Noometry

Model comparison

GLM-5.3-Flash vs Phi-4

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 31.2 on the Noometry Index. Phi-4 costs 2.7× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.

Last verified . 21 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Phi-4 Microsoft

31.2

Rank #279 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and Phi-4 in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3-Flash leads 53.3 to 20.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 13.8% for Phi-4.
  • Phi-4 is cheaper at $0.07 / $0.14 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 128K.

Side by side

GLM-5.3-FlashPhi-4
ProviderZ.ai (Zhipu)Microsoft
Noometry Index51.831.2
Released2026-08-202024-12-11
WeightsOpenOpen
Context window1M128K
Max output131K4K
Input $ / M tokens$0.15$0.07
Output $ / M tokens$0.50$0.14
Results tracked4037

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Phi-4: 34.4 (#239)

BenchmarkGLM-5.3-FlashPhi-4
LMArena Coding15081231
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
BigCodeBench Instruct—45.5%
LiveBench Coding—30.7%
BigCodeBench Complete—55.4%
ALE-Bench303.55—

Agentic & Tool Use GLM-5.3-Flash leads

GLM-5.3-Flash: 34.2 (#47), Phi-4: 22.8 (#128)

BenchmarkGLM-5.3-FlashPhi-4
APEX-Agents52.8%—
Berkeley Function Calling Leaderboard—28.8%
BALROG—11.6%
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Phi-4: 17.7 (#291)

BenchmarkGLM-5.3-FlashPhi-4
Chess Puzzles14%1%
LMArena Hard Prompts14911220
Epoch Capabilities Index151.88130.42
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
LiveBench Reasoning—47.8%
Mystery Game Puzzles8%—
LiveBench Data Analysis—45.2%
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
LiveBench—41.6%

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), Phi-4: 20.8 (#285)

BenchmarkGLM-5.3-FlashPhi-4
OTIS Mock AIME 2024-202593.9%13.8%
LMArena Math15001246
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
ProofBench21%—
LiveBench Math—42%
MATH Level 5—64.9%

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), Phi-4: 32.6 (#209)

BenchmarkGLM-5.3-FlashPhi-4
GPQA Diamond90.2%56.1%
LMArena Expert15131203
Confabulations—29.4%
Vectara Hallucination Rate—3.7%
MMLU—84.8%

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), Phi-4: —

BenchmarkGLM-5.3-FlashPhi-4
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Phi-4: 37.2 (#237)

BenchmarkGLM-5.3-FlashPhi-4
LMArena Non-English14621197
LMArena Chinese15271212
LMArena French14961224
LMArena German14701222
LMArena Japanese14291158
LMArena Korean14461151
LMArena Russian14691209
LMArena Spanish14711234

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Phi-4: 60.4 (#251)

BenchmarkGLM-5.3-FlashPhi-4
LMArena Instruction Following14781201
LiveBench Instruction Following—58.4%

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Phi-4: 36.9 (#226)

BenchmarkGLM-5.3-FlashPhi-4
LMArena Longer Query14821217

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Phi-4: 40.5 (#244)

BenchmarkGLM-5.3-FlashPhi-4
LMArena Text14711217
LMArena Creative Writing14421182
LMArena Multi-Turn14671206
Short-Story Creative Writing—62.6%
LiveBench Language—25.6%

Frequently asked questions

Is GLM-5.3-Flash better than Phi-4?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 31.2 on the Noometry Index. Phi-4 costs 2.7× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.

Which is cheaper, GLM-5.3-Flash or Phi-4?

Phi-4 is cheaper. It lists at $0.07 per million input tokens and $0.14 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.

Is GLM-5.3-Flash or Phi-4 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 34.4 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 Phi-4 share?

21 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Phi-4 has 37.

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