Model comparison

Mercury 2.5 vs Qwen3 32B

Qwen3 32B is the stronger model overall, scoring 39.2 to 33.5 on the Noometry Index. Mercury 2.5 costs 18× less per token, which makes it the better buy when Qwen3 32B's lead doesn't matter for your workload.

Last verified October 10, 2026. 2 shared benchmarks.

Mercury 2.5 Inception

33.5

Rank #242 Reported

Qwen3 32B

Alibaba (Qwen)

39.2

Rank #172 Confirmed

Summary

They share 2 benchmarks with published results for both. Mercury 2.5 scores higher in 2 categories and Qwen3 32B in 1 category; 3 gaps are clear of the uncertainty.
The widest gap is in math, where Qwen3 32B leads 39.7 to 23.3.
Mercury 2.5 is cheaper at $0.04 / $0.15 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
Mercury 2.5 accepts more context: 260K tokens versus 131K.
Qwen3 32B has downloadable open weights; the other is API-only.

Side by side

Mercury 2.5 and Qwen3 32B specifications
	Mercury 2.5	Qwen3 32B
Provider	Inception	Alibaba (Qwen)
Noometry Index	33.5	39.2
Released	2026-09-08	2025-04
Weights	Proprietary	Open
Context window	260K	131K
Max output	66K	16K
Input $ / M tokens	$0.04	$0.70
Output $ / M tokens	$0.15	$2.80
Results tracked	4	26

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Category by category

Coding Mercury 2.5 leads

Mercury 2.5: 39.5 (#156), Qwen3 32B: 37.7 (#190)

Coding benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
SciCode	38.5%	35.4%
Aider Polyglot	—	40%
LMArena Coding	—	1358
ALE-Bench	301.65	—

Agentic & Tool Use Not comparable

Mercury 2.5: —, Qwen3 32B: 32.6 (#62)

Agentic & Tool Use benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
Berkeley Function Calling Leaderboard	—	48.7%

Reasoning Mercury 2.5 leads

Mercury 2.5: 22.4 (#193), Qwen3 32B: 20.2 (#241)

Reasoning benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
CritPt	0%	0.3%
Kagi LLM Benchmark	—	54.9%
Chess Puzzles	—	5%
LMArena Hard Prompts	—	1334
DTBench	—	67.5%
LMCA	—	17.3%
Epoch Capabilities Index	—	138.51

Math Qwen3 32B leads

Mercury 2.5: 23.3 (#272), Qwen3 32B: 39.7 (#99)

Math benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
OTIS Mock AIME 2024-2025	—	66.9%
ProofBench	3%	—
LMArena Math	—	1399

Knowledge Not comparable

Mercury 2.5: —, Qwen3 32B: 40.0 (#125)

Knowledge benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
GPQA Diamond	—	65.7%
Vectara Hallucination Rate	—	5.9%
LMArena Expert	—	1362

Multilingual Not comparable

Mercury 2.5: —, Qwen3 32B: 45.6 (#167)

Multilingual benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
LMArena Non-English	—	1317
LMArena Chinese	—	1357
LMArena German	—	1341
LMArena Russian	—	1311

Instruction Following Not comparable

Mercury 2.5: —, Qwen3 32B: 68.9 (#179)

Instruction Following benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
LMArena Instruction Following	—	1305

Long Context Not comparable

Mercury 2.5: —, Qwen3 32B: 43.8 (#87)

Long Context benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
Fiction.LiveBench	—	74.2%
LMArena Longer Query	—	1327

Writing & Preference Not comparable

Mercury 2.5: —, Qwen3 32B: 52.9 (#163)

Writing & Preference benchmarks
Benchmark	Mercury 2.5	Qwen3 32B
LMArena Text	—	1340
LMArena Creative Writing	—	1297
LMArena Multi-Turn	—	1331

Frequently asked questions

Is Mercury 2.5 better than Qwen3 32B?

Which is cheaper, Mercury 2.5 or Qwen3 32B?

Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.

Is Mercury 2.5 or Qwen3 32B better for coding?

Mercury 2.5 scores higher on coding benchmarks: 39.5 versus 37.7 in the Noometry coding category.

Which has the bigger context window?

Mercury 2.5 does, with 260K tokens against 131K.

How many benchmarks do Mercury 2.5 and Qwen3 32B share?

2 benchmarks have published results for both models. Mercury 2.5 has 4 scored results on Noometry and Qwen3 32B has 26.