7 ms·

I think this is a game changer, because data privacy is a legitimate concern for many enterprise users. Btw, you can also run Mistral locally within the Docker

I think this is a game changer, because data privacy is a legitimate concern for many enterprise users. Btw, you can also run Mistral locally within the Docker model runner on a Mac.

kergonath 1y ago
> I think this is a game changer, because data privacy is a legitimate concern for many enterprise users. Indeed. At work, we are experimenting with this. Using a cloud platform is a non-starter for data confidentiality reasons. On-premise is the way to go. Also, they’re not American, which helps. > Btw, you can also run Mistral locally within the Docker model runner on a Mac. True, but you can do that only with their open-weight models, right? They are very useful and work well, but their commercial models are bigger and hopefully better (I use some of their free models every day, but none of their commercial ones).
- distances 1y ago
  I also kind of don't understand how it seems everyone is using AI for coding. I haven't had a client yet which would have approved any external AI usage. So I basically use them as search engines on steroids, but code can't go directly in or out.
  - trollbridge 1y ago
    Most my clients have the same requirement. Given the code bases I see my competition generating, I suspect other vendors are simply violating this rule.
  - fhd2 1y ago
    You might be able to get your clients to sign something to allow usage, but if you don't, as you say, it doesn't seem wise to vibe code for them. For two reasons: 1. A typical contract transfers the rights to the work. The ownership of AI generated code is legally a wee bit disputed. If you modify and refactor generated code heavily it's probably fine, but if you just accept AI generated code en masse, making your client think that you wrote it and it is therefore their copyright, that seems dangerous. 2. A typical contract or NDA also contains non disclosure, i.e. you can't share confidential information, e.g. code (including code you _just_ wrote, due to #1) with external parties or the general public willy nilly. Whether any terms of service assurances from OpenAI or Anthropic that your model inputs and outputs will probably not be used for training are legally sufficient, I have doubts. IANAL, and _perhaps_ I'm wrong about one or both of these, in one or more countries, but by and large I'd say the risk is not worth the benefit. I mostly use third party LLMs like I would StackOverflow: Don't post company code there verbatim, make an isolated example. And also don't paste from SO verbatim. I tried other ways of using LLMs for programming a few times in personal projects and can't say I worry about lower productivity with these limitations. YMMV. (All this also generally goes for employees with typical employment contracts: It's probably a contract violation.)
    - distances 1y ago
      Yes these are indeed the points. I don't really care too much, it would make me a bit more efficient but I'm billing by the hour anyway so I'm completely fine playing by the book.
      - fhd2 1y ago
        Not sure I can agree with the "I'm billing by the hour" part. I mean sure, but I think of my little agency providing value, for a price. Clients have budgets, they have limited benefits from any software they build, and in order to be competitive against other agencies or their internal teams, overall, I feel we need to provide a good bang for buck. But since it's not all that much about typing in code, and since even that activity isn't all that sped up by LLMs, not if quality and stability matters, I would still agree that it's completely fine.
        distances 1y ago
        Yes, it's important of course that I'm efficient, and I am. But my coding speed isn't the main differentiating factor why clients like me. I meant that I don't care enough to spearhead and drive this effort within the client orgs. They have their own processes, and internal employees would surely also like to use AI, so maybe they'll get there eventually. And meanwhile I'll just use it in the approved ways.
    - genghisjahn 1y ago
      What about 10 years ago when we all copied code from SO? Did we worry about copyright then? Maybe we did and I don’t recall.
      - fhd2 1y ago
        It's roughly the same, legally, and I was well aware of that. Legally speaking, you also want to be careful about your dependencies and their licenses, a company that's afraid to get sued usually goes to quite some lengths to ensure they play this stuff safe. A lot of smaller companies and startups don't know or don't care. From a professional ethics perspective, personally, I don't want to put my clients in that position unless they consciously decide they want that. They hire professionals not just to get work done they fully understand, but to a large part to have someone who tells them what they don't know.
  - mark_l_watson 1y ago
    I have good results running Ollama locally with olen models like Gemma 3, Qwen 3, etc. The major drawback is slower inference speed. Commercial APIs like Google Gemini are so much faster. Still, I find local models very much worth using after taking the time to set them up with Emacs, open-codex, etc.
  - shmel 1y ago
    How is it different from the cloud? Plenty startups store their code on github, run prod on aws, and keep all communications on gmail anyway. What's so different about LLMs?
    - jamessinghal 1y ago
