Model comparison
Grok 4.5 vs o3
Grok 4.5 is the stronger model overall, scoring 55.0 to 47.5 on the Noometry Index.
Last verified . 35 shared benchmarks.
Summary
- They share 35 benchmarks with published results for both. Grok 4.5 scores higher in 8 categories and o3 in 2 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.1 to 32.0.
- The biggest single-benchmark swing is ARC-AGI-2: 52.6% for Grok 4.5 and 6.5% for o3.
- Grok 4.5 is cheaper at $2 / $6 per million input/output tokens, against $2 / $8 for o3.
- Grok 4.5 accepts more context: 500K tokens versus 200K.
Side by side
| Grok 4.5 | o3 | |
|---|---|---|
| Provider | xAI | OpenAI |
| Noometry Index | 55.0 | 47.5 |
| Released | 2026-07-08 | 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 | 52 | 63 |
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Category by category
Coding Grok 4.5 leads
Grok 4.5: 52.2 (#35), o3: 46.8 (#64)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| WeirdML | 46.4% | 52.4% |
| LMArena Coding | 1474 | 1408 |
| ALE-Bench | 1,309 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.4% | — |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1553 | — |
| SciCode | 54.1% | — |
| GSO | — | 8.8% |
| CadEval | — | 74% |
Agentic & Tool Use Grok 4.5 leads
Grok 4.5: 44.4 (#17), o3: 34.5 (#44)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| LMArena Search | 1213 | 1144 |
| APEX-Agents | 56.2% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| τ²-bench Banking | 47.9% | — |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| PostTrainBench | 23.4% | — |
| GBAEval | 65.4% | — |
| GDP.pdf | 14% | — |
| METR Time Horizons | — | 65.4% |
| Vending-Bench 2 | 3,887 | — |
Reasoning Grok 4.5 leads
Grok 4.5: 56.1 (#25), o3: 32.0 (#78)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| ARC-AGI-2 | 52.6% | 6.5% |
| SimpleBench | 70% | 53.1% |
| Kagi LLM Benchmark | 83.5% | 67.6% |
| ARC-AGI-1 | 87.2% | 60.8% |
| CritPt | 15.4% | 1.4% |
| Chess Puzzles | 36% | 38% |
| LMArena Hard Prompts | 1462 | 1402 |
| DTBench | 96.5% | 84.8% |
| LMCA | 45.2% | 39.7% |
| Epoch Capabilities Index | 153.92 | 146.86 |
| NYT Connections (extended) | 79.9% | — |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| Surface Evolver Bench | 74.4% | — |
| ForecastBench | — | 62.5 |
Math Grok 4.5 leads
Grok 4.5: 60.9 (#35), o3: 50.2 (#58)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 57.2% | 33.3% |
| OTIS Mock AIME 2024-2025 | 97.8% | 84.4% |
| LMArena Math | 1459 | 1426 |
| FrontierMath Tier 4 | 24.4% | — |
| ProofBench | 31% | — |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Grok 4.5 leads
Grok 4.5: 62.3 (#24), o3: 54.6 (#52)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| GPQA Diamond | 93.4% | 81.8% |
| SimpleQA Verified | 48.3% | 49.4% |
| LMArena Expert | 1466 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
Multimodal o3 leads
Grok 4.5: 37.6 (#72), o3: 41.4 (#36)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| LMArena Vision | 1288 | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
| Blueprint-Bench 2 | 27.3% | — |
| Furniture Assembly | 22.5% | — |
| LMArena Document | 1452 | — |
Multilingual Grok 4.5 leads
Grok 4.5: 54.4 (#42), o3: 51.7 (#105)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| LMArena Non-English | 1440 | 1401 |
| LMArena Chinese | 1496 | 1437 |
| LMArena French | 1456 | 1430 |
| LMArena German | 1446 | 1420 |
| LMArena Japanese | 1428 | 1403 |
| LMArena Korean | 1404 | 1370 |
| LMArena Russian | 1448 | 1406 |
| LMArena Spanish | 1450 | 1395 |
Instruction Following Grok 4.5 leads
Grok 4.5: 76.0 (#48), o3: 72.8 (#127)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| LMArena Instruction Following | 1446 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
Grok 4.5: 44.8 (#56), o3: 53.3 (#6)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| LMArena Longer Query | 1463 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference Grok 4.5 leads
Grok 4.5: 65.8 (#42), o3: 63.5 (#64)
| Benchmark | Grok 4.5 | o3 |
|---|---|---|
| LMArena Text | 1448 | 1410 |
| LMArena Creative Writing | 1442 | 1359 |
| EQ-Bench Creative Writing | 1579 | 1676 |
| LMArena Multi-Turn | 1456 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| WildBench | — | 86.1% |
Frequently asked questions
Is Grok 4.5 better than o3?
Grok 4.5 is the stronger model overall, scoring 55.0 to 47.5 on the Noometry Index.
Which is cheaper, Grok 4.5 or o3?
Grok 4.5 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o3 lists at $2 and $8.
Is Grok 4.5 or o3 better for coding?
Grok 4.5 scores higher on coding benchmarks: 52.2 versus 46.8 in the Noometry coding category.
Which has the bigger context window?
Grok 4.5 does, with 500K tokens against 200K.
How many benchmarks do Grok 4.5 and o3 share?
35 benchmarks have published results for both models. Grok 4.5 has 52 scored results on Noometry and o3 has 63.