For those not trying, this allows Deepseek to understand a picture (instead of just extracting text from it), and it can describe what's in the picture, but this is not an image generation system, so you can't ask it to modify an image.
Personally, I'm a bit surprised the DS chat app still doesn't offer its own text to speech and speech to text features (I know DS doesn't have any ASR model for example, but there are quite a few in the open).
DeepSeek interpreting screenshots and images I send it at fractions of what I pay Claude and ChatGPT, for me, is of far higher priority than supporting dictation. There are workarounds for dictation but not image processing.
Can you explain what the benefits are of actually "talking" with the bot instead of typing and reading?
As someone who would rather send a slack message to a coworker rather than actually walking over and talk to them, the idea of having to talk with my laptop is not appealing at all, haha.
One problem has been ChatGpt/Claude apps don’t really do this well. They use weak and/or non-reasoning models for voice interaction and the UX is not optimized for hands free.
I wrote an iOS chatbot app mainly for this purpose for myself and family/friends. Allows starting/sending voice prompts with the action button so I never have to look at the screen. Supports any model at any reasoning level so conversations are not dumbed down. Added a video transcription tool so any model can “read” YouTube/Tiktok videos and chat about them. Great to discuss lectures on tech topics.
It takes slightly longer to use a reasoning model for voice interaction use but I prefer the intelligence. The latency can be minimized a few ways, bidirectional streaming helps. It’s TTS agnostic, I’ve got a few selectable providers and the output can be prompt styled “use a chill tone that’s not too eager”.
If you spend your life sitting in a chair, that's fine. I tend to get all kinds of ideas, questions, and research needs while I'm walking around. Typing a paragraph or two or context takes too much time and is very risky. Especially when driving. But also just walking, cooking, cleaning, etc. Sometimes it's just not practical - winter, carrying stuff... I mostly feel privileged if I can just sit at a computer and type my question and have the time to read the answer.
I hardly type at all now. I use Handy (free) with Parakeet and use its post-LLM processing feature with a custom prompt tailored towards coding, so I can say things like "Have it go to slash remote dash control" and it'll output "/remote-control". Converts brackets, etc.
Everything is almost instant, it's insanely fast, and lets me work on multiple different agents/windows at the same time fast with cmux.
I use the same thing to talk to people on Slack, iMessage, etc now when I'm working from home instead of typing.
I also can help articulate my thoughts better when I'm thinking them literally out loud instead of just sitting silent and typing them on a computer for hours.
It's just something that you need to try and get used to because I also thought it was something I wouldn't like at first.
I am someone that prefers a slack message to a coworker than talking to them and I use AI.
My current flow is: Google Eloquent to capture 127WPM (my typing is best case is 65wpm). This lets me get the thoughts out without thinking too much about structure or flow, the same way I would brain-dump type it.
Next I use AI to compress, summarize, and restructure to create a clear coherent message for my peer to read (which is way faster for them).
When communicating with AI, its the same thing, except I skip the second step since AI does a good job at understanding my ramblings.
----
It drives me crazy that some cultures only send voice messages to each other. It drives me crazy they can't be respectful of my time and use STT+AI to convert their 90 second monologue to a few written sentences.
I would find this behavior extremely aggravating from a co-worker. If you can’t be bothered to edit down your ramblings by hand, just don’t send me anything at all.
Slightly off-topic but: does it concern you that you're letting atrophy a very important skill for human communication (organising your thoughts and ideas, and then clearly communicating them to others)?
As someone who's still learning English, this is one thing I'd never use AI for, at least not in the near future, simply because thinking and structuring my thoughts before typing is the same as it is before speaking and actually talking to other people can't be outsourced to AI.
But I imagine if I'd been a native speaker I wouldn't mind using AI like OC does since it's a convenience. Same way I use a calculator for two digit multiplications in real life but spent years learning to do it manually in school.
> It drives me crazy they can't be respectful of my time and use STT+AI to convert their 90 second monologue to a few written sentences.