      I think it's a combination of a fundamental distrust of the model makers and a history of them training on user data with and without consent. The main players all allow some form of zero data retention but I'm sure the more cautious CISO/CIOs flat out don't trust it.
      - tcoff91 1y ago
        I think that using something like Claude on Amazon Bedrock makes more sense than directly using Anthropic. Maybe I'm naive but I trust AWS more than Anthropic, OpenAI, or Google to not misuse data.
    - simion314 1y ago
      >How is it different from the cloud? Plenty startups store their code on github, run prod on aws, and keep all communications on gmail anyway. What's so different about LLMs? Those plenty startups will also use Google, OpenAi or the built in Microsoft AI. This is clearly for companies that need to keep the sensitive data under their control. I think they also get support with adding more training to the model to be personalized for your needs.
    - layer8 1y ago
      It’s not different. If you have a confidentiality requirements like that, you also don’t store your code off-premises. At least not without enforceable contracts about confidentiality with the service provider, approved by the client.
  - betterThanTexas 1y ago
    I would take any such claim with a heavy rock of salt because the usefulness of AI is going to vary drastically with the sort of work you're tasked with producing.
  - abujazar 1y ago
    You can set up your IDE to use local LLMs through e.g. Ollama if your computer is powerful enough to run a decent model.
  - crimsoneer 1y ago
    Are your clients not on AWS/Azure/GCP? They all offer private LLMs out of the box now.
    - ATechGuy 1y ago
      That was my question too.
  - Pamar 1y ago
    Personally I am trying to see if we can leverage AI to help write design documents instead of code, based on a fairly large library of human (poorly) written design documents and bug reports.
  - blitzar 1y ago
    I also kind of don't understand how it seems everyone is using AI for doing their homework. I haven't had a teacher yet which would have approved any AI usage. Same process, less people being called out for "cheating" in a professional setting.
- ATechGuy 1y ago
  Have you tried using private inference that uses GPU confidential computing from Nvidia?
- Tepix 1y ago
  premises, not premise. https://www.grammar-monster.com/easily_confused/premise_premises.htm https://www.grammar-monster.com/easily_confused/premise_prem...
- demarq 1y ago
  Also it’s like saying you can host a database on your Mac. Unless you have experience hosting and maintaining models at scale and with an enterprise feature set, then I believe what they are offering is beyond (for now) what you’d be able put up on your own.
burnte 1y ago
I have an M4 Mac Mini with 24GB of RAM. I loaded Studio.LM on it 2 days ago and had Mistral NeMo running in ten minutes. It's a great model, I need to figure out how to add my own writing to it, I want it to generate some starter letters for me. Impressive model.
ulnarkressty 1y ago
I think many in this thread are underestimating the desire of VPs and CTOs to just offload the risk somewhere else. Quite a lot of companies handling sensitive data are already using various services in the cloud and it hasn't been a problem before - even in Europe with its GDPR laws. Just sign an NDA or whatever with OpenAI/Google/etc. and if any data gets leaked they are on the hook.
- boringg 1y ago
  Good luck ever winning that one. How are you going to prove out a data leak with an AI model without deploying excessive amounts of legal spend? You might be talking about small tech companies that have no other options.
nicce 1y ago
> Btw, you can also run Mistral locally within the Docker model runner on a Mac. Efficiently? I thought macOS does not have API so that Docker could use GPU.
- jt_b 1y ago
  I haven't/wouldn't use it because I have a decent K8S ollama/open-webui setup, but docker announced this a month ago: https://www.docker.com/blog/introducing-docker-model-runner https://www.docker.com/blog/introducing-docker-model-runner
  - nicce 1y ago
    Hmm, I guess that is not actually running inside container/ there is no isolation. Some kind of new way that mixes llama.cpp , OCI format and docker CLI.
v3ss0n 1y ago
What's the point when we can run much powerful models now? Qwen3 , Deepseek
- _bin_ 1y ago
  It would be short-termist for Americans or euros to use chinese-made models. Increasing their popularity has an indirect but significant cost in the long term. china "winning AI" should be an unacceptable outcome for America or europe by any means necessary.
  - atwrk 1y ago
    Why would that be? I can see why Americans wouldn't want to do that, but Europeans? In the current political climate, where the US openly claims their desire to annex European territory and so on? I'd rather see them prefer a locally hostable open source solution like DeepSeek.
    - tigroferoce 1y ago
      My two cents, as European, is that since we are more and more asking to LLMs for information, it wouldn't be wise to let a foreign country, not even truly democratic, to choose the information we get.
      - jamesblonde 1y ago
        The Chinese don't get any of information if we use self-hosted DeepSeek or Qwen. They are open-source. You can run them in an air-gapped environment that can't phone home.
        fennecbutt 1y ago
        But their models are gimped by bad censoring. At least I can still ask chatgpt how many innocent civilians America has bombed.
simonw 1y ago
