Noometry

Model comparison

Command R vs GLM-5.3

GLM-5.3 is the stronger model overall, scoring 54.8 to 31.4 on the Noometry Index. Command R costs 8.2× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Last verified . 19 shared benchmarks.

Command R Cohere

31.4

Rank #272 Confirmed

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Summary

  • They share 19 benchmarks with published results for both. Command R scores higher in 0 categories and GLM-5.3 in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.3 leads 75.7 to 38.2.
  • The biggest single-benchmark swing is LMCA: 9.2% for Command R and 55.5% for GLM-5.3.
  • Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
  • GLM-5.3 accepts more context: 1M tokens versus 128K.

Side by side

Command RGLM-5.3
ProviderCohereZ.ai (Zhipu)
Noometry Index31.454.8
Released2024-08-302026-08-14
WeightsOpenOpen
Context window128K1M
Max output4K131K
Input $ / M tokens$0.15$1.40
Output $ / M tokens$0.60$4.40
Results tracked2942

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Category by category

Coding GLM-5.3 leads

Command R: 29.3 (#306), GLM-5.3: 59.5 (#14)

BenchmarkCommand RGLM-5.3
LMArena Coding11691496
DeepSWE—69%
FrontierCode—40.1%
CursorBench—42.6%
LMArena WebDev—1622
FrontierSWE—30.2%
SciCode—59%
WeirdML—75.4%
BigCodeBench Instruct37.1%—
LiveBench Coding17.9%—
BigCodeBench Complete45.2%—
ALE-Bench—1,317

Agentic & Tool Use Not comparable

Command R: —, GLM-5.3: 36.4 (#38)

BenchmarkCommand RGLM-5.3
APEX-Agents—56.6%
Vending-Bench 2—8,164

Reasoning GLM-5.3 leads

Command R: 13.8 (#331), GLM-5.3: 46.1 (#46)

BenchmarkCommand RGLM-5.3
LMArena Hard Prompts11641489
DTBench46.4%87.7%
LMCA9.2%55.5%
NYT Connections (extended)—74.2%
CritPt—19.1%
Chess Puzzles—21%
LiveBench Reasoning21.9%—
Mystery Game Puzzles—33%
LiveBench Data Analysis33.3%—
Bench to the Future 3—0.15
Epoch Capabilities Index—155.61
LiveBench27.5%—

Math GLM-5.3 leads

Command R: 28.0 (#246), GLM-5.3: 62.3 (#33)

BenchmarkCommand RGLM-5.3
LMArena Math11551489
FrontierMath (Tiers 1-3)—68.8%
FrontierMath Tier 4—29.3%
OTIS Mock AIME 2024-2025—91.1%
ProofBench—49%
LiveBench Math19.4%—

Knowledge GLM-5.3 leads

Command R: 31.0 (#221), GLM-5.3: 58.3 (#37)

BenchmarkCommand RGLM-5.3
LMArena Expert11381516
GPQA Diamond—90.9%
SimpleQA Verified—41%
MMLU65.2%—

Multilingual GLM-5.3 leads

Command R: 35.7 (#245), GLM-5.3: 55.7 (#28)

BenchmarkCommand RGLM-5.3
LMArena Non-English11741457
LMArena Chinese11821528
LMArena French11621499
LMArena German11761499
LMArena Japanese11431453
LMArena Korean11631472
LMArena Russian11741463
LMArena Spanish11511460

Instruction Following GLM-5.3 leads

Command R: 58.1 (#261), GLM-5.3: 77.5 (#23)

BenchmarkCommand RGLM-5.3
LMArena Instruction Following11671477
LiveBench Instruction Following55.6%—

Long Context GLM-5.3 leads

Command R: 36.3 (#231), GLM-5.3: 45.4 (#41)

BenchmarkCommand RGLM-5.3
LMArena Longer Query11981482

Writing & Preference GLM-5.3 leads

Command R: 38.2 (#254), GLM-5.3: 75.7 (#6)

BenchmarkCommand RGLM-5.3
LMArena Text11871471
LMArena Creative Writing11701457
LMArena Multi-Turn11631472
EQ-Bench Creative Writing—2075
LiveBench Language16.7%—

Frequently asked questions

Is Command R better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.8 to 31.4 on the Noometry Index. Command R costs 8.2× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Which is cheaper, Command R or GLM-5.3?

Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

Is Command R or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 29.3 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 128K.

How many benchmarks do Command R and GLM-5.3 share?

19 benchmarks have published results for both models. Command R has 29 scored results on Noometry and GLM-5.3 has 42.

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