Grok vs GPT-5 in 2026: Which to Use

Grok and GPT-5 are not close on price, and most comparisons still say they are. Grok 4.3 lists at $1.25 input / $2.50 output per million tokens; GPT-5.5 lists at $5 / $30. That is 4x on input and 12x on output before you send a single request. One thing to fix in your head first: xAI's current flagship is Grok 4.5, released 9 July 2026 at $2 / $6 with a 500K context window — newer and dearer than Grok 4.3, and not something we have benchmarked, so every measured number on this page is Grok 4.3. Grok's other edge is native, real-time access to X (Twitter) data; GPT-5's is frontier quality, the deepest tooling ecosystem, and a wide tier ladder from nano to Pro. This guide compares them on capability, price and use case, models what each costs across real workloads, and gives a clear pick by job. It also includes something a spec sheet cannot: we ran Grok 4.3 and GPT-5.5 through the same nine executed coding tasks and priced the real token usage, so you can see what the price gap actually buys.

The short answer

Grok 4.3 for cost and speed; GPT-5.5 for not dropping tasks. There is no list-price parity between these two families and there is no point pretending otherwise: Grok 4.3 lists at $1.25 input / $2.50 output per million tokens, GPT-5.5 at $5 / $30 — 4x on input, 12x on output. A large bill gap is therefore the expected result, not the surprise. What our executed run adds is the direction of the trade: on the same nine coding tasks Grok 4.3 cost $1.75 per 1,000 tasks, averaged 8.4 s, and missed one task; GPT-5.5 cost $8.83, averaged 10.5 s, and missed none. You are paying roughly 5x for one fewer miss in nine, and paying it to the slower of the two. Capability fit still decides a lot — GPT-5 is the broader family, Grok's native real-time X data is its unmatched feature — but the money question is already answered before you run anything.

Side by side

Three things about that table trip people up. First, the top row and the row below it are different models on purpose: Grok 4.5 is what xAI ships as flagship today at $2/$6, and Grok 4.3 at $1.25/$2.50 is the one our benchmark actually ran — so the measured column further down is 4.3, never 4.5. Second, xAI flattened most of its price ladder: Grok 4.3 and both Grok 4.20 variants carry the identical $1.25/$2.50, so choosing among those is a question of context window and behaviour, not cost. Third, the cheap coding tier people remember is gone — Grok Code Fast 1 and its $0.20/$1.50 are retired, along with Grok 4, Grok 3 and Grok 3 Mini. The replacement, grok-build-0.1 at $1.00/$2.00, is not a drop-in: it sits on xAI's separate Code API rather than chat completions, so moving a coding loop onto it is an integration change, not a model-string change. Details in the Grok API pricing guide.

What we measured when we ran both

Everything above is a spec sheet. So we ran both sides ourselves. Our harness puts 13 models through 9 executed Python tasks at temperature 0 and max_tokens 4000, then scores each answer by running the returned code against assertions the model never sees — no human judgement, no partial credit, one scored attempt per task (the harness retries only on an API error, never on a wrong answer). The nine tasks are two_sum, valid_parentheses, merge_intervals, roman_to_int, lcs_len, flatten, top_k_words, token_bucket and parse_csv_line. Requests go through OpenRouter's OpenAI-compatible endpoint, not the DataLLM Lab gateway. Both families were in that run: Grok 4.3 and GPT-5.5. Grok 4.5 — xAI's flagship since 9 July 2026, $2 / $6 — was not in the run, so no number in this section is a Grok 4.5 number and none of it should be read as one. The Grok 4.20 variants, grok-build-0.1 and the GPT-5 mini and nano tiers were not tested either, so nothing below speaks for them; Grok 3 and Grok 4 are retired and were never in scope.

The bill gap is not news — the list prices predicted it. What the run adds is which way the quality trade points, and that is the part no price page tells you. Grok 4.3 was cheaper and faster on identical work — $1.75 per 1,000 tasks at 8.4 s average against $8.83 and 10.5 s — and it still dropped one task, flatten. GPT-5.5 dropped nothing. So the honest framing is not which model is better but what is one miss in nine worth to you: on work a human reviews before it ships, very little; on an unattended batch job where nobody reads the output, quite a lot. The premium buys reliability, and it does not buy speed.