There are plenty of other ways to run Mistral models on a Mac. I'm a big fan of Mistral Small 3.1. I've run that using both Ollama (easiest) and MLX. Here are the Ollama models: https://ollama.com/library/mistral-small3.1/tags https://ollama.com/library/mistral-small3.1/tags - the 15GB one works fine. For MLX https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-Instruct-2503-8bit https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-I... and https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-Instruct-2503-4bit https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-I... should work, I use the 8bit one like this: llm install llm-mlx llm mlx download-model mlx-community/Mistral-Small-3.1-Text-24B-Instruct-2503-8bit -a mistral-small-3.1 llm chat -m mistral-small-3.1 The Ollama one supports image inputs too: llm install llm-ollama ollama pull mistral-small3.1 llm -m mistral-small3.1 'describe this image' \ -a https://static.simonwillison.net/static/2025/Mpaboundrycdfw-1.png Output here: https://gist.github.com/simonw/89005e8aa2daef82c53c2c2c62207f6a#response https://gist.github.com/simonw/89005e8aa2daef82c53c2c2c62207...
- indigodaddy 1y ago
  Simon, can you recommend some small models that would be usable for coding on a standard M4 Mac Mini (only 16G ram) ?
  - simonw 1y ago
    That's pretty tough - the problem is that you need to have RAM left over to run actual applications! Qwen 3 8B on MLX runs in just 5GB of RAM and can write basic code but I don't know if it would be good enough for anything interesting: https://simonwillison.net/2025/May/2/qwen3-8b/ https://simonwillison.net/2025/May/2/qwen3-8b/ Honestly though with that little memory I'd stick to running against hosted LLMs - Claude 3.7 Sonnet, Gemini 2.5 Pro, o4-mini are all cheap enough that it's hard to spend much money with them for most coding workflows.
    - codetrotter 1y ago
      How about on an MacBook Pro M2 Max with 64GB RAM? Any recommendations for local models for coding on that? I tried to run some of the differently sized DeepSeek R1 locally when those had recently come out, but couldn’t manage at the time to run any of them. And I had to download a lot of data to try those. So if you know a specific size of DeepSeek R1 that will work on 64GB RAM on MacBook Pro M2 Max, or another great local LLM for coding on that, that would be super appreciated
ATechGuy 1y ago
Why not use confidential computing based offerings like Azure's private inference for privacy concerns?
lolinder 1y ago
Game changer feels a bit strong. This is a new entry in a field that's already pretty crowded with open source tooling that's already available to anyone with the time and desire to wire it all up. It's likely that they execute this better than the community-run projects have so far and make it more approachable and Enterprise friendly, but just for reference I have most of the features that they've listed here already set up on my desktop at home with Ollama, Open WebUI, and a collection of small hand-rolled apps that plug into them. I can't run very big models on mine, obviously, but if I were an Enterprise I would. The key thing they'd need to nail to make this better than what's already out there is the integrations. If they can make it seamless to integrate with all the key third-party enterprise systems then they'll have something strong here, otherwise it's not obvious how much they're adding over Open WebUI, LibreChat, and the other self-hosted AI agent tooling that's already available.
- troyvit 1y ago
  > crowded with open source tooling that's already available to anyone with the time and desire to wire it all up. Those who don't have the time and desire to wire it all up probably make up a larger part of the market than those who do. It's a long-tail proposition, and that might be a problem. > I have most of the features that they've listed here already set up on my desktop at home I think your boss and your boss' boss are the audience they are going for. In my org there's concern over the democratization of locally run LLMs and the loss of data control that comes with it. Mistral's product would allow IT or Ops or whatever department to set guardrails for the organization. The selling point that it's turn-key means that a small organization doesn't have to invest a ton of time into all the tooling needed to run it and maintain it. Edit: I just re-read your comment and I do have to agree though. "game-changer" is a bit strong of a word.
abujazar 1y ago
Actually you shouldn't be running LLMs in Docker on Mac because it doesn't have GPU support. So the larger models will be extremely slow if they'll even produce a single token.
raxxorraxor 1y ago
I think the the standard setup for vscode continue for ollama is already 99% of ai coding support I need. I think it is even better than commercial offerings like cursor, at least in the projects and languages I use and have tested it. We had a Mac Studio here nobody was using and it we now use it as a tiny AI station. If we like, we could even embed our codebases, but it wasn't necessary yet. Otherwise it should be easy to just buy a decent consumer PC with a stronger GPU, but performance isn't too bad even for autocomplete.
- thepill 1y ago
  Which models are you using?
dzhiurgis 1y ago
How many is many? Literally all of them use cloud services.
Palmik 1y ago
I really don't see the big deal. Gemini also allows on-prem in similar fashion: https://cloud.google.com/blog/products/ai-machine-learning/run-gemini-and-ai-on-prem-with-google-distributed-cloud https://cloud.google.com/blog/products/ai-machine-learning/r...

