Noometry

Model comparison

GLM-4.6V vs GPT-4.1 nano

GLM-4.6V is the stronger model overall, scoring 40.9 to 27.7 on the Noometry Index. GPT-4.1 nano costs 2.6× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

Last verified . 12 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

40.9

Rank #133 Confirmed

GPT-4.1 nano OpenAI

27.7

Rank #322 Confirmed

Summary

  • They share 12 benchmarks with published results for both. GLM-4.6V scores higher in 8 categories and GPT-4.1 nano in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.6V leads 26.5 to 8.6.
  • GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
  • GPT-4.1 nano accepts more context: 1.05M tokens versus 128K.
  • GLM-4.6V has downloadable open weights; the other is API-only.

Side by side

GLM-4.6VGPT-4.1 nano
ProviderZ.ai (Zhipu)OpenAI
Noometry Index40.927.7
Released2025-12-082025-04-14
WeightsOpenProprietary
Context window128K1.05M
Max output33K33K
Input $ / M tokens$0.30$0.10
Output $ / M tokens$0.90$0.40
Results tracked1238

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.2 (#128), GPT-4.1 nano: 23.8 (#325)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Coding13901306
Aider Polyglot—8.9%
SciCode—25.9%
WeirdML—19%

Agentic & Tool Use Not comparable

GLM-4.6V: —, GPT-4.1 nano: 26.3 (#98)

BenchmarkGLM-4.6VGPT-4.1 nano
Berkeley Function Calling Leaderboard—33%

Reasoning GLM-4.6V leads

GLM-4.6V: 26.5 (#117), GPT-4.1 nano: 8.6 (#344)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Hard Prompts13681286
ARC-AGI-2—0%
Kagi LLM Benchmark—33.3%
ARC-AGI-1—0%
CritPt—0%
DTBench—52.5%
LMCA—5.5%
Epoch Capabilities Index—129.62

Math Not comparable

GLM-4.6V: —, GPT-4.1 nano: 25.5 (#246)

BenchmarkGLM-4.6VGPT-4.1 nano
OTIS Mock AIME 2024-2025—28.9%
Omni-MATH—36.7%
LMArena Math—1274
MATH Level 5—70%
FrontierMath (Feb 2025 set)—1%

Knowledge GLM-4.6V leads

GLM-4.6V: 37.4 (#148), GPT-4.1 nano: 21.8 (#268)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Expert13721272
GPQA Diamond—48.9%
SimpleQA Verified—6%
MMLU-Pro—55%
GPQA (HELM)—50.7%

Multimodal GLM-4.6V leads

GLM-4.6V: 34.2 (#83), GPT-4.1 nano: 28.6 (#108)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Vision11641063

Multilingual GLM-4.6V leads

GLM-4.6V: 48.8 (#135), GPT-4.1 nano: 41.8 (#200)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Non-English13591260
LMArena Chinese14261270
LMArena Russian13411261
LMArena German—1288
LMArena Japanese—1199

Instruction Following GLM-4.6V leads

GLM-4.6V: 71.6 (#145), GPT-4.1 nano: 68.0 (#188)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Instruction Following13511267
IFEval—84.3%

Long Context GLM-4.6V leads

GLM-4.6V: 41.3 (#138), GPT-4.1 nano: 23.7 (#291)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Longer Query13581283
Fiction.LiveBench—25%

Writing & Preference GLM-4.6V leads

GLM-4.6V: 56.8 (#132), GPT-4.1 nano: 40.7 (#238)

BenchmarkGLM-4.6VGPT-4.1 nano
LMArena Text13771285
LMArena Creative Writing13471260
LMArena Multi-Turn13591277
EQ-Bench Creative Writing—946
WildBench—81.2%

Frequently asked questions

Is GLM-4.6V better than GPT-4.1 nano?

GLM-4.6V is the stronger model overall, scoring 40.9 to 27.7 on the Noometry Index. GPT-4.1 nano costs 2.6× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6V or GPT-4.1 nano?

GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

Is GLM-4.6V or GPT-4.1 nano better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 23.8 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 nano does, with 1.05M tokens against 128K.

How many benchmarks do GLM-4.6V and GPT-4.1 nano share?

12 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and GPT-4.1 nano has 38.

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