Model comparison
GPT-5.1 vs Grok 4.7
Grok 4.7 is the stronger model overall, scoring 53.1 to 49.0 on the Noometry Index.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. GPT-5.1 scores higher in 4 categories and Grok 4.7 in 6 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Grok 4.7 leads 62.8 to 50.6.
- The biggest single-benchmark swing is SciCode: 43.3% for GPT-5.1 and 57.8% for Grok 4.7.
- Grok 4.7 is cheaper at $2 / $6 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- Grok 4.7 accepts more context: 500K tokens versus 400K.
Side by side
| GPT-5.1 | Grok 4.7 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 49.0 | 53.1 |
| Released | 2025-11-13 | 2026-09-21 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 500K |
| Max output | 128K | 500K |
| Input $ / M tokens | $1.25 | $2 |
| Output $ / M tokens | $10 | $6 |
| Results tracked | 63 | 39 |
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Category by category
Coding Grok 4.7 leads
GPT-5.1: 46.4 (#66), Grok 4.7: 58.0 (#18)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| LMArena WebDev | 1395 | 1639 |
| SciCode | 43.3% | 57.8% |
| LMArena Coding | 1454 | 1427 |
| SWE-bench Verified | 68% | — |
| FrontierCode | — | 47.6% |
| SWE-bench Verified (bash only) | 66% | — |
| CursorBench | — | 46.3% |
| FrontierSWE | — | 29.5% |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
| ALE-Bench | 1,192 | — |
Agentic & Tool Use Grok 4.7 leads
GPT-5.1: 32.7 (#60), Grok 4.7: 36.7 (#37)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| Vending-Bench 2 | 1,473 | 10,537 |
| Terminal-Bench | 47.6% | — |
| APEX-Agents | — | 54.6% |
| DeepResearch Bench | 42.8% | — |
| GDP.pdf | — | 22.8% |
| LMArena Search | 1199 | — |
Reasoning Grok 4.7 leads
GPT-5.1: 39.8 (#58), Grok 4.7: 49.1 (#40)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| CritPt | 4.9% | 18% |
| Chess Puzzles | 32% | 38% |
| LMArena Hard Prompts | 1457 | 1413 |
| Mystery Game Puzzles | 19% | 29% |
| DTBench | 90.1% | 96% |
| LMCA | 43.9% | 49.4% |
| Epoch Capabilities Index | 149.64 | 153.53 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 76.8% |
| ARC-AGI-1 | 72.8% | — |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| LiveBench Data Analysis | 72.1% | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math Grok 4.7 leads
GPT-5.1: 52.2 (#51), Grok 4.7: 57.8 (#39)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 98.1% |
| LMArena Math | 1447 | 1407 |
| FrontierMath (Tiers 1-3) | — | 53% |
| FrontierMath Tier 4 | — | 17.1% |
| ProofBench | — | 34% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge Grok 4.7 leads
GPT-5.1: 50.6 (#71), Grok 4.7: 62.8 (#22)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| GPQA Diamond | 87.6% | 92.7% |
| SimpleQA Verified | 48% | 56% |
| LMArena Expert | 1470 | 1422 |
| Humanity's Last Exam | 23.7% | — |
| MMLU-Pro | 57.9% | — |
| Vectara Hallucination Rate | 10.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), Grok 4.7: 35.5 (#87)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| LMArena Vision | 1250 | 1228 |
| VPCT | 58.7% | — |
| Blueprint-Bench 2 | — | 32.5% |
| Furniture Assembly | — | 20.8% |
| LMArena Document | 1403 | — |
Multilingual GPT-5.1 leads
GPT-5.1: 53.8 (#56), Grok 4.7: 50.8 (#116)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| LMArena Non-English | 1431 | 1389 |
| LMArena Chinese | 1495 | 1455 |
| LMArena French | 1450 | 1455 |
| LMArena Russian | 1435 | 1397 |
| LMArena Spanish | 1433 | 1400 |
| LMArena German | 1438 | — |
| LMArena Japanese | 1453 | — |
| LMArena Korean | 1401 | — |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), Grok 4.7: 74.1 (#105)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| LMArena Instruction Following | 1443 | 1404 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Grok 4.7: 43.1 (#104)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| LMArena Longer Query | 1447 | 1413 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference Grok 4.7 leads
GPT-5.1: 64.5 (#55), Grok 4.7: 70.0 (#24)
| Benchmark | GPT-5.1 | Grok 4.7 |
|---|---|---|
| LMArena Text | 1443 | 1399 |
| LMArena Creative Writing | 1427 | 1391 |
| LMArena Multi-Turn | 1450 | 1393 |
| EQ-Bench Creative Writing | — | 2007 |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Grok 4.7?
Grok 4.7 is the stronger model overall, scoring 53.1 to 49.0 on the Noometry Index.
Which is cheaper, GPT-5.1 or Grok 4.7?
Grok 4.7 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Grok 4.7 better for coding?
Grok 4.7 scores higher on coding benchmarks: 58.0 versus 46.4 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 400K.
How many benchmarks do GPT-5.1 and Grok 4.7 share?
27 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Grok 4.7 has 39.