I think this is a game changer, because data privacy is a legitimate concern for many enterprise users. Btw, you can also run Mistral locally within the Docker model runner on a Mac.

kergonath 1y ago

> I think this is a game changer, because data privacy is a legitimate concern for many enterprise users. Indeed. At work, we are experimenting with this. Using a cloud platform is a non-starter for data confidentiality reasons. On-premise is the way to go. Also, they’re not American, which helps. > Btw, you can also run Mistral locally within the Docker model runner on a Mac. True, but you can do that only with their open-weight models, right? They are very useful and work well, but their commercial models are bigger and hopefully better (I use some of their free models every day, but none of their commercial ones).

distances 1y ago
I also kind of don't understand how it seems everyone is using AI for coding. I haven't had a client yet which would have approved any external AI usage. So I basically use them as search engines on steroids, but code can't go directly in or out.
- trollbridge 1y ago
  Most my clients have the same requirement. Given the code bases I see my competition generating, I suspect other vendors are simply violating this rule.
- fhd2 1y ago
  You might be able to get your clients to sign something to allow usage, but if you don't, as you say, it doesn't seem wise to vibe code for them. For two reasons: 1. A typical contract transfers the rights to the work. The ownership of AI generated code is legally a wee bit disputed. If you modify and refactor generated code heavily it's probably fine, but if you just accept AI generated code en masse, making your client think that you wrote it and it is therefore their copyright, that seems dangerous. 2. A typical contract or NDA also contains non disclosure, i.e. you can't share confidential information, e.g. code (including code you _just_ wrote, due to #1) with external parties or the general public willy nilly. Whether any terms of service assurances from OpenAI or Anthropic that your model inputs and outputs will probably not be used for training are legally sufficient, I have doubts. IANAL, and _perhaps_ I'm wrong about one or both of these, in one or more countries, but by and large I'd say the risk is not worth the benefit. I mostly use third party LLMs like I would StackOverflow: Don't post company code there verbatim, make an isolated example. And also don't paste from SO verbatim. I tried other ways of using LLMs for programming a few times in personal projects and can't say I worry about lower productivity with these limitations. YMMV. (All this also generally goes for employees with typical employment contracts: It's probably a contract violation.)
  - distances 1y ago
    Yes these are indeed the points. I don't really care too much, it would make me a bit more efficient but I'm billing by the hour anyway so I'm completely fine playing by the book.
    - fhd2 1y ago
      Not sure I can agree with the "I'm billing by the hour" part. I mean sure, but I think of my little agency providing value, for a price. Clients have budgets, they have limited benefits from any software they build, and in order to be competitive against other agencies or their internal teams, overall, I feel we need to provide a good bang for buck. But since it's not all that much about typing in code, and since even that activity isn't all that sped up by LLMs, not if quality and stability matters, I would still agree that it's completely fine.
      - distances 1y ago
        Yes, it's important of course that I'm efficient, and I am. But my coding speed isn't the main differentiating factor why clients like me. I meant that I don't care enough to spearhead and drive this effort within the client orgs. They have their own processes, and internal employees would surely also like to use AI, so maybe they'll get there eventually. And meanwhile I'll just use it in the approved ways.
  - genghisjahn 1y ago
