Noometry

Model comparison

GLM-4.5 vs gpt-oss-20b

GLM-4.5 is the stronger model overall, scoring 42.0 to 32.5 on the Noometry Index. gpt-oss-20b costs 28× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.

Last verified . 20 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

gpt-oss-20b OpenAI

32.5

Rank #255 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-4.5 scores higher in 7 categories and gpt-oss-20b in 1 category; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.5 leads 57.5 to 35.5.
  • gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.

Side by side

GLM-4.5gpt-oss-20b
ProviderZ.ai (Zhipu)OpenAI
Noometry Index42.032.5
Released2025-07-272025-08-05
WeightsOpenOpen
Context window131K131K
Max output98K16K
Input $ / M tokens$0.60$0.018
Output $ / M tokens$2.20$0.09
Results tracked2734

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Category by category

Coding GLM-4.5 leads

GLM-4.5: 41.4 (#125), gpt-oss-20b: 37.6 (#192)

BenchmarkGLM-4.5gpt-oss-20b
WeirdML40.6%40.9%
LMArena Coding14341306
ALE-Bench344.82566.05
SWE-bench Verified (bash only)54.2%—
SciCode—34.4%
AlgoTune1.52—

Agentic & Tool Use Not comparable

GLM-4.5: —, gpt-oss-20b: 9.3 (#154)

BenchmarkGLM-4.5gpt-oss-20b
Terminal-Bench—3.4%

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), gpt-oss-20b: 19.3 (#261)

BenchmarkGLM-4.5gpt-oss-20b
Kagi LLM Benchmark57.9%53.2%
LMArena Hard Prompts14291274
CritPt—1.4%
Chess Puzzles—4%
DTBench—68%
LMCA—14.5%
Epoch Capabilities Index—137.82

Math Too close to call

GLM-4.5: 39.0 (#116), gpt-oss-20b: 39.4 (#103)

BenchmarkGLM-4.5gpt-oss-20b
LMArena Math14271317
OTIS Mock AIME 2024-2025—65.3%
Omni-MATH—56.5%

Knowledge GLM-4.5 leads

GLM-4.5: 35.9 (#179), gpt-oss-20b: 34.6 (#195)

BenchmarkGLM-4.5gpt-oss-20b
LMArena Expert14331258
GPQA Diamond—60.8%
Humanity's Last Exam8.3%—
MMLU-Pro—74%
Confabulations11.3%—
GPQA (HELM)—59.4%

Multilingual GLM-4.5 leads

GLM-4.5: 52.8 (#77), gpt-oss-20b: 42.2 (#197)

BenchmarkGLM-4.5gpt-oss-20b
LMArena Non-English14171268
LMArena Chinese14651314
LMArena German14071255
LMArena Japanese14151244
LMArena Korean13801236
LMArena Russian14141278
LMArena Spanish14541267
LMArena French1418—

Instruction Following GLM-4.5 leads

GLM-4.5: 74.1 (#104), gpt-oss-20b: 61.8 (#240)

BenchmarkGLM-4.5gpt-oss-20b
LMArena Instruction Following14041236
IFEval—73.2%

Long Context Too close to call

GLM-4.5: 38.2 (#201), gpt-oss-20b: 37.9 (#209)

BenchmarkGLM-4.5gpt-oss-20b
LMArena Longer Query14121250
Fiction.LiveBench58.3%—

Writing & Preference GLM-4.5 leads

GLM-4.5: 57.5 (#127), gpt-oss-20b: 35.5 (#265)

BenchmarkGLM-4.5gpt-oss-20b
LMArena Text14301287
LMArena Creative Writing13951201
EQ-Bench Creative Writing1343666
LMArena Multi-Turn14151268
Short-Story Creative Writing73.4%—
WildBench—73.7%

Frequently asked questions

Is GLM-4.5 better than gpt-oss-20b?

GLM-4.5 is the stronger model overall, scoring 42.0 to 32.5 on the Noometry Index. gpt-oss-20b costs 28× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5 or gpt-oss-20b?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

Is GLM-4.5 or gpt-oss-20b better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 37.6 in the Noometry coding category.

Which has the bigger context window?

Both accept 131K tokens.

How many benchmarks do GLM-4.5 and gpt-oss-20b share?

20 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and gpt-oss-20b has 34.

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