I have used Whisper to transcribe audio into text in the past. You could probably build a pipeline for that, whether running locally or in the cloud - and the run the transcription through the same summarization agent.
I thought this way until I tried it, and the main difference is that when I'm managing tons of agents at once or just reviewing some plan / approving next steps, or need to give quick feedback/ask a simple followup, the voice interface makes me much faster and more likely to continue because it's lower friction (and in many cases that's good, though not all) and can be hands-free.
Actually, my thoughts on this matter changed so much that it inspired me to get much more into voice controls because I realized how this same problem was basically why some people sucked at remote work or weren't able to properly use tools like claude code, because it was essentially the same problem but worse (typing / messaging feeling too high-friction or raising the barrier for participation). I have a way to let Claude call me now to tell me stuff when I have a bunch of instances out doing stuff and then leave to go home.
I'm trying to get that better integrated in my devloop because I think it makes managing >4 agents simultaneously much more feasible and natural for some people (I used to play Starcraft a lot so I'm used to the multitasking, but it still takes sustained willpower to be constantly "driving" or monitoring things, or to field questions), especially ones who have never served as TLs or people managers before. IMO it's a big performance roadblock for a lot of developers to be treat directing multiple agents simultaneously as some kind of high-stakes/high-cost thing. The kind of developer who would not say anything in a team meeting unless prompted or who thinks everything is stupid by default (because they are afraid of making decisions / being wrong even if only briefly) is both very common and reluctant to work this way, but also really probably needs it to be as productive as more skilled developers.
I don't know about you, but I force myself to read the whole spaghetti thought process of any AI that's actually working on code, and make sure I understand what the hell it just said before I ask questions or give it a green light. Even or especially when whatever it said is full of fluffy stuff about having understood the problem space. That's usually where a well-placed question can bring the entire structure crashing down.
"You're right to push back" has become the gold standard phrase I'm looking for from these things to assure myself that I'm covering all the bases and understanding what it's building (not that that's enough, and not that it isn't still going to build some ungodly blob anyway).
I kinda like using voice to jot down my next questions or iterate on things, but there's a clear danger to it, which is that you may inadvertently be signing off on stuff you haven't thoroughly read. If there's one thing about LLM-written code, it's that the devil is in the details.
I type as fast as I talk so for majority of my LLM usage I don't need text to speech.
But I love the chatgpt voice interface e.g. on a long drive when I can use it to learn about random stuff (btw, turn advanced voice off for such usage).
Other part though is, hacker news vs regular population, majority of which would much much rather talk and listen than type and read.
I've been using ChatGTP by voice for things like cooking and house repair stuff. It's quite convenient for situations in which your hands are busy.
Other week I fixed a a water valve. After planning the thing with ChatGTP I brought the new valve. Then I described what I was seeing as I swapped the old valve for the new one to make sure everything was right. Really cool experience!
When I was still using OpenAI, I used it among other things to translate from English to Spanish while talking to Spanish-speaking people in person.
I understand a bit Spanish but I don’t speak Spanish yet, and they don’t speak English.
I speak English to the AI and end with “translate to Spanish, translation only”, and then the AI says the thing I was saying in Spanish (not perfect but good enough, and also it has a slightly weird accent that might be it using English or English influenced text to speech even when speaking Spanish sentences?).
This may sound strange and even callous, but I think it's appealing to people who are used to having employees. It's not about speech being a better interface, it's that thinking hard enough to sit down and compose a prompt is too much work if you're used to just yelling at someone.
Pity the managers with no one left to boss around besides the machines coming for their own jobs.
I was asked just yesterday if I could wire up [redacted] so that [redacted profession] could have a realtime voice interface while in the middle of performing [redacted]. My basic answer was yes, but it would be a bit slower than you want if something is going wrong, and it would probably be unethical for a whole lot of reasons.
it's very confusing. maaaybe if the stt is good and fast enough, speaking may be faster? english speakers can probably hit 150-180 wpm but seems like a hassle
It's easier, faster, and more natural to talk than to type for the vast, vast majority of people.
