Model comparison

Mercury 2 vs Qwen2.5 7B Instruct

Mercury 2 is the stronger model overall, scoring 39.1 to 29.0 on the Noometry Index.

Last verified October 11, 2026. 0 shared benchmarks.

Mercury 2 Inception

39.1

Rank #175 Confirmed

Qwen2.5 7B Instruct

Alibaba (Qwen)

29.0

Rank #320 Confirmed

Summary

The widest gap is in knowledge, where Mercury 2 leads 36.2 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.

Side by side

Mercury 2 and Qwen2.5 7B Instruct specifications
	Mercury 2	Qwen2.5 7B Instruct
Provider	Inception	Alibaba (Qwen)
Noometry Index	39.1	29.0
Released	2026-02-20	2024-09
Weights	Proprietary	Open
Context window	128K	131K
Max output	50K	8K
Input $ / M tokens	$0.25	$0.17
Output $ / M tokens	$0.75	$0.70
Results tracked	17	15

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Qwen2.5 7B Instruct leads

Mercury 2: 33.5 (#255), Qwen2.5 7B Instruct: 36.5 (#208)

Coding benchmarks
Benchmark	Mercury 2	Qwen2.5 7B Instruct
LMArena WebDev	1171	—
SciCode	38.7%	—
WeirdML	43.2%	—
BigCodeBench Instruct	—	37.6%
LMArena Coding	1391	—
BigCodeBench Complete	—	46.1%
ALE-Bench	785.58	—

Agentic & Tool Use Not comparable

Mercury 2: —, Qwen2.5 7B Instruct: 23.8 (#124)

Agentic & Tool Use benchmarks
Benchmark	Mercury 2	Qwen2.5 7B Instruct
BALROG	—	7.8%

Reasoning Mercury 2 leads

Mercury 2: 23.8 (#170), Qwen2.5 7B Instruct: 14.8 (#322)

Reasoning benchmarks
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	—	118.51

Math Not comparable

Mercury 2: —, Qwen2.5 7B Instruct: 12.6 (#306)

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

Knowledge Mercury 2 leads

Mercury 2: 36.2 (#172), Qwen2.5 7B Instruct: 17.0 (#286)

Knowledge benchmarks
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 Not comparable

Mercury 2: 46.6 (#157), Qwen2.5 7B Instruct: —

Multilingual benchmarks
Benchmark	Mercury 2	Qwen2.5 7B Instruct
LMArena Non-English	1331	—
LMArena Chinese	1417	—
LMArena Russian	1304	—

Instruction Following Mercury 2 leads

Mercury 2: 70.2 (#165), Qwen2.5 7B Instruct: 63.2 (#231)

Instruction Following benchmarks
Benchmark	Mercury 2	Qwen2.5 7B Instruct
IFEval	—	74.1%
LMArena Instruction Following	1329	—

Long Context Not comparable

Mercury 2: 40.5 (#154), Qwen2.5 7B Instruct: —

Long Context benchmarks
Benchmark	Mercury 2	Qwen2.5 7B Instruct
LMArena Longer Query	1330	—

Writing & Preference Mercury 2 leads

Mercury 2: 53.8 (#155), Qwen2.5 7B Instruct: 48.8 (#195)

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

Frequently asked questions

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

Mercury 2 is the stronger model overall, scoring 39.1 to 29.0 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: 36.5 versus 33.5 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.