Model comparison

DBRX vs GLM-5

GLM-5 is the stronger model overall, scoring 45.9 to 29.0 on the Noometry Index.

Last verified . 18 shared benchmarks.

DBRX Databricks

29.0

Rank #307 Confirmed

GLM-5 Z.ai (Zhipu)

45.9

Rank #59 Confirmed

Summary

  • They share 18 benchmarks with published results for both. DBRX scores higher in 0 categories and GLM-5 in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5 leads 52.2 to 14.9.
  • The biggest single-benchmark swing is GPQA Diamond: 32.9% for DBRX and 87.8% for GLM-5.

Side by side

DBRX and GLM-5 specifications
DBRXGLM-5
ProviderDatabricksZ.ai (Zhipu)
Noometry Index29.045.9
Released2024-03-272026-02-11
WeightsOpenOpen
Context window—205K
Max output—131K
Input $ / M tokens—$1
Output $ / M tokens—$3.20
Results tracked2145

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Category by category

Coding GLM-5 leads

DBRX: 32.3 (#262), GLM-5: 49.0 (#47)

Coding benchmarks
BenchmarkDBRXGLM-5
LMArena Coding11321461
SWE-bench Verified—72.1%
SWE-bench Verified (bash only)—72.8%
LMArena WebDev—1434
SWE-bench Multilingual—69.7%
WeirdML—48.2%
ALE-Bench—765.62
HumanEval+70.1%—
MBPP+55.8%—

Agentic & Tool Use Not comparable

DBRX: —, GLM-5: 30.9 (#65)

Agentic & Tool Use benchmarks
BenchmarkDBRXGLM-5
Terminal-Bench—52.4%
τ²-bench Airline—82.5%
τ²-bench Banking—9.8%
τ²-bench Retail—73.7%
τ²-bench Telecom—86.8%
Vending-Bench 2—4,432

Reasoning GLM-5 leads

DBRX: 20.5 (#218), GLM-5: 27.6 (#100)

Reasoning benchmarks
BenchmarkDBRXGLM-5
LMArena Hard Prompts11131451
ARC-AGI-2—4.9%
SimpleBench—53.2%
Kagi LLM Benchmark—75%
NYT Connections (extended)—74.8%
ARC-AGI-1—44.7%
Chess Puzzles—10%
Epoch Capabilities Index—145.84
ForecastBench—61

Math GLM-5 leads

DBRX: 22.3 (#265), GLM-5: 44.8 (#66)

Knowledge GLM-5 leads

DBRX: 14.9 (#289), GLM-5: 52.2 (#59)

Knowledge benchmarks
BenchmarkDBRXGLM-5
GPQA Diamond32.9%87.8%
LMArena Expert10761454
Vectara Hallucination Rate—10.1%

Multilingual GLM-5 leads

DBRX: 29.4 (#263), GLM-5: 53.9 (#57)

Multilingual benchmarks
BenchmarkDBRXGLM-5
LMArena Non-English10711430
LMArena Chinese10681511
LMArena French10951455
LMArena German10571445
LMArena Japanese9901416
LMArena Korean9931421
LMArena Russian10781436
LMArena Spanish10641452

Instruction Following GLM-5 leads

DBRX: 57.7 (#265), GLM-5: 75.4 (#64)

Instruction Following benchmarks
BenchmarkDBRXGLM-5
LMArena Instruction Following11121427

Long Context GLM-5 leads

DBRX: 33.7 (#253), GLM-5: 44.6 (#58)

Long Context benchmarks
BenchmarkDBRXGLM-5
LMArena Longer Query11121446
CL-bench—18.7%

Writing & Preference GLM-5 leads

DBRX: 33.7 (#271), GLM-5: 66.2 (#38)

Writing & Preference benchmarks
BenchmarkDBRXGLM-5
LMArena Text11191446
LMArena Creative Writing11041438
LMArena Multi-Turn11111456
EQ-Bench Creative Writing—1601

Frequently asked questions

Is DBRX better than GLM-5?

GLM-5 is the stronger model overall, scoring 45.9 to 29.0 on the Noometry Index.

Is DBRX or GLM-5 better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 32.3 in the Noometry coding category.

How many benchmarks do DBRX and GLM-5 share?

18 benchmarks have published results for both models. DBRX has 21 scored results on Noometry and GLM-5 has 45.

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