This trivial fact of life is observed every day by e.g.:
- students taking notes and finding it necessary to only jot down key facts so that they can keep up,
- stenographers who require special training and equipment to keep up verbatim with live speech in the courtroom,
- annoying colleagues who insist on "hopping on a quick call" or arranging big, wasteful, and disruptive meetings instead of just writing down their problem / sending a message or email,
- friends who insist on sending short voice messages in DMs instead of typing, because it's more "personal" that way (which to be fair it is, but not to the extent proclaimed).
If so, would other models like ChatGPT benefit from translating the user's prompt to Chinese/Japanese and thinking in Hanzi/Kanji and then converting the response back to the user's language before displaying it?
I believe that most reasoning models actually think in their own "language" which is not really understandable by humans. The thinking traces that are shown in the UI are actually summaries generated by a smaller model in plain english (or user language). Sometimes this leaks through and you see some chinese/japanese characters in e.g. Claude's reasoning.
Wait, this isn't real, is it? Is there actually an intermediate model that translates DeepSeek's thinking from its "alien language" into human languages? That's not actually the case, right?
I thought "thinking" is literally the model generating additional text in a human language that shows its "thought process". It's added to the model's context, which helps it reason better because it now has this self-generated context.
The "their own language" idea seems to come from some recent science fiction where LLMs develop their alien language and take over the world by 2037 or something.
The parent is off, you’re right. They may reason in any language, typically whatever the user’s language is, and you’ll see the reasoning directly with an open model like Deepseek.
Research only showed that thinking might be disconnected from the final output but in my experience they are very strongly correlated in recent models
Yeah, it's actually the case. Researchers have shown that the models response doesn't always follow from the reasoning. Whether you consider that an internal language or not really depends on what you're speculating the neural network is doing. I think there was an Antropic paper on it.
You're right, it's just additional text that allows it to do thinking / reasoning-like behavior. The big proprietary models hide the real output from the user and instead provide a friendly abridged version, but that's just to protect their secret sauce from distillation.
As far as I'm aware, it's not true for models like DeepSeek or other Chinese open-weight models (at least those that I have seen); their reasoning traces are fully composed from some human language, be it English, Chinese or another one; by the way, most of them can adapt their reasoning based on user language, for example, if user speaks English the reasoning more likely will be in English.
I think that for DeepSeek problem (thinking and replying in Chinese) everything is kinda simpler: in their official chat, they're probably using some kind of system prompt which is (probably) written in Chinese, so that's why model may prefer Chinese in it's output.
I have seen mixed language thinking from claude when i speak to it in english but we are discussing a product thats in spanish or searching amazon spain.
Summaries by different smaller models are usually made by closed proprietary models like Claude as a way to combat the distillation of real reasoning traces by competitors. Open weight models show the real reasoning traces. Reasoning traces operate in the same space as the non-reasoning output. It's all just one large text for an LLM. Internally, reasoning is just ordinary chat completion between <think></think> tags.
But why does it do so inconsistently, and sometimes even forgetting to swap back to English when it comes time to do 'normal' output? It also seems recent, as when I was using deepseek even a week ago this was very rare compared to what I was seeing yesterday. I had to start including a line asking it to stay to English because I can only speak/read English.
Are you running out of context? I’ve found that tooling and giberish most of the time happens when I’m butting up against the high watermark of my context window. One other thing it could be, I’ve read that lower quanta like Q1 and Q2 for smaller models can leak Chinese
Could go nicely with https://auge.franzai.com/ ( CLI on Apple Vision frameworks ) - do the first pass locally. If needed call their API for a more detailed analysis and then _finally_ we produce meaningful alt texts for images in HTML at a reasonable price ;)
Turns out, to use Claude Agents SDK, you need to have a vision enabled API. If Deepseek API could see, it can fully drive Claude Code and Claude Agents SDK. A project I'm working on relies on a Claude-in-CloudflareWorker setup and I've been relying on Qwen and gemini flash lite, both more expensive than Deepseek.
same here. I am using Gemini 2.5 Flash as VSCode "vision proivder" for Deepseek V4 Pro, but it is expensive and not accurate. can't wait for native Deepseek vision.
