Model comparison

Command R7B vs GLM-5.3

GLM-5.3 has enough public results to be ranked (#25); Command R7B does not yet, so treat this comparison as directional.

Last verified . 0 shared benchmarks.

Command R7B Cohere

32.1

Unranked Sparse

GLM-5.3 Z.ai (Zhipu)

54.6

Rank #25 Confirmed

Summary

  • The widest gap is in agentic & tool use, where GLM-5.3 leads 36.3 to 25.9.
  • Command R7B is cheaper at $0.0375 / $0.15 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 R7B and GLM-5.3 specifications
Command R7BGLM-5.3
ProviderCohereZ.ai (Zhipu)
Noometry Index32.154.6
Released2024-12-022026-08-14
WeightsOpenOpen
Context window128K1M
Max output4K131K
Input $ / M tokens$0.0375$1.40
Output $ / M tokens$0.15$4.40
Results tracked141

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Category by category

Coding Not comparable

Command R7B: —, GLM-5.3: 59.0 (#12)

Coding benchmarks
BenchmarkCommand R7BGLM-5.3
DeepSWE—69%
FrontierCode—40.1%
LMArena WebDev—1623
FrontierSWE—30.2%
SciCode—59%
WeirdML—75.4%
LMArena Coding—1499
ALE-Bench—1,317

Agentic & Tool Use GLM-5.3 leads

Command R7B: 25.9, GLM-5.3: 36.3 (#34)

Agentic & Tool Use benchmarks
BenchmarkCommand R7BGLM-5.3
APEX-Agents—56.6%
Berkeley Function Calling Leaderboard32.1%—
Vending-Bench 2—8,164

Reasoning Not comparable

Command R7B: —, GLM-5.3: 45.2 (#42)

Reasoning benchmarks
BenchmarkCommand R7BGLM-5.3
NYT Connections (extended)—74.2%
CritPt—19.1%
Chess Puzzles—21%
LMArena Hard Prompts—1491
Mystery Game Puzzles—33%
DTBench—87.7%
LMCA—55.5%
Bench to the Future 3—0.15
Epoch Capabilities Index—155.56

Math Not comparable

Command R7B: —, GLM-5.3: 62.1 (#27)

Math benchmarks
BenchmarkCommand R7BGLM-5.3
FrontierMath (Tiers 1-3)—68.8%
FrontierMath Tier 4—29.3%
OTIS Mock AIME 2024-2025—91.1%
ProofBench—49%
LMArena Math—1493

Knowledge Not comparable

Command R7B: —, GLM-5.3: 58.3 (#34)

Knowledge benchmarks
BenchmarkCommand R7BGLM-5.3
GPQA Diamond—90.9%
SimpleQA Verified—41%
LMArena Expert—1512

Multilingual Not comparable

Command R7B: —, GLM-5.3: 55.9 (#27)

Multilingual benchmarks
BenchmarkCommand R7BGLM-5.3
LMArena Non-English—1457
LMArena Chinese—1523
LMArena French—1499
LMArena German—1505
LMArena Japanese—1438
LMArena Korean—1478
LMArena Russian—1460
LMArena Spanish—1444

Instruction Following Not comparable

Command R7B: —, GLM-5.3: 77.8 (#15)

Instruction Following benchmarks
BenchmarkCommand R7BGLM-5.3
LMArena Instruction Following—1481

Long Context Not comparable

Command R7B: —, GLM-5.3: 45.5 (#32)

Long Context benchmarks
BenchmarkCommand R7BGLM-5.3
LMArena Longer Query—1485

Writing & Preference Not comparable

Command R7B: —, GLM-5.3: 75.9 (#6)

Writing & Preference benchmarks
BenchmarkCommand R7BGLM-5.3
LMArena Text—1473
LMArena Creative Writing—1459
EQ-Bench Creative Writing—2075
LMArena Multi-Turn—1473

Frequently asked questions

Is Command R7B better than GLM-5.3?

GLM-5.3 has enough public results to be ranked (#25); Command R7B does not yet, so treat this comparison as directional.

Which is cheaper, Command R7B or GLM-5.3?

Command R7B is cheaper. It lists at $0.0375 per million input tokens and $0.15 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

Which has the bigger context window?

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

How many benchmarks do Command R7B and GLM-5.3 share?

0 benchmarks have published results for both models. Command R7B has 1 scored results on Noometry and GLM-5.3 has 41.

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