Model comparison

GPT-4.5 vs Llama 13b

GPT-4.5 is the stronger model overall, scoring 37.2 to 24.4 on the Noometry Index.

Last verified . 9 shared benchmarks.

GPT-4.5 OpenAI

37.2

Rank #208 Confirmed

Llama 13b Meta

24.4

Rank #348 Confirmed

Summary

  • They share 9 benchmarks with published results for both. GPT-4.5 scores higher in 5 categories and Llama 13b in 1 category; 5 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GPT-4.5 leads 56.9 to 13.8.
  • Llama 13b has downloadable open weights; the other is API-only.

Side by side

GPT-4.5 and Llama 13b specifications
GPT-4.5Llama 13b
ProviderOpenAIMeta
Noometry Index37.224.4
Released2025-02-272023-02-24
WeightsProprietaryOpen
Context window——
Max output——
Input $ / M tokens——
Output $ / M tokens——
Results tracked4221

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Category by category

Coding GPT-4.5 leads

GPT-4.5: 42.2 (#109), Llama 13b: 21.4 (#337)

Coding benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Coding1396683
Aider Polyglot44.9%—
WeirdML39.4%—
LiveBench Coding75.2%—

Agentic & Tool Use Not comparable

GPT-4.5: 27.9 (#97), Llama 13b: —

Agentic & Tool Use benchmarks
BenchmarkGPT-4.5Llama 13b
Cybench17.5%—

Reasoning Too close to call

GPT-4.5: 13.9 (#330), Llama 13b: 14.0 (#329)

Reasoning benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Hard Prompts1403728
Epoch Capabilities Index136.74100.58
ARC-AGI-20.8%—
SimpleBench34.5%—
ARC-AGI-110.3%—
EnigmaEval3.2%—
LiveBench Reasoning71.1%—
LiveBench Data Analysis64.3%—
BIG-Bench Hard—37.9%
ForecastBench61.7—
HellaSwag—79.2%
LAMBADA—75.2%
LiveBench69%—
PIQA—80.1%
WinoGrande—73%

Math GPT-4.5 leads

GPT-4.5: 32.6 (#211), Llama 13b: 26.7 (#256)

Math benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Math1412838
OTIS Mock AIME 2024-202537.8%—
LiveBench Math69.3%—
MATH Level 578.6%—
GSM8K—20.6%

Knowledge Not comparable

GPT-4.5: 32.5 (#211), Llama 13b: —

Knowledge benchmarks
BenchmarkGPT-4.5Llama 13b
GPQA Diamond68.7%—
Humanity's Last Exam5.4%—
Confabulations13.6%—
LMArena Expert1394—
ARC (AI2) Challenge—52.7%
BoolQ—78.7%
MMLU—47.7%
OpenBookQA—56.4%
TriviaQA—77.9%

Multimodal Not comparable

GPT-4.5: 37.6 (#71), Llama 13b: —

Multimodal benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Vision1195—
VPCT45%—
ScienceQA—43.3%

Multilingual GPT-4.5 leads

GPT-4.5: 52.5 (#83), Llama 13b: 16.6 (#297)

Multilingual benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Non-English1413819
LMArena Chinese1421—
LMArena French1418—
LMArena German1457—
LMArena Japanese1416—
LMArena Korean1392—
LMArena Russian1419—

Instruction Following GPT-4.5 leads

GPT-4.5: 72.6 (#134), Llama 13b: 36.7 (#305)

Instruction Following benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Instruction Following1404781
LiveBench Instruction Following72.3%—

Long Context Not comparable

GPT-4.5: 40.4 (#155), Llama 13b: —

Long Context benchmarks
BenchmarkGPT-4.5Llama 13b
Fiction.LiveBench63.9%—
LMArena Longer Query1406—

Writing & Preference GPT-4.5 leads

GPT-4.5: 56.9 (#134), Llama 13b: 13.8 (#312)

Writing & Preference benchmarks
BenchmarkGPT-4.5Llama 13b
LMArena Text1417834
LMArena Creative Writing1394794
LMArena Multi-Turn1444753
Short-Story Creative Writing75.6%—
EQ-Bench Creative Writing1258—
LiveBench Language61.5%—

Frequently asked questions

Is GPT-4.5 better than Llama 13b?

GPT-4.5 is the stronger model overall, scoring 37.2 to 24.4 on the Noometry Index.

Is GPT-4.5 or Llama 13b better for coding?

GPT-4.5 scores higher on coding benchmarks: 42.2 versus 21.4 in the Noometry coding category.

How many benchmarks do GPT-4.5 and Llama 13b share?

9 benchmarks have published results for both models. GPT-4.5 has 42 scored results on Noometry and Llama 13b has 21.

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