If they'd do one of those little extraneous additions like Qwen does, so that I can have DS4 Flash with Vision that would be great. I've got to run a separate model entirely so that I can get vision and I'd prefer to just put it all in one space.
And it's really good and fast. Have tested with bunch of odd photos on what is happening. Overall the training set seems large enough to know what's what and where
Is that before or after the OpenAI and Anthropic pay off all the people and companies who's copyrights were violated when they used their works for free to train their models?
in other comments, you're arguing for banning deepseek because it is "against democratic capitalism." And here you are, arguing for governments to protect domestic companies against foreign competition.
Competition is a good thing sometimes. It forces companies to innovate.
Of course, organizations like ycombinator gave that up many years ago. Now our industry is mask-off about their desire to create monopolies so they can collect exorbitant rents.
If everything goes to plan everyone involved with big US models will be trillionaire and everyone else will poor and unemployed. If there are open and cheap to run Chinese models (and please god silicon) the financial house of cards that we have build will fall, people involved with big US models will be poor and unemployed, and everyone else will be slightly less poor and unemployed than in the first scenario.
How so? Everyone would still have their skills to provide goods and services and everyone would still have wants for other's goods and services, so an economy would still run. AI can shift the economy but it doesn't lock the entire population out of the economy. It can lock out any one group because everyone else gets the good/services of that group for cheaper from the AI, but if everyone else can't afford the AI, if the AI locks everyone out, then they trade between themselves instead. And that is the sort of 'worst case possible' outcome, not even what is likely to happen as the AI makes some things much cheaper.
For those not trying, this allows Deepseek to understand a picture (instead of just extracting text from it), and it can describe what's in the picture, but this is not an image generation system, so you can't ask it to modify an image.
Personally, I'm a bit surprised the DS chat app still doesn't offer its own text to speech and speech to text features (I know DS doesn't have any ASR model for example, but there are quite a few in the open).
Also vision can be used for "compaction" https://blog.can.ac/2026/06/10/snapcompact/
DeepSeek interpreting screenshots and images I send it at fractions of what I pay Claude and ChatGPT, for me, is of far higher priority than supporting dictation. There are workarounds for dictation but not image processing.
Can you explain what the benefits are of actually "talking" with the bot instead of typing and reading?
As someone who would rather send a slack message to a coworker rather than actually walking over and talk to them, the idea of having to talk with my laptop is not appealing at all, haha.
It’s crucial to use for driving/walking.
One problem has been ChatGpt/Claude apps don’t really do this well. They use weak and/or non-reasoning models for voice interaction and the UX is not optimized for hands free.
I wrote an iOS chatbot app mainly for this purpose for myself and family/friends. Allows starting/sending voice prompts with the action button so I never have to look at the screen. Supports any model at any reasoning level so conversations are not dumbed down. Added a video transcription tool so any model can “read” YouTube/Tiktok videos and chat about them. Great to discuss lectures on tech topics.
It takes slightly longer to use a reasoning model for voice interaction use but I prefer the intelligence. The latency can be minimized a few ways, bidirectional streaming helps. It’s TTS agnostic, I’ve got a few selectable providers and the output can be prompt styled “use a chill tone that’s not too eager”.
If you spend your life sitting in a chair, that's fine. I tend to get all kinds of ideas, questions, and research needs while I'm walking around. Typing a paragraph or two or context takes too much time and is very risky. Especially when driving. But also just walking, cooking, cleaning, etc. Sometimes it's just not practical - winter, carrying stuff... I mostly feel privileged if I can just sit at a computer and type my question and have the time to read the answer.
I hardly type at all now. I use Handy (free) with Parakeet and use its post-LLM processing feature with a custom prompt tailored towards coding, so I can say things like "Have it go to slash remote dash control" and it'll output "/remote-control". Converts brackets, etc.
Everything is almost instant, it's insanely fast, and lets me work on multiple different agents/windows at the same time fast with cmux.