    What about 10 years ago when we all copied code from SO? Did we worry about copyright then? Maybe we did and I don’t recall.
    - fhd2 1y ago
      It's roughly the same, legally, and I was well aware of that. Legally speaking, you also want to be careful about your dependencies and their licenses, a company that's afraid to get sued usually goes to quite some lengths to ensure they play this stuff safe. A lot of smaller companies and startups don't know or don't care. From a professional ethics perspective, personally, I don't want to put my clients in that position unless they consciously decide they want that. They hire professionals not just to get work done they fully understand, but to a large part to have someone who tells them what they don't know.
- mark_l_watson 1y ago
  I have good results running Ollama locally with olen models like Gemma 3, Qwen 3, etc. The major drawback is slower inference speed. Commercial APIs like Google Gemini are so much faster. Still, I find local models very much worth using after taking the time to set them up with Emacs, open-codex, etc.
- shmel 1y ago
  How is it different from the cloud? Plenty startups store their code on github, run prod on aws, and keep all communications on gmail anyway. What's so different about LLMs?
  - jamessinghal 1y ago
    I think it's a combination of a fundamental distrust of the model makers and a history of them training on user data with and without consent. The main players all allow some form of zero data retention but I'm sure the more cautious CISO/CIOs flat out don't trust it.
    - tcoff91 1y ago
      I think that using something like Claude on Amazon Bedrock makes more sense than directly using Anthropic. Maybe I'm naive but I trust AWS more than Anthropic, OpenAI, or Google to not misuse data.
  - simion314 1y ago
    >How is it different from the cloud? Plenty startups store their code on github, run prod on aws, and keep all communications on gmail anyway. What's so different about LLMs? Those plenty startups will also use Google, OpenAi or the built in Microsoft AI. This is clearly for companies that need to keep the sensitive data under their control. I think they also get support with adding more training to the model to be personalized for your needs.
  - layer8 1y ago
    It’s not different. If you have a confidentiality requirements like that, you also don’t store your code off-premises. At least not without enforceable contracts about confidentiality with the service provider, approved by the client.
- betterThanTexas 1y ago
  I would take any such claim with a heavy rock of salt because the usefulness of AI is going to vary drastically with the sort of work you're tasked with producing.
- abujazar 1y ago
  You can set up your IDE to use local LLMs through e.g. Ollama if your computer is powerful enough to run a decent model.
- crimsoneer 1y ago
  Are your clients not on AWS/Azure/GCP? They all offer private LLMs out of the box now.
  - ATechGuy 1y ago
    That was my question too.
- Pamar 1y ago
  Personally I am trying to see if we can leverage AI to help write design documents instead of code, based on a fairly large library of human (poorly) written design documents and bug reports.
- blitzar 1y ago
  I also kind of don't understand how it seems everyone is using AI for doing their homework. I haven't had a teacher yet which would have approved any AI usage. Same process, less people being called out for "cheating" in a professional setting.
ATechGuy 1y ago
Have you tried using private inference that uses GPU confidential computing from Nvidia?
Tepix 1y ago
premises, not premise. https://www.grammar-monster.com/easily_confused/premise_premises.htm https://www.grammar-monster.com/easily_confused/premise_prem...
demarq 1y ago
Also it’s like saying you can host a database on your Mac. Unless you have experience hosting and maintaining models at scale and with an enterprise feature set, then I believe what they are offering is beyond (for now) what you’d be able put up on your own.

