Model comparison

Mercury 2 vs Qwen3.5-9B

Mercury 2 is the stronger model overall, scoring 39.1 to 33.8 on the Noometry Index. Qwen3.5-9B costs 3.3× less per token, which makes it the better buy when Mercury 2's lead doesn't matter for your workload.

Last verified October 10, 2026. 2 shared benchmarks.

Mercury 2 Inception

39.1

Rank #175 Confirmed

Qwen3.5-9B

Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

They share 2 benchmarks with published results for both. Mercury 2 scores higher in 1 category and Qwen3.5-9B in 2 categories; 2 gaps are clear of the uncertainty.
The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 36.2.
The biggest single-benchmark swing is SciCode: 38.7% for Mercury 2 and 27.5% for Qwen3.5-9B.
Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.25 / $0.75 for Mercury 2.
Qwen3.5-9B accepts more context: 262K tokens versus 128K.
Qwen3.5-9B has downloadable open weights; the other is API-only.

Side by side

Mercury 2 and Qwen3.5-9B specifications
	Mercury 2	Qwen3.5-9B
Provider	Inception	Alibaba (Qwen)
Noometry Index	39.1	33.8
Released	2026-02-20	2026-02-23
Weights	Proprietary	Open
Context window	128K	262K
Max output	50K	66K
Input $ / M tokens	$0.25	$0.10
Output $ / M tokens	$0.75	$0.15
Results tracked	17	10

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Category by category

Coding Qwen3.5-9B leads

Mercury 2: 33.5 (#255), Qwen3.5-9B: 35.9 (#217)

Coding benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
SciCode	38.7%	27.5%
LMArena WebDev	1171	—
WeirdML	43.2%	—
LMArena Coding	1391	—
ALE-Bench	785.58	—

Agentic & Tool Use Not comparable

Mercury 2: —, Qwen3.5-9B: 14.5 (#151)

Agentic & Tool Use benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
Terminal-Bench	—	9.2%

Reasoning Too close to call

Mercury 2: 23.8 (#170), Qwen3.5-9B: 23.1 (#182)

Reasoning benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
CritPt	0.8%	0.3%
Chess Puzzles	—	12%
LMArena Hard Prompts	1362	—
DTBench	—	71.2%
LMCA	—	24.5%
Epoch Capabilities Index	—	139.46

Math Not comparable

Mercury 2: —, Qwen3.5-9B: 34.8 (#192)

Math benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
MathArena Final-Answer Competitions	—	48.5%
OTIS Mock AIME 2024-2025	—	61.7%

Knowledge Qwen3.5-9B leads

Mercury 2: 36.2 (#172), Qwen3.5-9B: 46.0 (#84)

Knowledge benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
GPQA Diamond	—	79%
Vectara Hallucination Rate	12.3%	—
LMArena Expert	1358	—

Multilingual Not comparable

Mercury 2: 46.6 (#157), Qwen3.5-9B: —

Multilingual benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
LMArena Non-English	1331	—
LMArena Chinese	1417	—
LMArena Russian	1304	—

Instruction Following Not comparable

Mercury 2: 70.2 (#165), Qwen3.5-9B: —

Instruction Following benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
LMArena Instruction Following	1329	—

Long Context Not comparable

Mercury 2: 40.5 (#154), Qwen3.5-9B: —

Long Context benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
LMArena Longer Query	1330	—

Writing & Preference Not comparable

Mercury 2: 53.8 (#155), Qwen3.5-9B: —

Writing & Preference benchmarks
Benchmark	Mercury 2	Qwen3.5-9B
LMArena Text	1355	—
LMArena Creative Writing	1289	—
LMArena Multi-Turn	1358	—

Frequently asked questions

Is Mercury 2 better than Qwen3.5-9B?

Which is cheaper, Mercury 2 or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Mercury 2 lists at $0.25 and $0.75.

Is Mercury 2 or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.9 versus 33.5 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 128K.

How many benchmarks do Mercury 2 and Qwen3.5-9B share?

2 benchmarks have published results for both models. Mercury 2 has 17 scored results on Noometry and Qwen3.5-9B has 10.