I use the same thing to talk to people on Slack, iMessage, etc now when I'm working from home instead of typing.
I also can help articulate my thoughts better when I'm thinking them literally out loud instead of just sitting silent and typing them on a computer for hours.
It's just something that you need to try and get used to because I also thought it was something I wouldn't like at first.
I am someone that prefers a slack message to a coworker than talking to them and I use AI.
My current flow is: Google Eloquent to capture 127WPM (my typing is best case is 65wpm). This lets me get the thoughts out without thinking too much about structure or flow, the same way I would brain-dump type it.
Next I use AI to compress, summarize, and restructure to create a clear coherent message for my peer to read (which is way faster for them).
When communicating with AI, its the same thing, except I skip the second step since AI does a good job at understanding my ramblings.
----
It drives me crazy that some cultures only send voice messages to each other. It drives me crazy they can't be respectful of my time and use STT+AI to convert their 90 second monologue to a few written sentences.
I would find this behavior extremely aggravating from a co-worker. If you can’t be bothered to edit down your ramblings by hand, just don’t send me anything at all.
Slightly off-topic but: does it concern you that you're letting atrophy a very important skill for human communication (organising your thoughts and ideas, and then clearly communicating them to others)?
As someone who's still learning English, this is one thing I'd never use AI for, at least not in the near future, simply because thinking and structuring my thoughts before typing is the same as it is before speaking and actually talking to other people can't be outsourced to AI.
But I imagine if I'd been a native speaker I wouldn't mind using AI like OC does since it's a convenience. Same way I use a calculator for two digit multiplications in real life but spent years learning to do it manually in school.
> It drives me crazy they can't be respectful of my time and use STT+AI to convert their 90 second monologue to a few written sentences.
I have used Whisper to transcribe audio into text in the past. You could probably build a pipeline for that, whether running locally or in the cloud - and the run the transcription through the same summarization agent.
What did you do prior to 2023?
I thought this way until I tried it, and the main difference is that when I'm managing tons of agents at once or just reviewing some plan / approving next steps, or need to give quick feedback/ask a simple followup, the voice interface makes me much faster and more likely to continue because it's lower friction (and in many cases that's good, though not all) and can be hands-free.
Actually, my thoughts on this matter changed so much that it inspired me to get much more into voice controls because I realized how this same problem was basically why some people sucked at remote work or weren't able to properly use tools like claude code, because it was essentially the same problem but worse (typing / messaging feeling too high-friction or raising the barrier for participation). I have a way to let Claude call me now to tell me stuff when I have a bunch of instances out doing stuff and then leave to go home.
I'm trying to get that better integrated in my devloop because I think it makes managing >4 agents simultaneously much more feasible and natural for some people (I used to play Starcraft a lot so I'm used to the multitasking, but it still takes sustained willpower to be constantly "driving" or monitoring things, or to field questions), especially ones who have never served as TLs or people managers before. IMO it's a big performance roadblock for a lot of developers to be treat directing multiple agents simultaneously as some kind of high-stakes/high-cost thing. The kind of developer who would not say anything in a team meeting unless prompted or who thinks everything is stupid by default (because they are afraid of making decisions / being wrong even if only briefly) is both very common and reluctant to work this way, but also really probably needs it to be as productive as more skilled developers.
I don't know about you, but I force myself to read the whole spaghetti thought process of any AI that's actually working on code, and make sure I understand what the hell it just said before I ask questions or give it a green light. Even or especially when whatever it said is full of fluffy stuff about having understood the problem space. That's usually where a well-placed question can bring the entire structure crashing down.
"You're right to push back" has become the gold standard phrase I'm looking for from these things to assure myself that I'm covering all the bases and understanding what it's building (not that that's enough, and not that it isn't still going to build some ungodly blob anyway).
I kinda like using voice to jot down my next questions or iterate on things, but there's a clear danger to it, which is that you may inadvertently be signing off on stuff you haven't thoroughly read. If there's one thing about LLM-written code, it's that the devil is in the details.