burnte 1y ago

I have an M4 Mac Mini with 24GB of RAM. I loaded Studio.LM on it 2 days ago and had Mistral NeMo running in ten minutes. It's a great model, I need to figure out how to add my own writing to it, I want it to generate some starter letters for me. Impressive model.

ulnarkressty 1y ago

I think many in this thread are underestimating the desire of VPs and CTOs to just offload the risk somewhere else. Quite a lot of companies handling sensitive data are already using various services in the cloud and it hasn't been a problem before - even in Europe with its GDPR laws. Just sign an NDA or whatever with OpenAI/Google/etc. and if any data gets leaked they are on the hook.

boringg 1y ago
Good luck ever winning that one. How are you going to prove out a data leak with an AI model without deploying excessive amounts of legal spend? You might be talking about small tech companies that have no other options.

nicce 1y ago

> Btw, you can also run Mistral locally within the Docker model runner on a Mac. Efficiently? I thought macOS does not have API so that Docker could use GPU.

jt_b 1y ago
I haven't/wouldn't use it because I have a decent K8S ollama/open-webui setup, but docker announced this a month ago: https://www.docker.com/blog/introducing-docker-model-runner https://www.docker.com/blog/introducing-docker-model-runner
- nicce 1y ago
  Hmm, I guess that is not actually running inside container/ there is no isolation. Some kind of new way that mixes llama.cpp , OCI format and docker CLI.

v3ss0n 1y ago

What's the point when we can run much powerful models now? Qwen3 , Deepseek

_bin_ 1y ago
It would be short-termist for Americans or euros to use chinese-made models. Increasing their popularity has an indirect but significant cost in the long term. china "winning AI" should be an unacceptable outcome for America or europe by any means necessary.
- atwrk 1y ago
  Why would that be? I can see why Americans wouldn't want to do that, but Europeans? In the current political climate, where the US openly claims their desire to annex European territory and so on? I'd rather see them prefer a locally hostable open source solution like DeepSeek.
  - tigroferoce 1y ago
    My two cents, as European, is that since we are more and more asking to LLMs for information, it wouldn't be wise to let a foreign country, not even truly democratic, to choose the information we get.
    - jamesblonde 1y ago
      The Chinese don't get any of information if we use self-hosted DeepSeek or Qwen. They are open-source. You can run them in an air-gapped environment that can't phone home.
      - fennecbutt 1y ago
        But their models are gimped by bad censoring. At least I can still ask chatgpt how many innocent civilians America has bombed.

simonw 1y ago

There are plenty of other ways to run Mistral models on a Mac. I'm a big fan of Mistral Small 3.1. I've run that using both Ollama (easiest) and MLX. Here are the Ollama models: https://ollama.com/library/mistral-small3.1/tags https://ollama.com/library/mistral-small3.1/tags - the 15GB one works fine. For MLX https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-Instruct-2503-8bit https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-I... and https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-Instruct-2503-4bit https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-I... should work, I use the 8bit one like this: llm install llm-mlx llm mlx download-model mlx-community/Mistral-Small-3.1-Text-24B-Instruct-2503-8bit -a mistral-small-3.1 llm chat -m mistral-small-3.1 The Ollama one supports image inputs too: llm install llm-ollama ollama pull mistral-small3.1 llm -m mistral-small3.1 'describe this image' \ -a https://static.simonwillison.net/static/2025/Mpaboundrycdfw-1.png Output here: https://gist.github.com/simonw/89005e8aa2daef82c53c2c2c62207f6a#response https://gist.github.com/simonw/89005e8aa2daef82c53c2c2c62207...

