Noometry

Model comparison

DeepSeek-V3.1 vs GLM-4.5

DeepSeek-V3.1 and GLM-4.5 score almost the same on the Noometry Index (42.8 vs 42.0), so choose on price, context window or the category you care about most.

Last verified . 21 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.8

Rank #108 Confirmed

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

Summary

  • They share 21 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 2 categories and GLM-4.5 in 6 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.7 to 35.9.
  • The biggest single-benchmark swing is Fiction.LiveBench: 52.8% for DeepSeek-V3.1 and 58.3% for GLM-4.5.
  • DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
  • DeepSeek-V3.1 accepts more context: 164K tokens versus 131K.

Side by side

DeepSeek-V3.1GLM-4.5
ProviderDeepSeekZ.ai (Zhipu)
Noometry Index42.842.0
Released2025-08-212025-07-27
WeightsOpenOpen
Context window164K131K
Max output8K98K
Input $ / M tokens$0.25$0.60
Output $ / M tokens$0.95$2.20
Results tracked2727

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GLM-4.5 leads

DeepSeek-V3.1: 40.3 (#144), GLM-4.5: 41.4 (#125)

BenchmarkDeepSeek-V3.1GLM-4.5
WeirdML38.4%40.6%
LMArena Coding14171434
SWE-bench Verified (bash only)—54.2%
ALE-Bench—344.82
AlgoTune—1.52

Reasoning Too close to call

DeepSeek-V3.1: 27.9 (#110), GLM-4.5: 28.6 (#100)

BenchmarkDeepSeek-V3.1GLM-4.5
Kagi LLM Benchmark53.2%57.9%
LMArena Hard Prompts14171429
SimpleBench40%—
DTBench82.7%—
LMCA24.3%—
Epoch Capabilities Index139.92—
ForecastBench58—

Math Too close to call

DeepSeek-V3.1: 38.9 (#122), GLM-4.5: 39.0 (#116)

BenchmarkDeepSeek-V3.1GLM-4.5
LMArena Math14201427

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.7 (#90), GLM-4.5: 35.9 (#179)

BenchmarkDeepSeek-V3.1GLM-4.5
LMArena Expert14051433
Humanity's Last Exam—8.3%
Confabulations—11.3%
Vectara Hallucination Rate5.5%—

Multilingual GLM-4.5 leads

DeepSeek-V3.1: 51.6 (#106), GLM-4.5: 52.8 (#77)

BenchmarkDeepSeek-V3.1GLM-4.5
LMArena Non-English14001417
LMArena Chinese14691465
LMArena French14471418
LMArena German14111407
LMArena Japanese13781415
LMArena Korean13371380
LMArena Russian14051414
LMArena Spanish14311454

Instruction Following Too close to call

DeepSeek-V3.1: 73.9 (#110), GLM-4.5: 74.1 (#104)

BenchmarkDeepSeek-V3.1GLM-4.5
LMArena Instruction Following14001404

Long Context GLM-4.5 leads

DeepSeek-V3.1: 36.3 (#232), GLM-4.5: 38.2 (#201)

BenchmarkDeepSeek-V3.1GLM-4.5
Fiction.LiveBench52.8%58.3%
LMArena Longer Query14221412

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.3 (#98), GLM-4.5: 57.5 (#127)

BenchmarkDeepSeek-V3.1GLM-4.5
LMArena Text14201430
LMArena Creative Writing14011395
EQ-Bench Creative Writing14361343
LMArena Multi-Turn14081415
Short-Story Creative Writing—73.4%

Frequently asked questions

Is DeepSeek-V3.1 better than GLM-4.5?

DeepSeek-V3.1 and GLM-4.5 score almost the same on the Noometry Index (42.8 vs 42.0), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.1 or GLM-4.5?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

Is DeepSeek-V3.1 or GLM-4.5 better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 40.3 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 131K.

How many benchmarks do DeepSeek-V3.1 and GLM-4.5 share?

21 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GLM-4.5 has 27.

Related comparisons

Go deeper