Faster, and that's it. If you don't need precision (like with prompting LLMs) the speed gain is massive (*for most people)
I type as fast as I talk so for majority of my LLM usage I don't need text to speech.
But I love the chatgpt voice interface e.g. on a long drive when I can use it to learn about random stuff (btw, turn advanced voice off for such usage).
Other part though is, hacker news vs regular population, majority of which would much much rather talk and listen than type and read.
I like to talk (stt) but I don't want tts to talk back to me I just want to read the response. voice synthesis is a waste for me personally.
I've been using ChatGTP by voice for things like cooking and house repair stuff. It's quite convenient for situations in which your hands are busy.
Other week I fixed a a water valve. After planning the thing with ChatGTP I brought the new valve. Then I described what I was seeing as I swapped the old valve for the new one to make sure everything was right. Really cool experience!
I can talk faster than I can type.
When I was still using OpenAI, I used it among other things to translate from English to Spanish while talking to Spanish-speaking people in person.
I understand a bit Spanish but I don’t speak Spanish yet, and they don’t speak English.
I speak English to the AI and end with “translate to Spanish, translation only”, and then the AI says the thing I was saying in Spanish (not perfect but good enough, and also it has a slightly weird accent that might be it using English or English influenced text to speech even when speaking Spanish sentences?).
This may sound strange and even callous, but I think it's appealing to people who are used to having employees. It's not about speech being a better interface, it's that thinking hard enough to sit down and compose a prompt is too much work if you're used to just yelling at someone.
Pity the managers with no one left to boss around besides the machines coming for their own jobs.
I was asked just yesterday if I could wire up [redacted] so that [redacted profession] could have a realtime voice interface while in the middle of performing [redacted]. My basic answer was yes, but it would be a bit slower than you want if something is going wrong, and it would probably be unethical for a whole lot of reasons.
Accessibility.
What about accuracy?
I'd imagine it'd be a reasonable tradeoff for disabled people who can't use their hands.
Much faster and better flow. Don't knock it til you've tried it.
it's very confusing. maaaybe if the stt is good and fast enough, speaking may be faster? english speakers can probably hit 150-180 wpm but seems like a hassle
It's easier, faster, and more natural to talk than to type for the vast, vast majority of people.
This trivial fact of life is observed every day by e.g.:
- students taking notes and finding it necessary to only jot down key facts so that they can keep up,
- stenographers who require special training and equipment to keep up verbatim with live speech in the courtroom,
- annoying colleagues who insist on "hopping on a quick call" or arranging big, wasteful, and disruptive meetings instead of just writing down their problem / sending a message or email,
- friends who insist on sending short voice messages in DMs instead of typing, because it's more "personal" that way (which to be fair it is, but not to the extent proclaimed).
Points to https://chat.deepseek.com/sign_in for me, that's just a login screen. Anything page with some info?
Not in official news yet, but works for me https://files.catbox.moe/hnnnlx.png
Only images or videos as well?
OP made a mistake, confused HN and https://www.reddit.com/r/DeepSeek .
What has been going on with deepseek recently? I have gotten lots of replies in Chinese and even more frequently, reasoning in Chinese as well.
Is it a new silent update?
Happened to me with Claude, doesn't need to be a China thing.
Well, it is a Chinese model, maybe it thinks better in Chinese?
Hànzì can use 30%-40% fewer tokens than English. So, yes, it probably thinks better in Chinese.
If so, would other models like ChatGPT benefit from translating the user's prompt to Chinese/Japanese and thinking in Hanzi/Kanji and then converting the response back to the user's language before displaying it?
I believe that most reasoning models actually think in their own "language" which is not really understandable by humans. The thinking traces that are shown in the UI are actually summaries generated by a smaller model in plain english (or user language). Sometimes this leaks through and you see some chinese/japanese characters in e.g. Claude's reasoning.
Wait, this isn't real, is it? Is there actually an intermediate model that translates DeepSeek's thinking from its "alien language" into human languages? That's not actually the case, right?
I thought "thinking" is literally the model generating additional text in a human language that shows its "thought process". It's added to the model's context, which helps it reason better because it now has this self-generated context.
