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Grok vs GPT: 2026 benchmark comparison
Compare xAI Grok and OpenAI GPT models on the same public evaluations.
Last collected by this site: 2026-11-15 06:40 (UTC+8, Asia/Shanghai). Source publication dates are in the table or the citations below.
Compare xAI Grok and OpenAI GPT models on the same public evaluations.
Grok 4.6
- Grok 4.6 (High)xAI · overall 82.6
- Grok 4.5xAI · overall 81.5
- Grok 4.20 Beta Reasoning 0309xAI · overall 75.1
- Grok 4.3xAI · overall 70.4
- Grok 4.7xAI · overall 69.1
- Grok 4.1 (Thinking)xAI · overall 67.7
GPT 6 Astra
- GPT 6 AstraOpenAI · overall 96.5
- GPT 6.1 SolOpenAI · overall 91.6
- GPT 6.1 TerraOpenAI · overall 89.5
- GPT 5 (High)OpenAI · overall 88.9
- GPT 6 Sol (Max)OpenAI · overall 84.7
- GPT 5.2OpenAI · overall 79.8
Flagship comparison (best overall variant in each family)
| Metric | Grok 4.6 (High) | GPT 6 Astra |
|---|---|---|
| Overall | 82.6 | 96.5 |
| AA Intelligence Index | — | — |
| LMArena Text | 1,457 | — |
| LiveBench overall | — | 84.5 |
| Coding | 71.4 | 95.0 |
| Reasoning | 85.8 | 91.0 |
| Chinese (SuperCLUE or arena) | 1,497.0 | — |
| Vision arena | 1,263 | — |
This is not a declaration of an overall winner between labs. It places the same public scores side by side. See the methodology page for the full rules.
Sources
- LMArena Text Arena (style-controlled) — Official Arena leaderboard dataset, text_style_control / latest. Scores are Arena ratings (Bradley-Terry).
- LMArena WebDev Arena — Official webdev / latest snapshot, measuring front-end and web-app battles.
- LMArena Vision Arena (style-controlled) — Official vision_style_control / latest snapshot.
- LMArena Text-to-Image Arena — Official text_to_image / latest snapshot.
- LMArena Text-to-Video Arena — Official text_to_video / latest snapshot.
- LMArena Agent Arena — Official agent / latest aggregate scores.
- Artificial Analysis Intelligence Index — Intelligence Index, cost per task, time per task and first-token latency from the official public leaderboard page.
- LiveBench 2.0 — Official CSV results. Overall uses the published formula: Long Agentic ×2, Design ×1.5, Coding ×1.5, other suites ×1, then a weighted mean over suites that have a score.
- Aider Polyglot — Official polyglot_leaderboard.yml. The metric is pass_rate_2 on 225 cross-language exercises. Repeated submissions keep the best score.
- SWE-bench Verified (mini-SWE-agent) — Official leaderboards.json, Verified board, resolved % under the mini-SWE-agent protocol so models are compared in a similar scaffold. Scores from other agents are not mixed into the composite coding score.
- SuperCLUE Chinese general board — Total and section scores from the official monthly general-board spreadsheet.
FAQ
- Where do these scores come from?
- Every score comes from a public benchmark or official machine-readable file, with a source link and date. This site does not invent scores, and missing values are not treated as zero.
- Do you only compare a single winner from each lab?
- Each comparison lists leading flagship families from both labs and the same-source breakdowns. When a family has several variants (for example High or Max), the variant with the better overall score is used.
- Are site prices part of the benchmarks?
- No. Benchmark scores come from third-party public boards. CNY prices are this site’s catalogue reference rates (CNY 1 = 1,000 points) and are settled on actual usage. They are shown separately so billing is not confused with quality.