Grok 4 Fast

Pricing is really good for this benchmark value. Let’s see how it holds against people testing it.

A faster model that outperforms its slower version on multiple benchmarks? Can anyone explain why that makes sense? Are they simply retraining on the benchmark tests?

> Can anyone explain why that makes sense?

Can be anything from different arch, more data, RL, etc. It's probably RL. In recent months top tier labs seem to have "cracked" RL to a level not seen yet in open models, and by a large margin.

If this is sonoma-dusk that was on preview on openrouter, it's pretty cool. I've tested it with some code reverse engineering tasks, and it is at or above gpt5-mini level, while being faster. Works well till about 110-130k tokens tasks, then it gets the case of "getthereitis" and finishes the task even if not all constraints are met (i.e. will say I've solved x/400 tests, the rest can be done later)

Matches Grok 4 at the top of the Extended NYT Connections leaderboard: https://github.com/lechmazur/nyt-connections/

Why would a model called "Fast" not advertise the tokens per second speed it performs at? Is "Fast" not representing speed, but another meaning? Is it too variable?

Just two different models branded under similar names. That's it. Grok 4 is not the slower version of Grok 4 Fast, just like gpt-4 is not the slower version of gpt-4o.

I think we all want fast AND accurate, is "AND accurate" true for this model? I would rather prefer to wait a few seconds more if the result is much more accurate.

I would guess that it is essentially just a “grok 4 mini”, but if you use mini as the qualifier then most people will be inclined not to use it. If you call it fast then it gives people a reason to select it.

Oh man. Life must be hard

I can imagine, no model so far could actually use those context sizes…

Grok / X does not have the moat that Microsoft had.

Did using Microsoft's tools ever feel like a political standpoint? Because I won't even consider pitching Grok to my employers/clients for that very reason.

> If half of the developers in the world hate Musk and refuse to use his company's tools

In general, developers use what tools their employers paid for.

Standing on the precipice of AI assisted total information awareness and total authoritarian oppression?

Life is frightening right now.

I'm waiting for the Tesla FSD playbook to be rolled out for Grok. That is, launch something named like Grok AGI 1, wait for it to become obvious it isn't infact AGI, create a narrative redefining AGI, promise new AGI is 1 year away, and repeat for many years.

The banality of evil and the milgram experiment showed that employees will happily shoot the people that they're told to as well.

And the milgram experiment didn't even have subhuman classes and other such psychological manipulation and pre-biasing

It doesn't outperform uniformly across benchmarks. It's worse than Grok 4 on GPQA Diamond and HLE (Humanity's Last Exam) without tools, both of which require the model to have memorized a large number of facts. Large (and thus slow) models typically do better on these.

The other benchmarks focus on reasoning and tool use, so the model doesn't need to have memorized quite so many facts, it just needs to be able to transform them from one representation to another. (E.g. user question to search tool call; list of search results to concise answer.) Larger models should in theory also be better at that, but you need to train them for those specific tasks first.

So I don't think they simply trained on the benchmark tests, but they shifted their training mix to emphasize particular tasks more, and now in the announcement they highlight benchmarks that test those tasks and where their model performs better.

You could also write an anti-announcement by picking a few more fact recall benchmarks and highlighting that it does worse at those. (I assume.)

For the fastest performance, run it on Groq. /s

I was wondering that too. Anything reflecting human institutional knowledge writ large will, from Elons perspective, have "liberal bias" which is why he's also attacking Wikipedia and mainstream knowledge across the board. But other attempts at making non "biased" AI have barely done more than have custom instructions requesting that it "be conservative".

Unless you train it on Conservapedia or some equivalent corpus I'm not sure you'll be able to make it agree that "the Irish were the real slaves", that the D's and R's never realigned after the civil war, that the 2020 election was stolen and that gamergate was truly about ethics in journalism.

Ok, throwaway. You must have some valuable code.

It's all due to robust primitives: https://www.glscott.org/uploads/2/1/3/3/21330938/5375912_ori...

This is called “derangement syndrome”

Bonus points if you manage to kill a few poor deluded saps with your unsafe product along the way.

Surprising to see negativity here. I send all my LLM queries to 5 LLMs - ChatGPT, Claude, DeepSeek (local), Perplexity, and Grok - and Grok consistently gives good answers and often the most helpful answers. It's ~always king when there's any 'ethical' consideration (i.e. other LLMs refuse to answer - I stopped bothering with Gemini for this reason).

'Ethical' is in quotes because I can see why other LLMs refuse to answer things like "can you generate a curl request to exploit this endpoint" - a prompt used frequently during pen testing. I grew tired of telling ChatGPT "it's for a script in a movie". Other examples are aplenty (yesterday Claude accused me of violating its usage policy when asking "can polar bears eat frozen meat" - I was curious after seeing a photograph of a polar bear discovering a frozen whale in a melted ice cap). Grok gave a sane answer, of course.

> create a narrative redefining AGI

Hasn't OpenAI redefined AGI already as "any AI that can [supposedly] create a hecto-unicorn's worth of economic value"?

How do you manage sending and receiving requests to multiple LLMs? Are you going it manually through multiple UIs or using some app which integrates with multiple APIs?

I created a workflow using Alfred on macOS [0]. You press command + space then type 'llm' then the prompt and hit enter, and it opens the 5 tabs in the browser.

These are the urls that are opened:

http://localhost:3005/?q={query}

https://www.perplexity.ai/?q={query}

https://x.com/i/grok?text={query}

https://chatgpt.com/?q={query}&model=gpt-5

https://claude.ai/new?q={query}

Extremely convenient.

(little tip: submitting to grok via URL parameter gets around free Grok's rate limit of 2 prompts per 2 hours)

[0] https://github.com/stevecondylios/alfred-workflows/tree/main

I will never use a product built by one of Elon Musk's teams. Never.

I've found the results shift quite a lot between models and updates. Deepseek is pretty consistently good at writing code that is rather easy to improve from mid to good quality. Claude used to be pretty good, but now writes 10x the code you'd need. Gemini is amazing, if you buy one of the more expensive tiers, which in turn isn't really worth it because there are so many other options. GPT and Grok are hit and miss. They deliver great code or they deliver horrible code. GPT and Claude have become such a hurdle I've had to turn github co-pilot off in my VScode. Basically I use deepseek for brainstorming and GPT for writing configs, queries, sql and so on. If either of them fails me I'll branch out, and Grok will be on that list. When I once in a while face a real issue where I'm unsure about the engineering aspects, I'll use one of my sparse free gemini pro queries. I'd argue that we should pay for it at my work, but since it's Google that will never happen.

From an ethical perspective, and I'm based in Denmark mind you, they are all equally horrible in my opinion. I can see why anyone in the anglo-saxon world would be opposed to Elon's, but from my perspective he's just another oligarch. The only thing which sets him appart from other tech oligarchs is that he's foolish enough to voice the opinion publicly. If you're based in the US or in any form of Government position then I can see why DeepSeek is problematic, but at least China hasn't threatened taking Greenland by force. Also, where I work, China has produced basically all of our hardware with possible hardware back-doors in around 70% of our IOT devices.

I will give a shoutout to French Mistral, but the truth is that it's just not as good as it's competition.

You can do it directly using Openrouter.

Really, you are "surprised" to see the negativity here?

They sound like they’re positioning it more that it’s faster to complete because it uses fewer tokens - see the mentions of token efficiency.

My only problem is I use custom frontends and unlike Qwen3 coder i don't see grok4 fast offering any free api access to test out these models.

The tools they've partnership with i don't really use.

[delayed]