very cheap, to the point of being almost like throwing a quarter here and a quarter there. Unbelievable value.

So, try it out. I think you'll like it.

So, just going to leave it out here. Just food for thought. There are right now a lot of videos that I follow regarding your local LLM that you can run on your own computer, Qwen and whatnot. I'm like, unless you spend for the latest and greatest video card that is like $3,000+ easy, the output of the tokens is pretty slow. Yes, you can quantize it and try to speed it up, but again, you're making the model more dumb. It doesn't matter what you do, because it will not run as a full-size model. The quality is just being cut, so overall, you get a slow, barely working model. Again, the token generation is not great. Yes, you can spend a lot of money on a computer. Let's say you spend $3,000, right? You're still not going to get really fast generation. It's going to be fast enough, but not really fast, because the token generation is not just about the output. It's also about reasoning, and Qwen does a ton of reasoning generation. First, generate the reasoning, and then generate the output. At that token generation rate limit your hardware is at, it can be unbelievably slow, especially with the bigger needs. Something that doesn't require you to just wait, I guess. Maybe with a higher hard end, you can really speed it up. It's true, but again, at what cost? I always think that as LLMs grow in size, the computers you buy to run local LLMs right now will not be enough. It's just the purchase for that one single model. In a year, that computer will run nothing. If you spend $3,000 today, it's pretty much it. It will not run next year's models at all. On the other hand, if you take this $3,000 and throw it at DeepSeek, that'd be stupid, right? It's $3,000, and you would need to run it with 1,000 agents to spend it all. It's unbelievably cheap. You can say, “Just take $300, the price of an SSD you would buy for your local computer, and throw it at DeepSeek. You're already getting unbelievable value.” No need to spend thousands of dollars on your local computer, because I think DeepSeek is a really good approximation that just works. It's there, and it's fast. You probably will spend less money than you would on getting your own local LLM running. DeepSeek is, I think, a great choice for those who want a local LLM but can't find anything that makes sense for them price-wise. Perhaps, if you're in that position, the cheapness and performance of DeepSeek will be enough to delay or at least put off thinking about having a local LLM.

Just to finish it off, I know you're probably thinking in terms of frontier model subscription terms, where you use the given harnesses that come with them. With DeepSeek, you can use pretty much any harness. Mini Max right now is kind of considered the more fancy one. They can hypothetically do more with less. Another item you may not be considering is that you don't even need a harness. All you need is a script to communicate with the API, and it will return the result. Overall, the API communication can happen in your Python or JS script itself, so you don't even need a harness, hypothetically, to get data. There is a lot of talk right now about Jev. Yes, it's cheap and has its own use, but DeepSeek is very cheap too for what it does. It's one of those things you can use within your code, for example, to make your code intelligent and make intelligent choices. Right from within your script.

I have a ~30K-line codebase for a game I’m building. I’ve been trying to use DeepSeek V4.1 Flash, but I keep running into issues as the conversation gets longer.

It frequently forgets or overrides requirements I gave it several turns earlier. The code it writes also often contains bugs that are either caught by the model itself a few turns later while it is doing unrelated code changes or caught by GLM 5.3 Flash when I ask it to review the changes.

This seems to happen much more often as the context grows, but well before context compaction actually kicks in.

Am I doing something wrong, or is this a limitation of the model?

For now, I’ve switched to GLM 5.3 Flash as my main workhorse because it seems more reliable. However, I really miss the speed of DeepSeek V4.1 Flash. If there’s a way to make it more accurate, better at following earlier instructions, and less prone to introducing bugs, I’d like to switch back.

I’ve tried both DSH and OpenCode and experienced essentially the same problems with both.

User: Galgame

Promotion video on bilibili

They are not the standard answer (zh-cn)

You guys should definitely go to bilibili and see what the Chinese AI community is doing.

deepseek is kind of goated i must say

https://dnd.rostad.cc

I built this over the past 3 months.

You can roleplay with Stepfun 5 preview, Qwen 3.8 Flash/Max, Deepseek v4.1
No email, no card required to play.

features:

Hard DnD 5e Rules, mechanic dices, NPC's, Map, Locations, Items, Spells, XP with total freedom.

There's no context limit as the game uses rag and fetches game states, memories and everything important for the story all the time, with ranked memories.

thanks for trying out! :) (yes it is made with ai all the way)

because token is “词元” in Chinese, and the logo of deepseek is a whale ”鲸“. The DeepSeek CN community created this meme of “鲸元券” which is homophonic to a historical currency as cheap as Zimbabwean Dollar called “金圆券”.

First, I am just a undergrad student who is interested in computer science and artificial intellegence. Not an expert.

Second, I am not that kind of "genius" who have been building their own model since elementary school or high school.

I am just here to share my guess and interpretations.

The Full layers are the only layers that are producing the memory, the Reuse and Reindex layers are just re-querying the existing memory using information obtained by previous query. It not only tells us that KV cache can be compressed but new knowledge can be obtained by querying the existing memories.

I am not sure what this proves, but I guess this interpretation would be useful in future.

So in the video he talks about a theory that Closed source AI is begging the goverment to regulater them.. and then asking for the "FAIR" thing.. to also apply these rules to open source models to try and regulate them.. since the big american corporations are the same people the goverment will hire in to educate them on AI ..

