Model comparison
Grok 4.7 vs o3
Grok 4.7 is the stronger model overall, scoring 53.1 to 47.5 on the Noometry Index.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. Grok 4.7 scores higher in 7 categories and o3 in 3 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.7 leads 49.1 to 32.0.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 53% for Grok 4.7 and 33.3% for o3.
- Grok 4.7 is cheaper at $2 / $6 per million input/output tokens, against $2 / $8 for o3.
- Grok 4.7 accepts more context: 500K tokens versus 200K.
Side by side
| Grok 4.7 | o3 | |
|---|---|---|
| Provider | xAI | OpenAI |
| Noometry Index | 53.1 | 47.5 |
| Released | 2026-09-21 | 2025-04-16 |
| Weights | Proprietary | Proprietary |
| Context window | 500K | 200K |
| Max output | 500K | 100K |
| Input $ / M tokens | $2 | $2 |
| Output $ / M tokens | $6 | $8 |
| Results tracked | 39 | 63 |
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Category by category
Coding Grok 4.7 leads
Grok 4.7: 58.0 (#18), o3: 46.8 (#64)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| LMArena Coding | 1427 | 1408 |
| SWE-bench Verified | — | 62.3% |
| FrontierCode | 47.6% | — |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| CursorBench | 46.3% | — |
| LMArena WebDev | 1639 | — |
| FrontierSWE | 29.5% | — |
| SciCode | 57.8% | — |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
| ALE-Bench | — | 933.55 |
Agentic & Tool Use Grok 4.7 leads
Grok 4.7: 36.7 (#37), o3: 34.5 (#44)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| APEX-Agents | 54.6% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| GDP.pdf | 22.8% | — |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
| Vending-Bench 2 | 10,537 | — |
Reasoning Grok 4.7 leads
Grok 4.7: 49.1 (#40), o3: 32.0 (#78)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| CritPt | 18% | 1.4% |
| Chess Puzzles | 38% | 38% |
| LMArena Hard Prompts | 1413 | 1402 |
| Mystery Game Puzzles | 29% | 29% |
| DTBench | 96% | 84.8% |
| LMCA | 49.4% | 39.7% |
| Epoch Capabilities Index | 153.53 | 146.86 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| NYT Connections (extended) | 76.8% | — |
| ARC-AGI-1 | — | 60.8% |
| EnigmaEval | — | 13.1% |
| ForecastBench | — | 62.5 |
Math Grok 4.7 leads
Grok 4.7: 57.8 (#39), o3: 50.2 (#58)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 53% | 33.3% |
| OTIS Mock AIME 2024-2025 | 98.1% | 84.4% |
| LMArena Math | 1407 | 1426 |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 34% | — |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Grok 4.7 leads
Grok 4.7: 62.8 (#22), o3: 54.6 (#52)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| GPQA Diamond | 92.7% | 81.8% |
| SimpleQA Verified | 56% | 49.4% |
| LMArena Expert | 1422 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
Multimodal o3 leads
Grok 4.7: 35.5 (#87), o3: 41.4 (#36)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| LMArena Vision | 1228 | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
| Blueprint-Bench 2 | 32.5% | — |
| Furniture Assembly | 20.8% | — |
Multilingual Too close to call
Grok 4.7: 50.8 (#116), o3: 51.7 (#105)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| LMArena Non-English | 1389 | 1401 |
| LMArena Chinese | 1455 | 1437 |
| LMArena French | 1455 | 1430 |
| LMArena Russian | 1397 | 1406 |
| LMArena Spanish | 1400 | 1395 |
| LMArena German | — | 1420 |
| LMArena Japanese | — | 1403 |
| LMArena Korean | — | 1370 |
Instruction Following Grok 4.7 leads
Grok 4.7: 74.1 (#105), o3: 72.8 (#127)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
Grok 4.7: 43.1 (#104), o3: 53.3 (#6)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| LMArena Longer Query | 1413 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference Grok 4.7 leads
Grok 4.7: 70.0 (#24), o3: 63.5 (#64)
| Benchmark | Grok 4.7 | o3 |
|---|---|---|
| LMArena Text | 1399 | 1410 |
| LMArena Creative Writing | 1391 | 1359 |
| EQ-Bench Creative Writing | 2007 | 1676 |
| LMArena Multi-Turn | 1393 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| WildBench | — | 86.1% |
Frequently asked questions
Is Grok 4.7 better than o3?
Grok 4.7 is the stronger model overall, scoring 53.1 to 47.5 on the Noometry Index.
Which is cheaper, Grok 4.7 or o3?
Grok 4.7 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o3 lists at $2 and $8.
Is Grok 4.7 or o3 better for coding?
Grok 4.7 scores higher on coding benchmarks: 58.0 versus 46.8 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 200K.
How many benchmarks do Grok 4.7 and o3 share?
26 benchmarks have published results for both models. Grok 4.7 has 39 scored results on Noometry and o3 has 63.