aiprompt.fyi
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Grok 4.20 vs GPT-5

xAI's irreverent challenger versus the incumbent.

Cheapest
Grok 4.20
$2.00 / 1M tok
Highest quality
GPT-5
9.2 / 10
Best V-Index
Grok 4.20
4.20
DimensionGrok 4.20GPT-5
VendorxAIOpenAI
Input price ($ / 1M tok)$2.00$2.50
Quality (1–10)8.49.2
V-Index (Quality ÷ Price)4.203.68
reasoning precisionHighHigh
coding precisionMediumHigh
creative precisionHighHigh
factual precisionMediumHigh
summarization precisionMediumHigh
extraction precisionMediumHigh

Verdict

For raw value-per-token, Grok 4.20 wins on V-Index (4.20 vs 3.68). For absolute quality on reasoning-heavy work, GPT-5 is the safer pick. Run your real prompt through the auditor below to see which one wins for your specific workload.

Scaling Roadmap

To scale your prompt engineering workflow: 1. Audit (1-2 days) to identify the optimal model. 2. Implement via API (3-5 days) using the chosen model. 3. Monitor V-Index drift (ongoing) as new models release.

Audit my prompt →

Grok 4.20 vs GPT-5 — the full picture

Grok 4.20 and GPT-5 sit at the top of the 2026 frontier-model market but optimise for different buyers. Grok 4.20 (xAI) lists at $2.00 per 1M input tokens with a curated quality score of 8.4/10. GPT-5 (OpenAI) lists at $2.50 per 1M with a quality score of 9.2/10. The headline gap looks small — but at scale, the price multiple is 1.3x and the V-Index gap is 0.52 points, which compounds fast across a typical 10M-token monthly workload.

The cost math at scale

At 10M input tokens per month — a realistic mid-market workload — Grok 4.20 costs $20 and GPT-5 costs $25. The annualised difference is $60. Whether that gap is worth paying depends entirely on whether the higher-priced model reduces downstream review time enough to cover it. Our auditor measures this directly on your real prompt.

Pick Grok 4.20 when…
  • when budget is the binding constraint — Grok 4.20 is both cheaper and higher V-Index
Pick GPT-5 when…
  • for writing, debugging or reviewing production code in real codebases — GPT-5 rates High, Grok 4.20 rates Medium
  • for retrieval, summarisation and Q&A where accuracy beats style — GPT-5 rates High, Grok 4.20 rates Medium
  • for condensing long documents without losing material detail — GPT-5 rates High, Grok 4.20 rates Medium
  • for pulling structured fields out of unstructured text at scale — GPT-5 rates High, Grok 4.20 rates Medium
  • for the highest-stakes work where raw quality matters more than cost — GPT-5 edges out on the overall quality score

Frequently asked questions

Is Grok 4.20 better than GPT-5?
Neither is universally better. GPT-5 has the higher curated quality score (9.2 vs 8.4), but Grok 4.20 has the higher V-Index (4.20 vs 3.68). The right choice depends on whether your workload is quality-bound or cost-bound — run a real prompt through the auditor to see which one wins for your specific use case.
What is V-Index?
V-Index is quality (1–10) divided by input price per 1M tokens (USD). It is a single number that captures value-per-dollar — higher is better. Grok 4.20 scores 4.20 on V-Index; GPT-5 scores 3.68.
Which model hallucinates less?
Both Grok 4.20 and GPT-5 hallucinate at non-zero rates in 2026, but the rate is highly task-dependent. Factual retrieval and citation tasks are the highest-risk categories on either model. The auditor on aiprompt.fyi flags hallucination risk per task type, per model, on your real prompt.
Can I switch between Grok 4.20 and GPT-5 based on the prompt?
Yes — and you should. Frontier-model routing (picking the right model per request based on task type and cost) typically cuts spend 30-50% versus defaulting to one model. The auditor produces a per-task recommendation you can wire directly into a router.
Where does the pricing come from?
Pricing is the public list price per 1M input tokens as of the most recent vendor update. Enterprise contracts often discount 20-40% off list. Quality scores are curated based on published benchmarks and our own task-specific testing — they are not vendor-supplied.

More 2026 model comparisons