Noometry

Model comparison

DeepSeek-V3.1-Terminus vs GLM-5V-Turbo

DeepSeek-V3.1-Terminus and GLM-5V-Turbo score almost the same on the Noometry Index (43.1 vs 43.8), so choose on price, context window or the category you care about most.

Last verified . 10 shared benchmarks.

DeepSeek-V3.1-Terminus DeepSeek

43.1

Rank #97 Confirmed

GLM-5V-Turbo Z.ai (Zhipu)

43.8

Rank #84 Confirmed

Summary

  • They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 0 categories and GLM-5V-Turbo in 7 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5V-Turbo leads 29.7 to 26.4.
  • DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
  • GLM-5V-Turbo accepts more context: 200K tokens versus 164K.
  • DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1-TerminusGLM-5V-Turbo
ProviderDeepSeekZ.ai (Zhipu)
Noometry Index43.143.8
Released2025-09-222026-04-01
WeightsOpenProprietary
Context window164K200K
Max output147K131K
Input $ / M tokens$0.27$1.20
Output $ / M tokens$1$4
Results tracked1619

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Category by category

Coding Too close to call

DeepSeek-V3.1-Terminus: 42.0 (#113), GLM-5V-Turbo: 42.1 (#111)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Coding14261466
LMArena WebDev—1401
SciCode40.6%—
ALE-Bench745.17—

Reasoning GLM-5V-Turbo leads

DeepSeek-V3.1-Terminus: 26.4 (#133), GLM-5V-Turbo: 29.7 (#89)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Hard Prompts14261443
Kagi LLM Benchmark57.4%—
CritPt1.7%—
DTBench81.3%—
LMCA28.6%—

Math Too close to call

DeepSeek-V3.1-Terminus: 38.5 (#137), GLM-5V-Turbo: 39.4 (#106)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Math14021441

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, GLM-5V-Turbo: 40.6 (#117)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Expert—1452

Multimodal Not comparable

DeepSeek-V3.1-Terminus: —, GLM-5V-Turbo: 40.9 (#42)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Vision—1264
LMArena Document—1416

Multilingual Too close to call

DeepSeek-V3.1-Terminus: 52.1 (#92), GLM-5V-Turbo: 53.0 (#73)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Non-English14071420
LMArena Russian14361431
LMArena Chinese—1488
LMArena French—1444
LMArena German—1423
LMArena Korean—1396
LMArena Spanish—1450

Instruction Following Too close to call

DeepSeek-V3.1-Terminus: 74.0 (#106), GLM-5V-Turbo: 75.0 (#80)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Instruction Following14041423

Long Context Too close to call

DeepSeek-V3.1-Terminus: 43.4 (#97), GLM-5V-Turbo: 44.0 (#80)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Longer Query14211438

Writing & Preference GLM-5V-Turbo leads

DeepSeek-V3.1-Terminus: 61.0 (#92), GLM-5V-Turbo: 62.5 (#73)

BenchmarkDeepSeek-V3.1-TerminusGLM-5V-Turbo
LMArena Text14191437
LMArena Creative Writing14031416
LMArena Multi-Turn14111432

Frequently asked questions

Is DeepSeek-V3.1-Terminus better than GLM-5V-Turbo?

DeepSeek-V3.1-Terminus and GLM-5V-Turbo score almost the same on the Noometry Index (43.1 vs 43.8), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.1-Terminus or GLM-5V-Turbo?

DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.

Is DeepSeek-V3.1-Terminus or GLM-5V-Turbo better for coding?

They score almost the same on coding (42.0 vs 42.1); test both on your own repository before choosing.

Which has the bigger context window?

GLM-5V-Turbo does, with 200K tokens against 164K.

How many benchmarks do DeepSeek-V3.1-Terminus and GLM-5V-Turbo share?

10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and GLM-5V-Turbo has 19.

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