Model comparison
GPT-4o vs Mercury 2
Mercury 2 is the stronger model overall, scoring 39.1 to 28.6 on the Noometry Index.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GPT-4o scores higher in 0 categories and Mercury 2 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Mercury 2 leads 23.8 to 9.4.
- The biggest single-benchmark swing is WeirdML: 25.1% for GPT-4o and 43.2% for Mercury 2.
- Mercury 2 is cheaper at $0.25 / $0.75 per million input/output tokens, against $2.50 / $10 for GPT-4o.
Side by side
| GPT-4o | Mercury 2 | |
|---|---|---|
| Provider | OpenAI | Inception |
| Noometry Index | 28.6 | 39.1 |
| Released | 2024-05-13 | 2026-02-20 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 128K |
| Max output | 16K | 50K |
| Input $ / M tokens | $2.50 | $0.25 |
| Output $ / M tokens | $10 | $0.75 |
| Results tracked | 72 | 17 |
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Category by category
Coding Mercury 2 leads
GPT-4o: 24.8 (#328), Mercury 2: 33.5 (#255)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| WeirdML | 25.1% | 43.2% |
| LMArena Coding | 1297 | 1391 |
| SWE-bench Verified | 31% | — |
| SWE-bench Verified (bash only) | 21.6% | — |
| Aider Polyglot | 45.3% | — |
| LMArena WebDev | — | 1171 |
| SciCode | — | 38.7% |
| GSO | 0% | — |
| BigCodeBench Instruct | 51.1% | — |
| LiveBench Coding | 51.4% | — |
| BigCodeBench Complete | 61.1% | — |
| CadEval | 26% | — |
| ALE-Bench | — | 785.58 |
| HumanEval+ | 87.2% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Not comparable
GPT-4o: 21.0 (#141), Mercury 2: —
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| GDPval | 9.9% | — |
| TheAgentCompany | 8.6% | — |
| Cybench | 12.5% | — |
| BALROG | 32.3% | — |
| LMArena Search | 1006 | — |
| METR Time Horizons | 40.8% | — |
Reasoning Mercury 2 leads
GPT-4o: 9.4 (#343), Mercury 2: 23.8 (#170)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| CritPt | 0% | 0.8% |
| LMArena Hard Prompts | 1281 | 1362 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 17.8% | — |
| ARC-AGI-1 | 4.5% | — |
| Chess Puzzles | 13% | — |
| EnigmaEval | 0.8% | — |
| LiveBench Reasoning | 55.8% | — |
| DTBench | 64.5% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 16.6% | — |
| Epoch Capabilities Index | 128.97 | — |
| ForecastBench | 57.7 | — |
| LiveBench | 55.3% | — |
Math Not comparable
GPT-4o: 10.6 (#312), Mercury 2: —
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.4% | — |
| OTIS Mock AIME 2024-2025 | 6.4% | — |
| Omni-MATH | 29.3% | — |
| LiveBench Math | 49.5% | — |
| LMArena Math | 1285 | — |
| MATH Level 5 | 53.3% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Mercury 2 leads
GPT-4o: 28.8 (#242), Mercury 2: 36.2 (#172)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| Vectara Hallucination Rate | 9.6% | 12.3% |
| LMArena Expert | 1250 | 1358 |
| GPQA Diamond | 49.2% | — |
| Humanity's Last Exam | 2.7% | — |
| SimpleQA Verified | 26% | — |
| MMLU-Pro | 71.3% | — |
| Confabulations | 15.3% | — |
| GPQA (HELM) | 52% | — |
| MMLU | 88.1% | — |
Multimodal Not comparable
GPT-4o: 34.5 (#91), Mercury 2: —
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| LMArena Vision | 1137 | — |
| Video-MME | 71.9% | — |
| GeoBench | 71% | — |
| VPCT | 40% | — |
| ScienceQA | 88.5% | — |
Multilingual Mercury 2 leads
GPT-4o: 43.2 (#186), Mercury 2: 46.6 (#157)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| LMArena Non-English | 1283 | 1331 |
| LMArena Chinese | 1277 | 1417 |
| LMArena Russian | 1286 | 1304 |
| LMArena French | 1304 | — |
| LMArena German | 1282 | — |
| LMArena Japanese | 1257 | — |
| LMArena Korean | 1234 | — |
| LMArena Spanish | 1292 | — |
Instruction Following Mercury 2 leads
GPT-4o: 66.6 (#207), Mercury 2: 70.2 (#165)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| LMArena Instruction Following | 1278 | 1329 |
| LiveBench Instruction Following | 68.6% | — |
| IFEval | 81.7% | — |
Long Context Mercury 2 leads
GPT-4o: 39.4 (#179), Mercury 2: 40.5 (#154)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| LMArena Longer Query | 1289 | 1330 |
| Fiction.LiveBench | 66.7% | — |
Writing & Preference Mercury 2 leads
GPT-4o: 52.6 (#166), Mercury 2: 53.8 (#155)
| Benchmark | GPT-4o | Mercury 2 |
|---|---|---|
| LMArena Text | 1300 | 1355 |
| LMArena Creative Writing | 1292 | 1289 |
| LMArena Multi-Turn | 1302 | 1358 |
| Short-Story Creative Writing | 81.8% | — |
| WildBench | 82.8% | — |
| LiveBench Language | 47.6% | — |
Frequently asked questions
Is GPT-4o better than Mercury 2?
Mercury 2 is the stronger model overall, scoring 39.1 to 28.6 on the Noometry Index.
Which is cheaper, GPT-4o or Mercury 2?
Mercury 2 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GPT-4o lists at $2.50 and $10.
Is GPT-4o or Mercury 2 better for coding?
Mercury 2 scores higher on coding benchmarks: 33.5 versus 24.8 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do GPT-4o and Mercury 2 share?
14 benchmarks have published results for both models. GPT-4o has 72 scored results on Noometry and Mercury 2 has 17.