Grok vs GPT-5 for Coding: Real-World Outputs

Grok 4.5 arrived with a pitch aimed squarely at OpenAI’s wallet share: $2 per million input tokens, $6 per million output, a 500k context window, and xAI’s usual speed claims. GPT-5.5 sits at $1.25 in and $10 out and remains the default coding model for a large share of developers. Benchmark threads will argue about which is “better” forever. We do something narrower and more checkable: run both on identical one-shot coding prompts, publish the running outputs, and let the community vote blind.

The sticker prices answer less than they seem to

Read the price list carelessly and you get two contradictory headlines. “GPT-5.5 is cheaper” — true on input, $1.25 against Grok’s $2. “Grok 4.5 undercuts OpenAI by 40%” — true on output, $6 against $10. Which one applies to you depends entirely on the shape of your workload, and coding workloads are not all one shape. Paste a large codebase and ask for a small patch, and input dominates. Hand over a short spec and ask for a complete working app — the one-shot pattern our arena tests — and output dominates. Same two models, opposite winners.

How we actually compare them

• One published prompt per challenge. Both models get the identical one-shot instruction — landing pages, games, emulators, physics toys.
• One shot, no retries. The first response is the entry. No best-of-five, no cherry-picking.
• Live outputs, not screenshots. The generated apps run in your browser, bugs included.
• Blind community votes. Model names stay hidden until after you vote, and every vote lands on the public leaderboard.
• Disclosed cost per task. Output tokens and estimated cost sit next to every entry, so a close vote can be settled by the invoice.

You can watch the matchup directly: Grok 4.5 vs GPT-5.5 puts the two side by side on the landing-page challenge, outputs running live. We are not going to quote a winner here — the tally moves as votes come in, and pretending a snapshot is a verdict is exactly the benchmark-headline habit this site exists to break.

One shot, no retries. What the model returned first is what you see.

What to watch when you compare outputs

Three things separate these two in practice, and only one of them shows up on a price list. First, completeness on the first try: one-shot prompting punishes models that return a skeleton and an apology, whichever lab made them. Second, speed: xAI markets Grok 4.5 hard on tokens per second, and for interactive coding that matters more than leaderboard position — judge it from the per-entry timing data rather than from anyone’s launch post, ours included. Third, the 500k context window: our one-shot tasks don’t stress it, so if your real work is repo-scale refactoring, treat that spec as Grok’s untested advantage here and verify it on your own codebase.

So which should you use?

The honest answer is a procedure, not a name. Open the arena, pull up the same task from both models, and vote before you look at the labels. If the outputs look equally good to you, take the cheaper bill for your token mix — Grok 4.5 for generation-heavy work, GPT-5.5 for prompt-heavy work. And if you are choosing a daily driver across the whole roster rather than settling this one rivalry, the best AI for coding guide applies the same rules to all twenty model families.