The "their own language" idea seems to come from some recent science fiction where LLMs develop their alien language and take over the world by 2037 or something.
The parent is off, you’re right. They may reason in any language, typically whatever the user’s language is, and you’ll see the reasoning directly with an open model like Deepseek.
Research only showed that thinking might be disconnected from the final output but in my experience they are very strongly correlated in recent models
Yeah, it's actually the case. Researchers have shown that the models response doesn't always follow from the reasoning. Whether you consider that an internal language or not really depends on what you're speculating the neural network is doing. I think there was an Antropic paper on it.
You're right, it's just additional text that allows it to do thinking / reasoning-like behavior. The big proprietary models hide the real output from the user and instead provide a friendly abridged version, but that's just to protect their secret sauce from distillation.
As far as I'm aware, it's not true for models like DeepSeek or other Chinese open-weight models (at least those that I have seen); their reasoning traces are fully composed from some human language, be it English, Chinese or another one; by the way, most of them can adapt their reasoning based on user language, for example, if user speaks English the reasoning more likely will be in English.
I think that for DeepSeek problem (thinking and replying in Chinese) everything is kinda simpler: in their official chat, they're probably using some kind of system prompt which is (probably) written in Chinese, so that's why model may prefer Chinese in it's output.
I have seen mixed language thinking from claude when i speak to it in english but we are discussing a product thats in spanish or searching amazon spain.
Summaries by different smaller models are usually made by closed proprietary models like Claude as a way to combat the distillation of real reasoning traces by competitors. Open weight models show the real reasoning traces. Reasoning traces operate in the same space as the non-reasoning output. It's all just one large text for an LLM. Internally, reasoning is just ordinary chat completion between <think></think> tags.
> summaries generated
Or hallucinated
There are other even more efficient ways of doing this, i.e. using images instead of raw text https://xcancel.com/karpathy/status/1980397031542989305?lang...
Yeah, it’s why the Caveman skill includes a Wenyan mode.
https://github.com/JuliusBrussee/caveman
But why does it do so inconsistently, and sometimes even forgetting to swap back to English when it comes time to do 'normal' output? It also seems recent, as when I was using deepseek even a week ago this was very rare compared to what I was seeing yesterday. I had to start including a line asking it to stay to English because I can only speak/read English.
A chinese model which tells me it is Claude from Anthropic? Not really. Chinese HW yes, SW not.
Google Chrome tells me it's like 14 different things. How is that any different then DeepSeek saying it is Claude?
I guess Claude isn’t an American model either considering how Anthropic has fed basically all of the globe into it.
This happens to me a lot when I ask a qwen3.6 model to respond to a question in JSON. No clue why.
Maybe, you could pipe it through T5 or something.
I use DeepSeek daily, never happened to me.
I use the API however, not the chat interface.
It doesn’t seem that recent to me, at least been like that for six months.
yes, kind of silent update plus they might have better chinese datasets and user data for their training, that might be leading to chinese preference.
it's a hint that you should start learning the new Lingua Franca.
Are you running out of context? I’ve found that tooling and giberish most of the time happens when I’m butting up against the high watermark of my context window. One other thing it could be, I’ve read that lower quanta like Q1 and Q2 for smaller models can leak Chinese
It never happened to me with Deepseek, but it happened multiple times with Kimi 2.6.
It also happened a handful of times with Anthropic models.
Could go nicely with https://auge.franzai.com/ ( CLI on Apple Vision frameworks ) - do the first pass locally. If needed call their API for a more detailed analysis and then _finally_ we produce meaningful alt texts for images in HTML at a reasonable price ;)
I wonder what it has to say for the Tank Man image.
I heard it would just refuse to talk about that incident.
I really need this as an API.
Turns out, to use Claude Agents SDK, you need to have a vision enabled API. If Deepseek API could see, it can fully drive Claude Code and Claude Agents SDK. A project I'm working on relies on a Claude-in-CloudflareWorker setup and I've been relying on Qwen and gemini flash lite, both more expensive than Deepseek.
