Grok 4.5 Review: I Tested SpaceXAI's Cheap Coder

Most of the launch-day coverage for a new model is a quick rewrite of the press release and a few Musk tweets, which is understandable when you're racing to publish. So here's my Grok 4.5 review with the one thing that coverage can't fake: I actually ran the thing through my usual coding tests. Two website builds, a Go poker simulation, an audit of my own site. It's fast, it's cheap, and it caught a bug that no other model has ever flagged for me, including the ones I rate higher than it. That last part is the bit I keep chewing on, so I'll come back to it.

What Grok 4.5 actually is (and why the price is the story)

Grok 4.5 launched July 8, 2026 for developers, with the wider public rollout a day later, from SpaceXAI. If that name makes you do a double take, fair enough: SpaceX absorbed xAI back in February, so the company shipping Grok now is the merged entity. It's pitched squarely at coding, agentic tasks, and knowledge work. This is not a consumer-chatbot play, which is a nice change of pace.

Here's a clean definition if you just want the one-liner: Grok 4.5 is a mixture-of-experts coding and agentic model from SpaceXAI, jointly trained with Cursor, that lands near the top of the independent leaderboards while costing a fraction of its rivals per task. The headline isn't the leaderboard, though. It's the economics.

The API price is $2 per million input tokens and $6 per million output, which Artificial Analysis clocks at more than 60% below Claude Opus 4.8 and GPT-5.5. On top of that, it's stingy with tokens: roughly 4.2 times fewer output tokens than Opus 4.8 to resolve the same task. Cheap price multiplied by fewer tokens is where the real gap opens up.

One thing to get straight before anyone runs away with a "Grok beats Opus" headline. Musk's own framing, in the pre-launch chatter, put it at roughly Opus 4.7, not 4.8. So "Opus-class tier" is fair. "Beats Opus" is not what the numbers say. Cursor also disclosed that an earlier snapshot of its own codebase accidentally ended up in training, which gave Grok an unfair edge on one internal benchmark. Credit for owning it publicly. It's also worth naming, because it does raise a small flag about training-data contamination.

The Cursor connection: why this model can code

This is the part that actually explains the coding ability, so stick with me.

On June 16, 2026, SpaceX exercised an option to buy Anysphere, the maker of Cursor, for $60 billion in an all-stock deal. That's the largest acquisition of a venture-backed startup ever recorded, nearly double Google's Wiz purchase. TechCrunch, Reuters, CNBC, and everyone else confirmed it, so this isn't a rumour I'm passing along.

But the deal itself isn't the interesting part for us. The training is. Cursor's own launch post says Grok 4.5 was trained on trillions of tokens of Cursor data: real developer-agent interactions, not just scraped public repos. That's the difference between learning what code looks like and learning how developers actually work through a problem. Identify the bug, run the tool, read the error, fix it, verify. That feedback loop is a genuinely plausible source of the token-efficiency edge, not marketing fluff.

Here's the question I actually wanted answered. Cursor's own Composer 2.5 was already a strong, cheap coding specialist. So what did the joint training add on top of a model that was already good? The honest answer from the outside is: breadth. Cursor deliberately widened the data mix beyond pure software engineering into STEM, research, and general knowledge work, so Grok 4.5 generalises where Composer stayed narrow. Whether that trade lands for your specific workflow is exactly the kind of thing you'd want to test yourself.

Speculating a little, because it's fun: the more interesting thing over the next year probably isn't the model at all. It's what SpaceX and Cursor ship around it, the agent and tooling layer, now that the same company owns both the IDE and the weights. That's a tighter loop than any competitor has right now. We'll see if they use it.

I ran my usual tests

If you've read my other model reviews, you know the drill. I keep the prompts fixed across every model so the comparison actually means something. Same three tests, every time:

• Two single-file HTML website builds: a Sydney coffee roaster and a pop-culture clothing store.
• A Go Texas Hold'em terminal simulation: six personality-driven bots, 1000 hands, full statistics at the end.
• An audit of thomas-wiegold.com, my own blog.

None of this is a scientific benchmark. It's a working developer poking at a tool the way he'd actually use it. I'll be explicit about that, because the whole point is that it's hands-on rather than a leaderboard screenshot.

The website builds

These were among the best build results I've gotten out of any model. Layout was clean, the animations were tasteful rather than the usual "look at all the CSS I know" mess, the fonts were sensible, and it was fully responsive on mobile without me asking twice. It also generated fast.

I'll hedge honestly, though. I still slightly prefer the builds I got from Gemini 3.5 Flash in my Antigravity review. Not by a lot, and reasonable people could flip the ranking, but I'm not going to oversell Grok here just because the price is good.

