Model comparison

Amazon Nova Experimental Chat 10 20 vs GLM-5

GLM-5 is the stronger model overall, scoring 46.1 to 42.1 on the Noometry Index.

Last verified . 17 shared benchmarks.

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Amazon Nova Experimental Chat 10 20 scores higher in 1 category and GLM-5 in 7 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5 leads 52.3 to 38.5.
  • GLM-5 has downloadable open weights; the other is API-only.

Side by side

Amazon Nova Experimental Chat 10 20 and GLM-5 specifications
Amazon Nova Experimental Chat 10 20GLM-5
ProviderAmazonZ.ai (Zhipu)
Noometry Index42.146.1
Released—2026-02-11
WeightsProprietaryOpen
Context window—205K
Max output—131K
Input $ / M tokens—$1
Output $ / M tokens—$3.20
Results tracked1745

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Category by category

Coding GLM-5 leads

Amazon Nova Experimental Chat 10 20: 41.6 (#123), GLM-5: 49.0 (#52)

Coding benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Coding14121461
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

Agentic & Tool Use Not comparable

Amazon Nova Experimental Chat 10 20: —, GLM-5: 31.1 (#71)

Agentic & Tool Use benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-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 Too close to call

Amazon Nova Experimental Chat 10 20: 28.4 (#106), GLM-5: 27.6 (#116)

Reasoning benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Hard Prompts13961452
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—145.83
ForecastBench—61

Math GLM-5 leads

Amazon Nova Experimental Chat 10 20: 39.0 (#119), GLM-5: 46.4 (#71)

Math benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Math14251440
MathArena Final-Answer Competitions—65.7%
OTIS Mock AIME 2024-2025—80%
FrontierMath (Feb 2025 set)—16.4%
FrontierMath Tier 4 (v1)—2.1%

Knowledge GLM-5 leads

Amazon Nova Experimental Chat 10 20: 38.5 (#144), GLM-5: 52.3 (#64)

Knowledge benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Expert13861454
GPQA Diamond—87.8%
Vectara Hallucination Rate—10.1%

Multilingual GLM-5 leads

Amazon Nova Experimental Chat 10 20: 49.5 (#131), GLM-5: 53.7 (#58)

Multilingual benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Non-English13721430
LMArena Chinese14041511
LMArena French14251455
LMArena German13911445
LMArena Japanese13601416
LMArena Korean13241423
LMArena Russian13711436
LMArena Spanish13821454

Instruction Following GLM-5 leads

Amazon Nova Experimental Chat 10 20: 72.1 (#141), GLM-5: 75.2 (#67)

Instruction Following benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Instruction Following13651428

Long Context GLM-5 leads

Amazon Nova Experimental Chat 10 20: 41.7 (#133), GLM-5: 44.7 (#60)

Long Context benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Longer Query13701446
CL-bench—18.7%

Writing & Preference GLM-5 leads

Amazon Nova Experimental Chat 10 20: 56.6 (#136), GLM-5: 66.0 (#38)

Writing & Preference benchmarks
BenchmarkAmazon Nova Experimental Chat 10 20GLM-5
LMArena Text13941446
LMArena Creative Writing13181439
LMArena Multi-Turn13641456
EQ-Bench Creative Writing—1601

Frequently asked questions

Is Amazon Nova Experimental Chat 10 20 better than GLM-5?

GLM-5 is the stronger model overall, scoring 46.1 to 42.1 on the Noometry Index.

Is Amazon Nova Experimental Chat 10 20 or GLM-5 better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 41.6 in the Noometry coding category.

How many benchmarks do Amazon Nova Experimental Chat 10 20 and GLM-5 share?

17 benchmarks have published results for both models. Amazon Nova Experimental Chat 10 20 has 17 scored results on Noometry and GLM-5 has 45.

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