Noometry

Model comparison

Gemma 1.1 7b IT vs GLM-5.3-Flash

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 31.3 on the Noometry Index.

Last verified . 17 shared benchmarks.

Gemma 1.1 7b IT Google

31.3

Rank #277 Confirmed

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Gemma 1.1 7b IT scores higher in 0 categories and GLM-5.3-Flash in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.3-Flash leads 65.3 to 30.4.

Side by side

Gemma 1.1 7b ITGLM-5.3-Flash
ProviderGoogleZ.ai (Zhipu)
Noometry Index31.351.8
Released—2026-08-20
WeightsOpenOpen
Context window—1M
Max output—131K
Input $ / M tokens—$0.15
Output $ / M tokens—$0.50
Results tracked1940

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Category by category

Coding GLM-5.3-Flash leads

Gemma 1.1 7b IT: 31.5 (#284), GLM-5.3-Flash: 53.1 (#31)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Coding10841508
DeepSWE—63.4%
FrontierCode—31.8%
CursorBench—36.8%
LMArena WebDev—1609
FrontierSWE—18.1%
SciCode—51.6%
ALE-Bench—303.55
HumanEval+35.4%—
MBPP+45%—

Agentic & Tool Use Not comparable

Gemma 1.1 7b IT: —, GLM-5.3-Flash: 34.2 (#47)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
APEX-Agents—52.8%
GDP.pdf—14%

Reasoning GLM-5.3-Flash leads

Gemma 1.1 7b IT: 20.5 (#238), GLM-5.3-Flash: 48.0 (#42)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Hard Prompts10711491
ARC-AGI-2—65.8%
ARC-AGI-1—91%
CritPt—15.4%
Chess Puzzles—14%
Mystery Game Puzzles—8%
Surface Evolver Bench—52.5%
Bench to the Future 3—0.15
Epoch Capabilities Index—151.88

Math GLM-5.3-Flash leads

Gemma 1.1 7b IT: 32.0 (#220), GLM-5.3-Flash: 53.3 (#47)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Math11071500
FrontierMath (Tiers 1-3)—55.8%
FrontierMath Tier 4—17.1%
OTIS Mock AIME 2024-2025—93.9%
ProofBench—21%

Knowledge GLM-5.3-Flash leads

Gemma 1.1 7b IT: 28.3 (#247), GLM-5.3-Flash: 58.4 (#36)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Expert10391513
GPQA Diamond—90.2%

Multimodal Not comparable

Gemma 1.1 7b IT: —, GLM-5.3-Flash: 42.8 (#27)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Vision—1296

Multilingual GLM-5.3-Flash leads

Gemma 1.1 7b IT: 28.1 (#273), GLM-5.3-Flash: 56.0 (#25)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Non-English10521462
LMArena Chinese10611527
LMArena French10651496
LMArena German10541470
LMArena Japanese9711429
LMArena Korean9881446
LMArena Russian10461469
LMArena Spanish10491471

Instruction Following GLM-5.3-Flash leads

Gemma 1.1 7b IT: 54.0 (#283), GLM-5.3-Flash: 77.5 (#20)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Instruction Following10571478

Long Context GLM-5.3-Flash leads

Gemma 1.1 7b IT: 32.1 (#272), GLM-5.3-Flash: 45.4 (#39)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Longer Query10561482

Writing & Preference GLM-5.3-Flash leads

Gemma 1.1 7b IT: 30.4 (#288), GLM-5.3-Flash: 65.3 (#50)

BenchmarkGemma 1.1 7b ITGLM-5.3-Flash
LMArena Text10941471
LMArena Creative Writing10601442
LMArena Multi-Turn10401467

Frequently asked questions

Is Gemma 1.1 7b IT better than GLM-5.3-Flash?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 31.3 on the Noometry Index.

Is Gemma 1.1 7b IT or GLM-5.3-Flash better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 31.5 in the Noometry coding category.

How many benchmarks do Gemma 1.1 7b IT and GLM-5.3-Flash share?

17 benchmarks have published results for both models. Gemma 1.1 7b IT has 19 scored results on Noometry and GLM-5.3-Flash has 40.

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