The Go poker simulation

This might be my best-ever result on this test, full stop.

Before Grok 4.5, exactly one model had one-shotted the poker sim cleanly: Claude Fable. Grok did it too, first try, and its statistics output at the end was more detailed than what I'd seen before. Six bots with distinct personalities, a thousand hands, and a stats breakdown I didn't have to fix. Under ten minutes, start to finish. For a test that's tripped up plenty of frontier models, that's a genuine result.

The site audit

This is the one. This is the reason I'm bothering to write the review at all.

Grok 4.5 caught a real problem on my site that no other model has ever flagged, and I've run this audit a lot. Not even Fable found it. My Markdown to HTML article conversion was injecting hidden, non-rendering data into the output, quietly inflating the payload of every single article. Invisible to a reader, invisible to me, and adding weight to every page load. Concrete, fixable, and exactly the kind of finding that justifies running the test in the first place. I fixed it today.

So where does that leave the section verdict? The benchmarks put Grok 4.5 a notch below Fable, Opus, and GPT-5.5. In my hands, across these three tasks, it felt level with them or close enough that I couldn't reliably tell them apart. Gut feel, not science. But that honesty is exactly why I trust my own tests more than a vendor chart, and hopefully why you do too.

Pricing and SuperGrok: where the value actually lands

I'll say it plainly, because it's the number that matters. On Artificial Analysis's Coding Agent Index, a task in Grok Build runs about $2.49. The same class of task costs roughly $5.07 for GPT-5.5 in Codex and about $11.80 for Fable 5 in Claude Code. That's not a rounding difference. Multiply it across a month of agent runs and the arithmetic bends hard in Grok's favour.

The API breakdown, if you want it: $2 input, $6 output, $0.50 cached (a 75% discount), and prices double once your prompt crosses 200k tokens. Cached-heavy agentic loops are where this gets silly cheap.

My own experience backs the number up. I'm on the $30-a-month SuperGrok plan, and my full review test suite, all three tests, barely dented my quota. Somewhere around 1% of my weekly usage. I had to double-check that, because it felt too low. It wasn't.

This tracks with the thesis I've been banging on about since my MAI-Code-1-Flash review: I back cheap-and-fast models for the work most of us do most of the time. Fable is a better model. I'm not disputing that. But I won't pay Fable prices for routine work, and neither will most teams once they see the invoice. Grok 4.5 is the one I'll actually reach for day to day.

The caveats worth knowing

Nothing here is a dealbreaker on its own, but you should know all of it before committing.

The context window is 500k tokens. That's a regression from Grok 4.3's 1M, and it sits behind the 1M windows on Claude and Gemini. Now, I'd argue those headline numbers are mostly marketing anyway, since models degrade and start dropping detail long before the window is actually full, so I wouldn't lose sleep over the on-paper gap. Still, less usable room is less usable room, and if you're doing long-document work or feeding in a large repo, it's worth knowing you've got a smaller runway to play with than the previous version gave you.

Reliability has a real wrinkle. On the AA-Omniscience benchmark, accuracy improved but the hallucination rate rose to around 54%, up from 25%. In plain terms: it knows more, and it's also more confident when it's wrong. For knowledge work, keep a hand on the wheel.

It's not available in the EU at launch. Mid-July is the expected date, so European devs should confirm access before building anything on it.

On trust: the loudest Hacker News thread on launch day wasn't about capability at all, it was about alleged Musk-linked steering of political outputs. I'll note it and leave it there. Opinions in that thread were genuinely split, and it's not my job to settle it for you.

And the "1.5 trillion parameters on a V9 foundation" figure that's floating around? That's attributed to Musk and reporting, not officially disclosed by SpaceXAI. Treat it as widely-repeated-but-unconfirmed.

Grok 4.5 review verdict: a game-changer for Grok

Straight call: Grok 4.5 is a genuinely good coding model now, and at $30 a month on SuperGrok it's an absurd amount of value. I'll keep using it. Even though Fable is the better model, I'm not paying Fable prices for the routine stuff, and this closes enough of the gap that I don't feel like I'm compromising.

The way to think about it isn't "replace Claude." It's routing. Send the high-volume, repetitive, agentic work to Grok 4.5, and keep Opus 4.8 or Fable 5 for the hardest, highest-risk tasks where a mistake is expensive. Match the model to the job. That's the whole game in mid-2026.

And the competition is only heating up, which is great for us. GPT-5.6 is landing within days and Grok 5 is reportedly already in training. More pressure on all of them means better tools and lower prices for the rest of us. Mostly, I'm curious where Cursor goes now that it's part of a rocket company. That's a sentence I did not expect to write this year.