# gpt-oss-120b vs Mercury 2

> Mercury 2 is the stronger model overall, scoring 38.8 to 36.0 on the Noometry Index. gpt-oss-120b costs 5.3× less per token, which makes it the better buy when Mercury 2's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-oss-120b-vs-mercury-2
- Last updated: 2026-10-10
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. gpt-oss-120b scores higher in 2 categories and Mercury 2 in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where Mercury 2 leads 40.4 to 31.4.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.25 / $0.75 for Mercury 2.
- gpt-oss-120b accepts more context: 131K tokens versus 128K.
- gpt-oss-120b has downloadable open weights; the other is API-only.

## Snapshot

| | gpt-oss-120b | Mercury 2 |
|---|---|---|
| Provider | OpenAI | Inception |
| Noometry Index | 36.0 | 38.8 |
| Rank | 210 | 167 |
| Context | 131K | 128K |
| Input $/M | $0.037 | $0.25 |
| Output $/M | $0.17 | $0.75 |
| Weights | Open | Proprietary |

## Coding

- gpt-oss-120b: 33.2 (#251)
- Mercury 2: 33.2 (#250)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| SciCode | 36% | 38.7% |
| WeirdML | 48.2% | 43.2% |
| LMArena Coding | 1380 | 1391 |
| ALE-Bench | 575.62 | 785.58 |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| LMArena WebDev | — | 1170 |
| AlgoTune | 1.41 | — |

## Agentic & Tool Use

- gpt-oss-120b: 12.1 (#145)
- Mercury 2: —

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |

## Reasoning

- gpt-oss-120b: 19.5 (#236)
- Mercury 2: 23.0 (#170)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| CritPt | 1.1% | 0.8% |
| LMArena Hard Prompts | 1364 | 1362 |
| SimpleBench | 22.1% | — |
| Kagi LLM Benchmark | 58.6% | — |
| Chess Puzzles | 20% | — |
| Mystery Game Puzzles | 2% | — |
| DTBench | 76.3% | — |
| LMCA | 22.1% | — |
| Surface Evolver Bench | 25% | — |
| Epoch Capabilities Index | 139.94 | — |

## Math

- gpt-oss-120b: 50.6 (#43)
- Mercury 2: —

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| Omni-MATH | 68.8% | — |
| LMArena Math | 1388 | — |

## Knowledge

- gpt-oss-120b: 42.3 (#89)
- Mercury 2: 35.6 (#170)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| Vectara Hallucination Rate | 14.2% | 12.3% |
| LMArena Expert | 1356 | 1358 |
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| GPQA (HELM) | 68.4% | — |

## Multilingual

- gpt-oss-120b: 48.2 (#142)
- Mercury 2: 46.8 (#153)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| LMArena Non-English | 1350 | 1331 |
| LMArena Chinese | 1384 | 1416 |
| LMArena Russian | 1343 | 1303 |
| LMArena French | 1370 | — |
| LMArena German | 1355 | — |
| LMArena Japanese | 1332 | — |
| LMArena Korean | 1283 | — |
| LMArena Spanish | 1388 | — |

## Instruction Following

- gpt-oss-120b: 69.5 (#168)
- Mercury 2: 70.4 (#161)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| LMArena Instruction Following | 1318 | 1328 |
| IFEval | 83.6% | — |

## Long Context

- gpt-oss-120b: 31.4 (#273)
- Mercury 2: 40.4 (#149)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| LMArena Longer Query | 1319 | 1329 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- gpt-oss-120b: 46.7 (#213)
- Mercury 2: 54.0 (#151)

| Benchmark | gpt-oss-120b | Mercury 2 |
|---|---|---|
| LMArena Text | 1366 | 1355 |
| LMArena Creative Writing | 1274 | 1289 |
| LMArena Multi-Turn | 1340 | 1358 |
| Short-Story Creative Writing | 77.1% | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |

## FAQ

### Is gpt-oss-120b better than Mercury 2?

Mercury 2 is the stronger model overall, scoring 38.8 to 36.0 on the Noometry Index. gpt-oss-120b costs 5.3× less per token, which makes it the better buy when Mercury 2's lead doesn't matter for your workload.

### Which is cheaper, gpt-oss-120b or Mercury 2?

gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Mercury 2 lists at $0.25 and $0.75.

### Is gpt-oss-120b or Mercury 2 better for coding?

They score almost the same on coding (33.2 vs 33.2); test both on your own repository before choosing.

### Which has the bigger context window?

gpt-oss-120b does, with 131K tokens against 128K.

### How many benchmarks do gpt-oss-120b and Mercury 2 share?

16 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Mercury 2 has 17.