Grok 4 Fast now has 2M context window

Yeah, same for OpenAI because of Sama. I'm proud to say I haven't touched either for over a year. There are enough good alternatives out there.

Not defending anyone, but by that logic, you shouldn’t be using any Chinese models either.

This. I would never use Grok, and my sympathy for people who do is essentially zero. I haven’t even tried it. No matter how good it is, I would have to give money and data to a neo‑Nazi, which is an absolute no‑go.

I like grok for noncoding stuff. I find it hasn't been tuned for "Safety" (meaning it isn't tuned much for political correctness). It also seems good at making images and stories up well. I run some choose your own adventures stories with my kids through it. We tell it who each of their characters are and what the theme is for the night and grok gives them each a section of story and 4 choices. They also have the option of choosing something different then suggested. We have it so it cycles around the turns for everyone. Works pretty well, and if the kids wanna go dark (preteen boy) grok doesn't mind the violence.

Kinda reminds me of the video game from enders game.

All propietary AIs are probably biased in some way. I mean, that is the power of them and the reason they're propietary, right?

So I tend to use different LLMs from different providers, personally compare them and read between the lines.

Going off OpenRouter's rankings (https://openrouter.ai/rankings), Grok Code Fast 1 is the most used model by a significant margin, and since those metrics are calculated as of this week, that's after providers stopped giving free promotional access to it. Grok 4 Fast is #5 on that list which was never free.

In terms of models, Grok 4 Fast has essentially zero restrictions on safety, which a) makes it unusable for most applications that allow user input and b) makes it extremely useful for certain applications.

In my experience Grok Fast is the best "cheaper" model out there. Far better than Haiku 4.5 and Gemini Flash. I don't think the other cheaper models should be treated seriously at this point.

As you point out, Sam Altman is not exactly an altar boy: https://fastcompany.co.za/business/2025-11-07-sam-altmans-tr...

For at least the last year, I've been using Grok for 90% of my queries. I pay for their $30 plan as well as $20 for Claude Code, which I only use for simple development projects. For anything more complicated, Grok's expert mode has consistently better results.

I used Grok to successfully split a large 10K-line file of spaghetti code into multiple smaller well organised files. This was after giving the same task to Claude, OpenAI, and Gemini, all of which consistently failed.

Grok certainly has its uses, but I default to OpenAI for most business tasks and Claude for code.

I do! I have felt bad vibes from OpenAI for a while now, and eventually defaulted to Grok as somewhat the lesser of many evils. I respect anybody who doesn't wish to use it, but it's good enough for what I need it for. Case in point: it just spit out valid OpenSCAD code for an adapter piece I want to 3D print.

How do they make the context window longer? (serious question, I want to learn how this works)

I came here just to complain about that :-) All LLMs I used seem to give more weight to things at the beginning of the context window and omit many details. Eg. I tried this simple thing: pasted a friend's and my CV into Gemini and asked it to recommend topics for a joint conference presentation. Results depended greatly on the order of CVs pasted in.

No they can't, it's a N^2 algorithm, just fitting it in the context window is a challenge.

And sure maybe not 2mil of it is usable, but they're reliably pushing the frontier here.

Long context window = huge amounts of vacant VRAM = our servers are fucking empty

I not an expert ai user (and have never touched Codex), but anything remotely important I do, I force the smallest context window possible. I just did something very beautiful using that principle, which will soon be ready to show the world. It would have been a garbled pile of garbage with long context windows.

Obviously major architectural changes need a bigger context window. But try to aggressively modularize your tasks as much as you can, and where possible run batch jobs to keep your workflow moving while each task stays a smaller chunk.

With the current crop of LLMs/agents, I find that refactors still have to be done at a granular level. "I want to make X change. Give me the plan and do not implement it yet. Do the first thing. Do the second thing. Now update the first call site to use the new pattern. You did it wrong and I fixed it in an editor; update the second call site to match the final implementation in $file. Now do the next one. Do the next one. Continue. Continue.", etc.

This. I wouldn't pay to use it, but big context windows are amazing for programming and especially prototyping when you can keep whole codebase in context.

Gemini's 1M is amazing.

Here are the 5 steps of denial:

1. It's not better.

2. It's better but it doesn't matter.

3. It matters but people wouldn't use it.

4. People use it but I wouldn't use it.

5. Ok, I use it but you sir are racist!

We are at around number 2 and 3.

It's probably because lots of people here resent their difference in personal ideology with Elon Musk.

Seems reductive. Some applications require higher context length or fast tokens/s. Consider it a multidimensional Pareto frontier you can optimize for.

Depends. For coding at least, you can divide tasks into high-intelligence ($$$) and low-intelligence ($) tasks. Being able to do low-intelligence tasks super fast and cheap would be quite beneficial. A majority of code edits would fall into the fast-and-cheap subset.