Noometry

Model comparison

Command R+ vs GLM-4.6

GLM-4.6 is the stronger model overall, scoring 41.4 to 32.4 on the Noometry Index.

Last verified . 18 shared benchmarks.

Command R+ Cohere

32.4

Rank #257 Confirmed

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Summary

  • They share 18 benchmarks with published results for both. Command R+ scores higher in 0 categories and GLM-4.6 in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 43.5.
  • GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2.50 / $10 for Command R+.
  • GLM-4.6 accepts more context: 205K tokens versus 128K.

Side by side

Command R+GLM-4.6
ProviderCohereZ.ai (Zhipu)
Noometry Index32.441.4
Released2024-08-302025-09-30
WeightsOpenOpen
Context window128K205K
Max output4K131K
Input $ / M tokens$2.50$0.60
Output $ / M tokens$10$2.20
Results tracked3429

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Category by category

Coding GLM-4.6 leads

Command R+: 29.1 (#309), GLM-4.6: 40.1 (#148)

BenchmarkCommand R+GLM-4.6
LMArena Coding11871449
SWE-bench Verified (bash only)—55.4%
LMArena WebDev—1340
SciCode—38.4%
BigCodeBench Instruct33.8%—
LiveBench Coding19.1%—
BigCodeBench Complete41.9%—
ALE-Bench—340.82
HumanEval+56.7%—
MBPP+63.5%—

Agentic & Tool Use Not comparable

Command R+: —, GLM-4.6: 32.3 (#66)

BenchmarkCommand R+GLM-4.6
Terminal-Bench—24.5%
Berkeley Function Calling Leaderboard—72.4%

Reasoning GLM-4.6 leads

Command R+: 9.2 (#344), GLM-4.6: 23.7 (#172)

BenchmarkCommand R+GLM-4.6
LMArena Hard Prompts11861440
SimpleBench17.4%—
Kagi LLM Benchmark—47.4%
CritPt—1.1%
LiveBench Reasoning24.8%—
DTBench54.9%—
LiveBench Data Analysis38.1%—
LMCA5%—
Epoch Capabilities Index119.34—
LiveBench31.8%—

Math GLM-4.6 leads

Command R+: 28.9 (#242), GLM-4.6: 39.1 (#111)

BenchmarkCommand R+GLM-4.6
LMArena Math11881432
LiveBench Math21.3%—
FrontierMath (Feb 2025 set)—3.8%
FrontierMath Tier 4 (v1)—2.1%

Knowledge GLM-4.6 leads

Command R+: 36.4 (#169), GLM-4.6: 40.2 (#124)

BenchmarkCommand R+GLM-4.6
Vectara Hallucination Rate6.9%9.5%
LMArena Expert11741431
MMLU69.4%—

Multilingual GLM-4.6 leads

Command R+: 38.6 (#227), GLM-4.6: 53.5 (#66)

BenchmarkCommand R+GLM-4.6
LMArena Non-English12161426
LMArena Chinese12261499
LMArena French12091459
LMArena German12161447
LMArena Japanese11661393
LMArena Korean11381400
LMArena Russian12271419
LMArena Spanish11891436

Instruction Following GLM-4.6 leads

Command R+: 60.0 (#254), GLM-4.6: 74.3 (#98)

BenchmarkCommand R+GLM-4.6
LMArena Instruction Following11971410
LiveBench Instruction Following57.6%—

Long Context GLM-4.6 leads

Command R+: 37.3 (#219), GLM-4.6: 43.4 (#94)

BenchmarkCommand R+GLM-4.6
LMArena Longer Query12301422

Writing & Preference GLM-4.6 leads

Command R+: 43.5 (#228), GLM-4.6: 61.1 (#90)

BenchmarkCommand R+GLM-4.6
LMArena Text12291440
LMArena Creative Writing12351411
LMArena Multi-Turn12131427
EQ-Bench Creative Writing—1411
LiveBench Language29.7%—

Frequently asked questions

Is Command R+ better than GLM-4.6?

GLM-4.6 is the stronger model overall, scoring 41.4 to 32.4 on the Noometry Index.

Which is cheaper, Command R+ or GLM-4.6?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Command R+ lists at $2.50 and $10.

Is Command R+ or GLM-4.6 better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 29.1 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 128K.

How many benchmarks do Command R+ and GLM-4.6 share?

18 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and GLM-4.6 has 29.

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