Two numbers are worth pulling out. First, the measured gap is about 5x, which sits between the 4x input-price ratio and the 12x output-price ratio — the workload's token mix, not the sticker, decided where in that band the invoice landed. Second, and this kills the usual explanation: GPT-5.5 emitted fewer reasoning tokens than Grok 4.3 on these tasks (176 against 482), so it was not thinking itself into a bigger bill. It thought less and still billed 5x, which points squarely at the per-token rate rather than verbosity. That also means you cannot prompt your way out of the gap.

And neither model was the best result in the run. Claude Sonnet 5 matched GPT-5.5's 9/9 at $1.67, below Grok 4.3's price, and qwen3-coder-next did it for $0.10. Ten of the thirteen models scored 9/9; the cheapest perfect score was $0.10 and the most expensive was $8.83, an 88x spread for output that passed the identical assertions. The fastest model overall was Mistral Medium 3.5 at 2.9 s, which is neither of the two models on this page. On tasks this size, frontier pricing bought no extra correctness.

Pricing

This is where the comparison is decided, and the two families are nowhere near each other. On input, Grok 4.3 is $1.25 against GPT-5.5's $5 — 4x. On output, $2.50 against $30 — 12x. Even GPT-5.4, the cheaper OpenAI chat tier at $2.50 / $15, is 2x Grok 4.3's input and 6x its output. Going up to xAI's current flagship narrows the gap without closing it: Grok 4.5 at $2 / $6 is 2.5x under GPT-5.5 on input and 5x under it on output. The gap is widest exactly where generation-heavy workloads live:

Input prices for the same five: grok-build-0.1 $1.00, Grok 4.3 $1.25, Grok 4.5 $2.00, GPT-5.4 $2.50, GPT-5.5 $5.00. Note what is not on this chart — Grok's old $0.20/$1.50 coding tier. Grok Code Fast 1 is retired, so the current xAI floor for output is $2.00, not $1.50, and its input floor is $1.00 rather than $0.20. If you built a budget on the old numbers, rebuild it.

What they cost to run

Modeled monthly cost across five workloads:

Grok 4.3 is cheapest in every row, and the multiple against GPT-5.5 swings from 4.8x on batch extraction to 10.4x on content generation — the more output-heavy the workload, the wider the gap, exactly as the $2.50-vs-$30 output rate implies. Read the table for what it is, though: it holds token volume fixed for every model, so it prices a list, not a run. Our executed benchmark is the check on it, and the check is interesting. On nine identical tasks Grok 4.3 and GPT-5.5 billed $1.75 and $8.83 per 1,000 tasks — about 5x, near the low end of this table's 4.8x–10.4x band, because Grok emitted more reasoning tokens (482 to GPT-5.5's 176) and gave some of its rate advantage back. The list price sets the ceiling on your savings; your token mix decides how much of it you keep.

Where Grok wins

• Price, and not by a little — Grok 4.3 at $1.25 / $2.50 against GPT-5.5 at $5 / $30 is 4x on input and 12x on output. Modeled at 80M in / 25M out a month, that is $162.50 against $1,150.00.
• Real-time X data — native access for current-events and social-trend questions. Nothing in our coding run touches this; it is Grok's one genuinely unmatched feature.
• Cheaper and faster per task, measured — on our nine executed tasks Grok 4.3 ran at $1.75 per 1,000 tasks and 8.4 s average, against GPT-5.5's $8.83 and 10.5 s.
• One price across the chat family — Grok 4.3 and both Grok 4.20 variants cost the same, so you can move to a 2M context window without a cost review.
• Not a win any more: the budget coding tier. Grok Code Fast 1 at $0.20 / $1.50 is retired; grok-build-0.1 replaces it at $1.00 / $2.00 on a separate Code API, and we have not benchmarked it.

Where GPT-5 wins

• It doesn't drop tasks — GPT-5.5 scored 9/9 in our run; Grok 4.3 scored 8/9, missing flatten. That reliability is the entire thing the 5x buys: it does not buy speed (10.5 s against 8.4 s), and it is not explained by longer thinking (176 reasoning tokens against 482).
• General frontier quality — the broader, more capable family across tasks, though on short coding work the ceiling is crowded: ten of the thirteen models we ran also scored 9/9, one of them for $0.10.
• Ecosystem — the widest tooling, libraries, and integrations.
• Tier range — nano to Pro, for fine-grained cost control.

Which to pick

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