Model comparison

Mercury vs Qwen3.5-Flash

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 37.6 on the Noometry Index.

Last verified . 8 shared benchmarks.

Mercury Inception

37.6

Rank #199 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.5

Rank #112 Confirmed

Summary

  • They share 8 benchmarks with published results for both. Mercury scores higher in 1 category and Qwen3.5-Flash in 5 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.5-Flash leads 33.7 to 17.5.

Side by side

Mercury and Qwen3.5-Flash specifications
MercuryQwen3.5-Flash
ProviderInceptionAlibaba (Qwen)
Noometry Index37.642.5
Released—2026-02-23
WeightsProprietaryProprietary
Context window—1M
Max output—66K
Input $ / M tokens—$0.10
Output $ / M tokens—$0.40
Results tracked932

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Category by category

Coding Mercury leads

Mercury: 38.7 (#170), Qwen3.5-Flash: 34.2 (#242)

Coding benchmarks
BenchmarkMercuryQwen3.5-Flash
LMArena Coding13221412
LMArena WebDev—1244
ALE-Bench—221.8

Agentic & Tool Use Not comparable

Mercury: —, Qwen3.5-Flash: —

Agentic & Tool Use benchmarks
BenchmarkMercuryQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

Mercury: 17.5 (#293), Qwen3.5-Flash: 33.7 (#72)

Reasoning benchmarks
BenchmarkMercuryQwen3.5-Flash
LMArena Hard Prompts12851403
Kagi LLM Benchmark21.6%—
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math Not comparable

Mercury: —, Qwen3.5-Flash: 37.4 (#158)

Math benchmarks
BenchmarkMercuryQwen3.5-Flash
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%
LMArena Math—1407
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Not comparable

Mercury: —, Qwen3.5-Flash: 43.2 (#93)

Knowledge benchmarks
BenchmarkMercuryQwen3.5-Flash
GPQA Diamond—82.3%
SimpleQA Verified—20.3%
Vectara Hallucination Rate—10.5%
LMArena Expert—1407

Multilingual Qwen3.5-Flash leads

Mercury: 41.6 (#206), Qwen3.5-Flash: 50.5 (#121)

Multilingual benchmarks
BenchmarkMercuryQwen3.5-Flash
LMArena Non-English12601385
LMArena Chinese—1446
LMArena French—1412
LMArena German—1390
LMArena Japanese—1368
LMArena Korean—1344
LMArena Russian—1379
LMArena Spanish—1400

Instruction Following Qwen3.5-Flash leads

Mercury: 65.2 (#224), Qwen3.5-Flash: 72.6 (#139)

Instruction Following benchmarks
BenchmarkMercuryQwen3.5-Flash
LMArena Instruction Following12391374

Long Context Qwen3.5-Flash leads

Mercury: 38.4 (#198), Qwen3.5-Flash: 42.4 (#124)

Long Context benchmarks
BenchmarkMercuryQwen3.5-Flash
LMArena Longer Query12661392

Writing & Preference Qwen3.5-Flash leads

Mercury: 46.2 (#221), Qwen3.5-Flash: 57.9 (#122)

Writing & Preference benchmarks
BenchmarkMercuryQwen3.5-Flash
LMArena Text12821397
LMArena Creative Writing11911343
LMArena Multi-Turn12821393

Frequently asked questions

Is Mercury better than Qwen3.5-Flash?

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 37.6 on the Noometry Index.

Is Mercury or Qwen3.5-Flash better for coding?

Mercury scores higher on coding benchmarks: 38.7 versus 34.2 in the Noometry coding category.

How many benchmarks do Mercury and Qwen3.5-Flash share?

8 benchmarks have published results for both models. Mercury has 9 scored results on Noometry and Qwen3.5-Flash has 32.

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