That's true but a similar advice that is given to junior developers in their early career is to actually reinvent the wheel, so that they can learn from the pain and then rip the profits of using reusable components. That's unvaluable. You have to read through thousands of lines of code and write some more yourself to get good at programming.

Sad that the model is not open.

Finally, I have a bit of a grudge against the naming Mistral gives to their models. This is Voxtral 3, right? Instead of appending the variations at the end consistently, they just do this:

Voxtral Mini Transcribe 3 (batch), Voxtral Mini Transcribe Realtime 3, Voxtral Small Transcribe 3, Voxtral Speech 3 (batch and realtime, same API)

Why not Voxtral 3 Transcribe Mini (batch), Voxtral 3 Transcribe Realtime, Voxtral 3 Transcribe Small, Voxtral 3 Speech. Then it reads more like it's layered, like it should be.

Old man yelling at cloud

I am especially interested in this part. Could you please share the prompt you are using to instruct the LLM to clean up the dictation? Thanks in advance!

> [...] I also completely maxed out two subscriptions [...]

TIL that Mistral provides hosted GLM-5.3 and that it has a subscription model as well.

> Not being able to stack subs is my biggest gripe with Mistral.

If you were to use a gateway like GoModel[1] then you could use Virtual Models[2] to load balance across the subscriptions. For that to work, though, you would have to register the same provider as many times as subscriptions you have. It can all be defined in code, so you'd only have to do this once.

[1] https://github.com/ENTERPILOT/GoModel

[2] https://gomodel.enterpilot.io/docs/features/virtual-models#l...

EDIT: formatting

- https://github.com/ENTERPILOT/GoModel - https://github.com/maximhq/bifrost - https://github.com/BerriAI/litellm

Would you care to share what makes experiential different?

In this case you are placing your trust in OpenAI and Anthropic. I'm not sure about Anthropic but OpenAI has changed their mission corpus quite a lot from its humble beginnings that it results hard to trust them when they say they don't use your stuff to further train their models. If I'm a Big Corp with enough lawyers to putnup a fight, I would then feel ok with such clause, but being a small guy, who is going to defend me when the truth comes out that they have been training their models with my data? Similar fiasco as with Facebook, who had claimed they didn't sell your data, even though they were.

That's where I'm coming from with all this "trust us, we don't train our models with your data". At least this Chinese company is being upfront about it.

Can you please elaborate what you mean by "critical market"?

Edit: formatting

There are packages for Vulkan, ROCm and CUDA. They all work.

I have had the chance to test the main Chinese models through OpenRouter but the Pay-as-you-go model is expensive compared to a subscription model, but I don't want to marry to a single provider.

Thanks for bringing OpenCode Go to my attention. Your comparison is the research I didn't know I needed, and I will be cancelling my Copilot subscription to replace it with OpenCode Go right away.

> when they take that tone with you.

This makes it sound as if you took it personally?