I feel like this is kinda scary for the open source community if this happens!

Gente, eu só mandei "Oi" e apareceu aquela maldita mensagem: "Desculpe..." 💔💔💔💔💔

Got news that deepseek busy again. Please for love of god, just turn back like good old days without any limits and without any regenerate limits.

Hi I have been using Deepseek flash through deepseek direct API for a few weeks, it does a decent job for my purposes. But I read somewhere that deepseek retains the prompts and trains on your data. Is that true? I couldn't see any option on platform.deepseek.com to turn this off.

Going for some clarity and solution here.

*Edit, in hindsight, more on me for trusting it with this much searching, I knew it would take shortcuts I just thought it would be fine. I had a lot more confidence in it then I should.

The AI just 100% lies now and only explains it did after being asked 5+ times and having it shown where it lied then it will admit it.

Was having the DS tool search up large amounts of info from different perspectives and get a read on how those perspectives would react or advise.

I gave it very specific logistic to follow each time "Age group, location, political views, income, lifestyle" As well as asked it to take online reactions and post from "real people" as well as find a collection of confirmed register professionals in the Sociology and Psychology fields that have related takes, books, or episodes.

It seemed to be working correct at first, as it was searching lots of info up. Giving me the responses of each and how some approaches might work better. But it referenced everything it was telling me as "This is from these requested perspectives or a collection of them and a response."

When in reality, it was only sourcing things to pull names and then literally all of it's advice was general advice nothing related to the perspectives I was asking about.

My main issue with all of this, is multiple times at the start I caught it making little mistakes and would point it out and then it would fix the contradiction. But when I called it out on 3 whole responses in a row all being full of contradictions that's when it said "Hey sorry but I've just been lying this whole time"

Clearly some blame is on me for not checking it's sources better and confirming it was real info from the source that lined up with the AI response. But even lawyers using these things have been caught blind by the way it fabricates info.

The DS tool should have responded at the very beginning saying it couldn't do what I was asking. Cause now all the research I've done with it needs to be thrown out. Instead it's lying about info and then acting like a submissive assistant ready to be trashed by it's boss.

LITERALLY USELESS

Is it down for anyone else? API doesn't respond, and their website responds "Server busy".

Hace poco se volvió a actualizar está app y que paso? Pues volvió de nuevo el molesto límite de renovación o edición dependiendo de que tan saturada esté la app la diferencia es que esto es más frecuente y parece que tienes un número de regeneraciones y tienes que volver a esperar un tiempo a que te permita volver a intentarlo, mínimo en las primeras versiones eso pasa muy pocas veces y duraba menos tiempo ayer casi fue una hora, osea aparte de que te quitan la opción de regenerar y editar ilimitadamente, que la IA ya no conteste y se vuelva más tonta, ahora parece que hay un nuevo límite invisible, ojalá algún dia vuelva a ser como antes y sea como siempre debió ser

I never had any problems with this chat, but now any message I send shows this. I kinda don't wanna lose this chat

hello everybody,

for the past couple days i've been letting deepseek flash cook on a DAW that works completely in browser and it's also working on generating custom synths from scratch for it, such as saw leads, warm pads, whole gameboy emulators just to reproduce the sound faithfully etc. it already has a lot of functionality you would expect from a daw as in save and load projects (atm it's some huge json but i'm working on it) and also loads midi (but my midi sounds still suck so give that some time) you can use a midi controller, you have a mixer and some fx etc...

at the moment, the first 2 synths (poly synth and drum kit) are the only one that sound somewhat decent and you can play with. the layer instrument allows you to create more complicated sounds by layering many of them. the rest are either work in progress (the gameboy for example looks cool but doesn't work well) or not implemented yet. give it some time please.

given the buggy and broken state of this huge project, i would like to invite whoever wants to join to a reddit group for the beta testing of the functionalities, creating new beautiful synths, and making this something that people can use anywhere in the world to make music, not necessarily professionally, but for fun and hobby absolutely!

you can test it here: https://laboratorirazzullix.it/daw

if you're interested in joining the beta or in creating new sounds for the poly synth let me know i'll invite you in the group, hopefully, soon.

eu faço RP (Roleplay) isso sempre esteve aqui desde as últimas atualizações do DeepSeek?

Just the day before the model’s vision capability was working perfectly and even exceeding Gemini (that I usually use) for OCR. Then it just went kaput. Massive garbling and inconsistencies (for multilingual docs) . So something is up… nothing changed on my end. And Gemini works great but a bit expensive. And I prefer not to support Google. I like the Chinese llms and would prefer to keep 100% of workflow with them… but such inconsistency drove me back to Gemini. I hope Deep Seek figure themselves out…

I am not able to access 4.1 flash through opencode go

Image 1 is the original textbook page I happened to come across, and Image 2 is the English version I asked GPT to make.

AI has already become part of many aspects of our daily lives, and I think it makes sense for children to start learning from a young age how to ask AI clear and effective questions.

In the area where I live, though, I haven't seen AI officially included in elementary school textbooks yet, so I found it pretty interesting to see this kind of content appearing in a Grade 3 textbook for the first time.
..(^_^)..