Noometry

Model comparison

Codellama 70b Instruct vs GLM-5.2

GLM-5.2 is the stronger model overall, scoring 51.1 to 33.7 on the Noometry Index.

Last verified . 4 shared benchmarks.

Codellama 70b Instruct Meta

33.7

Rank #237 Confirmed

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Summary

  • They share 4 benchmarks with published results for both. Codellama 70b Instruct scores higher in 0 categories and GLM-5.2 in 5 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.2 leads 70.4 to 33.4.

Side by side

Codellama 70b InstructGLM-5.2
ProviderMetaZ.ai (Zhipu)
Noometry Index33.751.1
Released—2026-06-13
WeightsOpenOpen
Context window—1M
Max output—131K
Input $ / M tokens—$1.40
Output $ / M tokens—$4.40
Results tracked751

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Category by category

Coding GLM-5.2 leads

Codellama 70b Instruct: 37.6 (#193), GLM-5.2: 51.3 (#41)

BenchmarkCodellama 70b InstructGLM-5.2
SWE-bench Verified—78.7%
DeepSWE—43.8%
FrontierCode—24.5%
LMArena WebDev—1603
SciCode—50.5%
WeirdML—70.1%
BigCodeBench Instruct40.7%—
LMArena Coding—1485
BigCodeBench Complete49.6%—
ALE-Bench—1,047
HumanEval+65.9%—

Agentic & Tool Use Not comparable

Codellama 70b Instruct: —, GLM-5.2: 32.4 (#63)

BenchmarkCodellama 70b InstructGLM-5.2
APEX-Agents—45.2%
τ²-bench Banking—37.1%
PostTrainBench—31.7%
GBAEval—0%
Vending-Bench 2—8,314

Reasoning GLM-5.2 leads

Codellama 70b Instruct: 20.1 (#242), GLM-5.2: 42.3 (#52)

BenchmarkCodellama 70b InstructGLM-5.2
LMArena Hard Prompts10521480
ARC-AGI-2—22.8%
SimpleBench—58.8%
Kagi LLM Benchmark—62.6%
NYT Connections (extended)—74.3%
ARC-AGI-1—77%
CritPt—20.9%
Chess Puzzles—21%
EBR-Bench—9.5%
Mystery Game Puzzles—19%
DTBench—93.6%
LMCA—45.8%
Surface Evolver Bench—55.6%
Epoch Capabilities Index—151.78

Math Not comparable

Codellama 70b Instruct: —, GLM-5.2: 55.7 (#43)

BenchmarkCodellama 70b InstructGLM-5.2
FrontierMath (Tiers 1-3)—59.2%
FrontierMath Tier 4—29.3%
MathArena Final-Answer Competitions—67.6%
OTIS Mock AIME 2024-2025—86.4%
ProofBench—35%
LMArena Math—1482

Knowledge Not comparable

Codellama 70b Instruct: —, GLM-5.2: 57.1 (#40)

BenchmarkCodellama 70b InstructGLM-5.2
GPQA Diamond—91.9%
SimpleQA Verified—34.2%
LMArena Expert—1486

Multilingual GLM-5.2 leads

Codellama 70b Instruct: 24.8 (#288), GLM-5.2: 55.8 (#26)

BenchmarkCodellama 70b InstructGLM-5.2
LMArena Non-English9921459
LMArena Chinese—1519
LMArena French—1479
LMArena German—1468
LMArena Japanese—1451
LMArena Korean—1445
LMArena Russian—1466
LMArena Spanish—1477

Instruction Following GLM-5.2 leads

Codellama 70b Instruct: 51.9 (#293), GLM-5.2: 76.9 (#34)

BenchmarkCodellama 70b InstructGLM-5.2
LMArena Instruction Following10241465

Long Context Not comparable

Codellama 70b Instruct: —, GLM-5.2: 45.3 (#43)

BenchmarkCodellama 70b InstructGLM-5.2
LMArena Longer Query—1479

Writing & Preference GLM-5.2 leads

Codellama 70b Instruct: 33.4 (#277), GLM-5.2: 70.4 (#21)

BenchmarkCodellama 70b InstructGLM-5.2
LMArena Text10571470
LMArena Creative Writing—1462
EQ-Bench Creative Writing—1757
EQ-Bench 4—1222
LMArena Multi-Turn—1469

Frequently asked questions

Is Codellama 70b Instruct better than GLM-5.2?

GLM-5.2 is the stronger model overall, scoring 51.1 to 33.7 on the Noometry Index.

Is Codellama 70b Instruct or GLM-5.2 better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 37.6 in the Noometry coding category.

How many benchmarks do Codellama 70b Instruct and GLM-5.2 share?

4 benchmarks have published results for both models. Codellama 70b Instruct has 7 scored results on Noometry and GLM-5.2 has 51.

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