Noometry

Model comparison

GLM-4.5V vs gpt-oss-20b

GLM-4.5V is the stronger model overall, scoring 39.8 to 32.5 on the Noometry Index. gpt-oss-20b costs 25× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Last verified . 14 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

gpt-oss-20b OpenAI

32.5

Rank #255 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 7 categories and gpt-oss-20b in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.5V leads 52.5 to 35.5.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 53.2% for gpt-oss-20b.
  • gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • gpt-oss-20b accepts more context: 131K tokens versus 64K.

Side by side

GLM-4.5Vgpt-oss-20b
ProviderZ.ai (Zhipu)OpenAI
Noometry Index39.832.5
Released2025-08-112025-08-05
WeightsOpenOpen
Context window64K131K
Max output16K16K
Input $ / M tokens$0.60$0.018
Output $ / M tokens$1.80$0.09
Results tracked1534

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), gpt-oss-20b: 37.6 (#192)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Coding13471306
SciCode—34.4%
WeirdML—40.9%
ALE-Bench—566.05

Agentic & Tool Use Not comparable

GLM-4.5V: —, gpt-oss-20b: 9.3 (#154)

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

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), gpt-oss-20b: 19.3 (#261)

BenchmarkGLM-4.5Vgpt-oss-20b
Kagi LLM Benchmark59.8%53.2%
LMArena Hard Prompts13341274
CritPt—1.4%
Chess Puzzles—4%
DTBench—68%
LMCA—14.5%
Epoch Capabilities Index—137.82

Math gpt-oss-20b leads

GLM-4.5V: 37.4 (#159), gpt-oss-20b: 39.4 (#103)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Math13541317
OTIS Mock AIME 2024-2025—65.3%
Omni-MATH—56.5%

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), gpt-oss-20b: 34.6 (#195)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Expert13531258
GPQA Diamond—60.8%
MMLU-Pro—74%
GPQA (HELM)—59.4%

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), gpt-oss-20b: —

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Vision1154—

Multilingual GLM-4.5V leads

GLM-4.5V: 44.6 (#177), gpt-oss-20b: 42.2 (#197)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Non-English13031268
LMArena Chinese13371314
LMArena Russian12981278
LMArena Spanish13361267
LMArena German—1255
LMArena Japanese—1244
LMArena Korean—1236

Instruction Following GLM-4.5V leads

GLM-4.5V: 69.2 (#175), gpt-oss-20b: 61.8 (#240)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Instruction Following13111236
IFEval—73.2%

Long Context GLM-4.5V leads

GLM-4.5V: 39.6 (#171), gpt-oss-20b: 37.9 (#209)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Longer Query13041250

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.5 (#170), gpt-oss-20b: 35.5 (#265)

BenchmarkGLM-4.5Vgpt-oss-20b
LMArena Text13331287
LMArena Creative Writing12951201
LMArena Multi-Turn13321268
EQ-Bench Creative Writing—666
WildBench—73.7%

Frequently asked questions

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

GLM-4.5V is the stronger model overall, scoring 39.8 to 32.5 on the Noometry Index. gpt-oss-20b costs 25× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5V 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-4.5V lists at $0.60 and $1.80.

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

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 37.6 in the Noometry coding category.

Which has the bigger context window?

gpt-oss-20b does, with 131K tokens against 64K.

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

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and gpt-oss-20b has 34.

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