Model comparison
GPT-4o vs Grok-2 (Dec 2024)
Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 28.6 on the Noometry Index.
Last verified . 34 shared benchmarks.
Summary
- They share 34 benchmarks with published results for both. GPT-4o scores higher in 3 categories and Grok-2 (Dec 2024) in 5 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok-2 (Dec 2024) leads 20.8 to 10.6.
- The biggest single-benchmark swing is Short-Story Creative Writing: 81.8% for GPT-4o and 63.6% for Grok-2 (Dec 2024).
Side by side
| GPT-4o | Grok-2 (Dec 2024) | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 28.6 | 33.7 |
| Released | 2024-05-13 | 2024-08-13 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | — |
| Max output | 16K | — |
| Input $ / M tokens | $2.50 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 72 | 34 |
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Category by category
Coding Grok-2 (Dec 2024) leads
GPT-4o: 24.8 (#328), Grok-2 (Dec 2024): 33.3 (#258)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| WeirdML | 25.1% | 22.2% |
| LiveBench Coding | 51.4% | 46.4% |
| LMArena Coding | 1297 | 1287 |
| SWE-bench Verified | 31% | — |
| SWE-bench Verified (bash only) | 21.6% | — |
| Aider Polyglot | 45.3% | — |
| GSO | 0% | — |
| BigCodeBench Instruct | 51.1% | — |
| BigCodeBench Complete | 61.1% | — |
| CadEval | 26% | — |
| HumanEval+ | 87.2% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Not comparable
GPT-4o: 21.0 (#141), Grok-2 (Dec 2024): —
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| GDPval | 9.9% | — |
| TheAgentCompany | 8.6% | — |
| Cybench | 12.5% | — |
| BALROG | 32.3% | — |
| LMArena Search | 1006 | — |
| METR Time Horizons | 40.8% | — |
Reasoning Grok-2 (Dec 2024) leads
GPT-4o: 9.4 (#343), Grok-2 (Dec 2024): 16.9 (#299)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| SimpleBench | 17.8% | 22.7% |
| LiveBench Reasoning | 55.8% | 54.8% |
| LMArena Hard Prompts | 1281 | 1272 |
| DTBench | 64.5% | 65.2% |
| LiveBench Data Analysis | 60.9% | 54.5% |
| Epoch Capabilities Index | 128.97 | 130.48 |
| LiveBench | 55.3% | 54.3% |
| ARC-AGI-2 | 0% | — |
| ARC-AGI-1 | 4.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | 13% | — |
| EnigmaEval | 0.8% | — |
| LMCA | 16.6% | — |
| ForecastBench | 57.7 | — |
Math Grok-2 (Dec 2024) leads
GPT-4o: 10.6 (#312), Grok-2 (Dec 2024): 20.8 (#284)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.4% | 11.5% |
| LiveBench Math | 49.5% | 54.9% |
| LMArena Math | 1285 | 1283 |
| MATH Level 5 | 53.3% | 63.5% |
| FrontierMath (Feb 2025 set) | 0.3% | 0.7% |
| FrontierMath (Tiers 1-3) | 0.4% | — |
| Omni-MATH | 29.3% | — |
Knowledge Too close to call
GPT-4o: 28.8 (#242), Grok-2 (Dec 2024): 29.8 (#233)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| GPQA Diamond | 49.2% | 53.8% |
| Confabulations | 15.3% | 20.1% |
| LMArena Expert | 1250 | 1254 |
| Humanity's Last Exam | 2.7% | — |
| SimpleQA Verified | 26% | — |
| MMLU-Pro | 71.3% | — |
| Vectara Hallucination Rate | 9.6% | — |
| GPQA (HELM) | 52% | — |
| MMLU | 88.1% | — |
Multimodal Not comparable
GPT-4o: 34.5 (#91), Grok-2 (Dec 2024): —
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Vision | 1137 | — |
| Video-MME | 71.9% | — |
| GeoBench | 71% | — |
| VPCT | 40% | — |
| ScienceQA | 88.5% | — |
Multilingual Too close to call
GPT-4o: 43.2 (#186), Grok-2 (Dec 2024): 43.1 (#188)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Non-English | 1283 | 1282 |
| LMArena Chinese | 1277 | 1289 |
| LMArena French | 1304 | 1318 |
| LMArena German | 1282 | 1287 |
| LMArena Japanese | 1257 | 1244 |
| LMArena Korean | 1234 | 1237 |
| LMArena Russian | 1286 | 1286 |
| LMArena Spanish | 1292 | 1281 |
Instruction Following Too close to call
GPT-4o: 66.6 (#207), Grok-2 (Dec 2024): 66.9 (#202)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| LiveBench Instruction Following | 68.6% | 69.6% |
| LMArena Instruction Following | 1278 | 1270 |
| IFEval | 81.7% | — |
Long Context Too close to call
GPT-4o: 39.4 (#179), Grok-2 (Dec 2024): 38.8 (#190)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Longer Query | 1289 | 1276 |
| Fiction.LiveBench | 66.7% | — |
Writing & Preference GPT-4o leads
GPT-4o: 52.6 (#166), Grok-2 (Dec 2024): 48.6 (#198)
| Benchmark | GPT-4o | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Text | 1300 | 1305 |
| LMArena Creative Writing | 1292 | 1284 |
| Short-Story Creative Writing | 81.8% | 63.6% |
| LMArena Multi-Turn | 1302 | 1290 |
| LiveBench Language | 47.6% | 45.6% |
| WildBench | 82.8% | — |
Frequently asked questions
Is GPT-4o better than Grok-2 (Dec 2024)?
Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 28.6 on the Noometry Index.
Is GPT-4o or Grok-2 (Dec 2024) better for coding?
Grok-2 (Dec 2024) scores higher on coding benchmarks: 33.3 versus 24.8 in the Noometry coding category.
How many benchmarks do GPT-4o and Grok-2 (Dec 2024) share?
34 benchmarks have published results for both models. GPT-4o has 72 scored results on Noometry and Grok-2 (Dec 2024) has 34.