Noometry

Model comparison

GLM-5.3-Flash vs Sonar

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 38.5 on the Noometry Index.

Last verified . 0 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Sonar Perplexity

38.5

Rank #187 Confirmed

Summary

  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 21.1.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $1 / $1 for Sonar.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 128K.
  • GLM-5.3-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-5.3-FlashSonar
ProviderZ.ai (Zhipu)Perplexity
Noometry Index51.838.5
Released2026-08-202024-01-01
WeightsOpenProprietary
Context window1M128K
Max output131K4K
Input $ / M tokens$0.15$1
Output $ / M tokens$0.50$1
Results tracked407

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Sonar: 35.7 (#221)

BenchmarkGLM-5.3-FlashSonar
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
LiveBench Coding—35.1%
LMArena Coding1508—
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), Sonar: —

BenchmarkGLM-5.3-FlashSonar
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Sonar: 21.1 (#227)

BenchmarkGLM-5.3-FlashSonar
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
LiveBench Reasoning—46.3%
LMArena Hard Prompts1491—
Mystery Game Puzzles8%—
LiveBench Data Analysis—37.9%
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.88—
LiveBench—46.9%

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), Sonar: 33.7 (#200)

BenchmarkGLM-5.3-FlashSonar
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—
LiveBench Math—41.6%
LMArena Math1500—

Knowledge Not comparable

GLM-5.3-Flash: 58.4 (#36), Sonar: —

BenchmarkGLM-5.3-FlashSonar
GPQA Diamond90.2%—
LMArena Expert1513—

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), Sonar: —

BenchmarkGLM-5.3-FlashSonar
LMArena Vision1296—

Multilingual Not comparable

GLM-5.3-Flash: 56.0 (#25), Sonar: —

BenchmarkGLM-5.3-FlashSonar
LMArena Non-English1462—
LMArena Chinese1527—
LMArena French1496—
LMArena German1470—
LMArena Japanese1429—
LMArena Korean1446—
LMArena Russian1469—
LMArena Spanish1471—

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Sonar: 71.4 (#150)

BenchmarkGLM-5.3-FlashSonar
LiveBench Instruction Following—76.2%
LMArena Instruction Following1478—

Long Context Not comparable

GLM-5.3-Flash: 45.4 (#39), Sonar: —

BenchmarkGLM-5.3-FlashSonar
LMArena Longer Query1482—

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Sonar: 52.6 (#167)

BenchmarkGLM-5.3-FlashSonar
LMArena Text1471—
LMArena Creative Writing1442—
LMArena Multi-Turn1467—
LiveBench Language—44.1%

Frequently asked questions

Is GLM-5.3-Flash better than Sonar?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 38.5 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or Sonar?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Sonar lists at $1 and $1.

Is GLM-5.3-Flash or Sonar better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 35.7 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 128K.

How many benchmarks do GLM-5.3-Flash and Sonar share?

0 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Sonar has 7.

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