indigodaddy 1y ago
Simon, can you recommend some small models that would be usable for coding on a standard M4 Mac Mini (only 16G ram) ?
- simonw 1y ago
  That's pretty tough - the problem is that you need to have RAM left over to run actual applications! Qwen 3 8B on MLX runs in just 5GB of RAM and can write basic code but I don't know if it would be good enough for anything interesting: https://simonwillison.net/2025/May/2/qwen3-8b/ https://simonwillison.net/2025/May/2/qwen3-8b/ Honestly though with that little memory I'd stick to running against hosted LLMs - Claude 3.7 Sonnet, Gemini 2.5 Pro, o4-mini are all cheap enough that it's hard to spend much money with them for most coding workflows.
  - codetrotter 1y ago
    How about on an MacBook Pro M2 Max with 64GB RAM? Any recommendations for local models for coding on that? I tried to run some of the differently sized DeepSeek R1 locally when those had recently come out, but couldn’t manage at the time to run any of them. And I had to download a lot of data to try those. So if you know a specific size of DeepSeek R1 that will work on 64GB RAM on MacBook Pro M2 Max, or another great local LLM for coding on that, that would be super appreciated

ATechGuy 1y ago

Why not use confidential computing based offerings like Azure's private inference for privacy concerns?

lolinder 1y ago

Game changer feels a bit strong. This is a new entry in a field that's already pretty crowded with open source tooling that's already available to anyone with the time and desire to wire it all up. It's likely that they execute this better than the community-run projects have so far and make it more approachable and Enterprise friendly, but just for reference I have most of the features that they've listed here already set up on my desktop at home with Ollama, Open WebUI, and a collection of small hand-rolled apps that plug into them. I can't run very big models on mine, obviously, but if I were an Enterprise I would. The key thing they'd need to nail to make this better than what's already out there is the integrations. If they can make it seamless to integrate with all the key third-party enterprise systems then they'll have something strong here, otherwise it's not obvious how much they're adding over Open WebUI, LibreChat, and the other self-hosted AI agent tooling that's already available.

troyvit 1y ago
> crowded with open source tooling that's already available to anyone with the time and desire to wire it all up. Those who don't have the time and desire to wire it all up probably make up a larger part of the market than those who do. It's a long-tail proposition, and that might be a problem. > I have most of the features that they've listed here already set up on my desktop at home I think your boss and your boss' boss are the audience they are going for. In my org there's concern over the democratization of locally run LLMs and the loss of data control that comes with it. Mistral's product would allow IT or Ops or whatever department to set guardrails for the organization. The selling point that it's turn-key means that a small organization doesn't have to invest a ton of time into all the tooling needed to run it and maintain it. Edit: I just re-read your comment and I do have to agree though. "game-changer" is a bit strong of a word.

abujazar 1y ago

Actually you shouldn't be running LLMs in Docker on Mac because it doesn't have GPU support. So the larger models will be extremely slow if they'll even produce a single token.

raxxorraxor 1y ago

I think the the standard setup for vscode continue for ollama is already 99% of ai coding support I need. I think it is even better than commercial offerings like cursor, at least in the projects and languages I use and have tested it. We had a Mac Studio here nobody was using and it we now use it as a tiny AI station. If we like, we could even embed our codebases, but it wasn't necessary yet. Otherwise it should be easy to just buy a decent consumer PC with a stronger GPU, but performance isn't too bad even for autocomplete.

thepill 1y ago
Which models are you using?

dzhiurgis 1y ago

How many is many? Literally all of them use cloud services.

Palmik 1y ago

I really don't see the big deal. Gemini also allows on-prem in similar fashion: https://cloud.google.com/blog/products/ai-machine-learning/run-gemini-and-ai-on-prem-with-google-distributed-cloud https://cloud.google.com/blog/products/ai-machine-learning/r...