Can't wait to have it available on deepseek.
Xiaomi Mimo v2.5 is my favorite alternative. Matches DS v4 Flash (official) pricing exactly and supports image/audio/video input.
same here. I am using Gemini 2.5 Flash as VSCode "vision proivder" for Deepseek V4 Pro, but it is expensive and not accurate. can't wait for native Deepseek vision.
Have you looked at MiniMax or MiMo? Available today via OpenRouter, and it’ll make the path to porting to DeepSeek a line change https://openrouter.ai/collections/vision-models
I wish they published a post where we read about capabilities, quality, accuracy and other parameters
Multi-Modal is the way to go. Deepmind nailed this a long back.
Deepmind hasn't produced any frontier model since Gemini 3.0 pro though.
Direct competition to american companies like OpenAi, Anthropic proving china can also launch great models
If they'd do one of those little extraneous additions like Qwen does, so that I can have DS4 Flash with Vision that would be great. I've got to run a separate model entirely so that I can get vision and I'd prefer to just put it all in one space.
Maybe they will do now as they got huge funding.
I already had it for months? What's the news here?
And it's really good and fast. Have tested with bunch of odd photos on what is happening. Overall the training set seems large enough to know what's what and where
yes and I hope their rate of shipping increases after recent funding.
Vision has been in A/B testing for a while now (at least in China). Is there an official announcement that this will be available for everyone?
I haven't seen any official announcement yet, works for me though.
Nice, is this available in the API now as well?
I am also waiting on the vision support in API. Its the only thing blocking me from buying their subscription.
What subscription?
I mean't topup. They don't have subsciptions.
Not in the api yet.
Does the api support vision yet?
No announcements about it yet.
That makes sense. I haven’t found it work in api yet.
what is more interesting to me is why it takes so long for them to support vision.
does it implies that Liang believes vision/voice is less important on its way to AGI?
Might be compute bottleneck due to the US chips act and migrating to Huawei ecosystem.
Just wait until they release their coding model. Once they do an Opus-level coding model, the sandcastle of the AI economy in the US will fall
They had deepseek-coder.
Yeah but it wasnt close to Opus etc. Still a good local model when it released
OpenAI and Anthropic need to get this free foreign competition banned.
Is that before or after the OpenAI and Anthropic pay off all the people and companies who's copyrights were violated when they used their works for free to train their models?
At least DeepSeek freely gives back the benefits.
in other comments, you're arguing for banning deepseek because it is "against democratic capitalism." And here you are, arguing for governments to protect domestic companies against foreign competition.
Competition is a good thing sometimes. It forces companies to innovate.
Of course, organizations like ycombinator gave that up many years ago. Now our industry is mask-off about their desire to create monopolies so they can collect exorbitant rents.
Care to expand on why? Or did you forgot the /s at the end?
I feel like '/s' has ruined irony on the internet. Irony is at its best if left ambiguous, lol.
Too many people have said too many stupid things entirely seriously.
Nah, they're serious actually!
Wait, did that need a /s?
If everything goes to plan everyone involved with big US models will be trillionaire and everyone else will poor and unemployed. If there are open and cheap to run Chinese models (and please god silicon) the financial house of cards that we have build will fall, people involved with big US models will be poor and unemployed, and everyone else will be slightly less poor and unemployed than in the first scenario.
What is good for Dario is good for America.
>and everyone else will poor and unemployed
How so? Everyone would still have their skills to provide goods and services and everyone would still have wants for other's goods and services, so an economy would still run. AI can shift the economy but it doesn't lock the entire population out of the economy. It can lock out any one group because everyone else gets the good/services of that group for cheaper from the AI, but if everyone else can't afford the AI, if the AI locks everyone out, then they trade between themselves instead. And that is the sort of 'worst case possible' outcome, not even what is likely to happen as the AI makes some things much cheaper.
Why do you think it’s free?
Any ideas, theories where they get their payoff?
But it's not free, unless you also call Claude free just because it has a free tier.
Yes, subscription options they sell on deepseek.com