# Mercury 2 vs Qwen2.5 7B Instruct

> Mercury 2 is the stronger model overall, scoring 38.8 to 28.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/mercury-2-vs-qwen2-5-7b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in knowledge, where Mercury 2 leads 35.6 to 17.0.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $0.25 / $0.75 for Mercury 2.
- Qwen2.5 7B Instruct accepts more context: 131K tokens versus 128K.
- Qwen2.5 7B Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | Inception | Alibaba (Qwen) |
| Noometry Index | 38.8 | 28.6 |
| Rank | 167 | 314 |
| Context | 128K | 131K |
| Input $/M | $0.25 | $0.17 |
| Output $/M | $0.75 | $0.70 |
| Weights | Proprietary | Open |

## Coding

- Mercury 2: 33.2 (#250)
- Qwen2.5 7B Instruct: 35.9 (#204)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena WebDev | 1170 | — |
| SciCode | 38.7% | — |
| WeirdML | 43.2% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1391 | — |
| BigCodeBench Complete | — | 46.1% |
| ALE-Bench | 785.58 | — |

## Agentic & Tool Use

- Mercury 2: —
- Qwen2.5 7B Instruct: 23.5 (#117)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | — | 7.8% |

## Reasoning

- Mercury 2: 23.0 (#170)
- Qwen2.5 7B Instruct: 14.3 (#317)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| CritPt | 0.8% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1362 | — |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |
| Epoch Capabilities Index | — | 118.44 |

## Math

- Mercury 2: —
- Qwen2.5 7B Instruct: 11.8 (#300)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.5% |
| Omni-MATH | — | 29.4% |

## Knowledge

- Mercury 2: 35.6 (#170)
- Qwen2.5 7B Instruct: 17.0 (#281)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | — | 35.5% |
| MMLU-Pro | — | 53.9% |
| Vectara Hallucination Rate | 12.3% | — |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1358 | — |
| MMLU | — | 72.9% |

## Multilingual

- Mercury 2: 46.8 (#153)
- Qwen2.5 7B Instruct: —

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1331 | — |
| LMArena Chinese | 1416 | — |
| LMArena Russian | 1303 | — |

## Instruction Following

- Mercury 2: 70.4 (#161)
- Qwen2.5 7B Instruct: 63.4 (#226)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1328 | — |

## Long Context

- Mercury 2: 40.4 (#149)
- Qwen2.5 7B Instruct: —

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1329 | — |

## Writing & Preference

- Mercury 2: 54.0 (#151)
- Qwen2.5 7B Instruct: 48.8 (#194)

| Benchmark | Mercury 2 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1355 | — |
| LMArena Creative Writing | 1289 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1358 | — |

## FAQ

### Is Mercury 2 better than Qwen2.5 7B Instruct?

Mercury 2 is the stronger model overall, scoring 38.8 to 28.6 on the Noometry Index.

### Which is cheaper, Mercury 2 or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; Mercury 2 lists at $0.25 and $0.75.

### Is Mercury 2 or Qwen2.5 7B Instruct better for coding?

Qwen2.5 7B Instruct scores higher on coding benchmarks: 35.9 versus 33.2 in the Noometry coding category.

### Which has the bigger context window?

Qwen2.5 7B Instruct does, with 131K tokens against 128K.

### How many benchmarks do Mercury 2 and Qwen2.5 7B Instruct share?

0 benchmarks have published results for both models. Mercury 2 has 17 scored results on Noometry and Qwen2.5 7B Instruct has 15.