Noometry

Model comparison

GLM-5.3 vs Qwen3.7 Max

GLM-5.3 is the stronger model overall, scoring 54.8 to 51.5 on the Noometry Index.

Last verified . 28 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Qwen3.7 Max Alibaba (Qwen)

51.5

Rank #42 Confirmed

Summary

  • They share 28 benchmarks with published results for both. GLM-5.3 scores higher in 4 categories and Qwen3.7 Max in 5 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in agentic & tool use, where GLM-5.3 leads 36.4 to 22.1.
  • The biggest single-benchmark swing is ProofBench: 49% for GLM-5.3 and 26% for Qwen3.7 Max.
  • GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
  • GLM-5.3 has downloadable open weights; the other is API-only.

Side by side

GLM-5.3Qwen3.7 Max
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index54.851.5
Released2026-08-142026-05-19
WeightsOpenProprietary
Context window1M1M
Max output131K131K
Input $ / M tokens$1.40$2.50
Output $ / M tokens$4.40$7.50
Results tracked4233

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Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), Qwen3.7 Max: 50.4 (#45)

BenchmarkGLM-5.3Qwen3.7 Max
LMArena WebDev16221515
SciCode59%48.8%
LMArena Coding14961498
ALE-Bench1,3171,189
SWE-bench Verified—77.3%
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
FrontierSWE30.2%—
WeirdML75.4%—

Agentic & Tool Use GLM-5.3 leads

GLM-5.3: 36.4 (#38), Qwen3.7 Max: 22.1 (#135)

BenchmarkGLM-5.3Qwen3.7 Max
APEX-Agents56.6%—
GBAEval—0.4%
Vending-Bench 28,164—

Reasoning Qwen3.7 Max leads

GLM-5.3: 46.1 (#46), Qwen3.7 Max: 49.2 (#38)

BenchmarkGLM-5.3Qwen3.7 Max
NYT Connections (extended)74.2%85.1%
CritPt19.1%13.4%
Chess Puzzles21%19%
LMArena Hard Prompts14891483
Mystery Game Puzzles33%32%
DTBench87.7%92.3%
LMCA55.5%44%
Epoch Capabilities Index155.61153.68
SimpleBench—70.4%
EBR-Bench—9.5%
Bench to the Future 30.15—

Math Too close to call

GLM-5.3: 62.3 (#33), Qwen3.7 Max: 62.4 (#32)

BenchmarkGLM-5.3Qwen3.7 Max
FrontierMath (Tiers 1-3)68.8%64.6%
FrontierMath Tier 429.3%34.1%
OTIS Mock AIME 2024-202591.1%95.6%
ProofBench49%26%
LMArena Math14891490

Knowledge Qwen3.7 Max leads

GLM-5.3: 58.3 (#37), Qwen3.7 Max: 61.6 (#28)

BenchmarkGLM-5.3Qwen3.7 Max
GPQA Diamond90.9%90.9%
SimpleQA Verified41%55.8%
LMArena Expert15161488

Multilingual Qwen3.7 Max leads

GLM-5.3: 55.7 (#28), Qwen3.7 Max: 56.9 (#15)

BenchmarkGLM-5.3Qwen3.7 Max
LMArena Non-English14571474
LMArena Chinese15281530
LMArena Russian14631484
LMArena French1499—
LMArena German1499—
LMArena Japanese1453—
LMArena Korean1472—
LMArena Spanish1460—

Instruction Following Too close to call

GLM-5.3: 77.5 (#23), Qwen3.7 Max: 76.7 (#38)

BenchmarkGLM-5.3Qwen3.7 Max
LMArena Instruction Following14771460

Long Context Too close to call

GLM-5.3: 45.4 (#41), Qwen3.7 Max: 45.4 (#40)

BenchmarkGLM-5.3Qwen3.7 Max
LMArena Longer Query14821482

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), Qwen3.7 Max: 65.0 (#54)

BenchmarkGLM-5.3Qwen3.7 Max
LMArena Text14711476
LMArena Creative Writing14571449
LMArena Multi-Turn14721481
EQ-Bench Creative Writing2075—
EQ-Bench 4—1110

Frequently asked questions

Is GLM-5.3 better than Qwen3.7 Max?

GLM-5.3 is the stronger model overall, scoring 54.8 to 51.5 on the Noometry Index.

Which is cheaper, GLM-5.3 or Qwen3.7 Max?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.

Is GLM-5.3 or Qwen3.7 Max better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 50.4 in the Noometry coding category.

Which has the bigger context window?

Both accept 1M tokens.

How many benchmarks do GLM-5.3 and Qwen3.7 Max share?

28 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Qwen3.7 Max has 33.

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