Noometry

Model comparison

GPT-4 vs Llama 3.1-405B

Llama 3.1-405B is the stronger model overall, scoring 30.4 to 28.9 on the Noometry Index.

Last verified . 30 shared benchmarks.

GPT-4 OpenAI

28.9

Rank #308 Confirmed

Llama 3.1-405B Meta

30.4

Rank #279 Confirmed

Summary

  • They share 30 benchmarks with published results for both. GPT-4 scores higher in 1 category and Llama 3.1-405B in 7 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Llama 3.1-405B leads 30.4 to 18.4.
  • The biggest single-benchmark swing is MATH Level 5: 23% for GPT-4 and 49.8% for Llama 3.1-405B.
  • Llama 3.1-405B has downloadable open weights; the other is API-only.

Side by side

GPT-4Llama 3.1-405B
ProviderOpenAIMeta
Noometry Index28.930.4
Released2023-03-142024-07-23
WeightsProprietaryOpen
Context window8K—
Max output8K—
Input $ / M tokens$30—
Output $ / M tokens$60—
Results tracked3842

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Category by category

Coding Llama 3.1-405B leads

GPT-4: 31.2 (#277), Llama 3.1-405B: 32.7 (#257)

BenchmarkGPT-4Llama 3.1-405B
WeirdML12.4%21.4%
LMArena Coding12541291
BigCodeBench Instruct46%—
BigCodeBench Complete57.2%—
HumanEval+79.3%—

Agentic & Tool Use Not comparable

GPT-4: —, Llama 3.1-405B: 20.9 (#131)

BenchmarkGPT-4Llama 3.1-405B
TheAgentCompany—7.4%
Cybench—7.5%
METR Time Horizons36.1%—

Reasoning Too close to call

GPT-4: 17.3 (#285), Llama 3.1-405B: 16.4 (#293)

BenchmarkGPT-4Llama 3.1-405B
LMArena Hard Prompts12411270
DTBench62.7%61.4%
BIG-Bench Hard75.1%82.9%
Epoch Capabilities Index125.88128.76
ForecastBench57.859.9
HellaSwag95.3%89.2%
WinoGrande87.5%89.2%
SimpleBench—23%
Kagi LLM Benchmark—45%
Chess Puzzles4%—
Mystery Game Puzzles12%—
LMCA17.1%—
PIQA—85.9%

Math Llama 3.1-405B leads

GPT-4: 10.1 (#304), Llama 3.1-405B: 17.3 (#283)

BenchmarkGPT-4Llama 3.1-405B
OTIS Mock AIME 2024-20251.1%9.7%
LMArena Math12691281
MATH Level 523%49.8%
Omni-MATH—24.9%
GSM8K92%—

Knowledge Llama 3.1-405B leads

GPT-4: 18.4 (#277), Llama 3.1-405B: 30.4 (#221)

BenchmarkGPT-4Llama 3.1-405B
GPQA Diamond35.7%50.9%
LMArena Expert12111243
MMLU86.4%84.5%
TriviaQA84.8%82.7%
MMLU-Pro—72.3%
Confabulations—17.6%
GPQA (HELM)—52.2%
ARC (AI2) Challenge—95.3%

Multilingual Too close to call

GPT-4: 40.8 (#210), Llama 3.1-405B: 40.9 (#209)

BenchmarkGPT-4Llama 3.1-405B
LMArena Non-English12461248
LMArena Chinese12421242
LMArena French12821278
LMArena German12511252
LMArena Japanese12091208
LMArena Korean11841184
LMArena Russian12511265
LMArena Spanish12611259

Instruction Following Too close to call

GPT-4: 65.5 (#217), Llama 3.1-405B: 66.1 (#209)

BenchmarkGPT-4Llama 3.1-405B
LMArena Instruction Following12411259
IFEval—81.1%

Long Context Too close to call

GPT-4: 37.7 (#207), Llama 3.1-405B: 38.4 (#192)

BenchmarkGPT-4Llama 3.1-405B
LMArena Longer Query12441266

Writing & Preference Llama 3.1-405B leads

GPT-4: 35.0 (#263), Llama 3.1-405B: 39.1 (#246)

BenchmarkGPT-4Llama 3.1-405B
LMArena Text12631284
LMArena Creative Writing12441262
EQ-Bench Creative Writing752870
LMArena Multi-Turn12571297
WildBench—78.3%

Frequently asked questions

Is GPT-4 better than Llama 3.1-405B?

Llama 3.1-405B is the stronger model overall, scoring 30.4 to 28.9 on the Noometry Index.

Is GPT-4 or Llama 3.1-405B better for coding?

Llama 3.1-405B scores higher on coding benchmarks: 32.7 versus 31.2 in the Noometry coding category.

How many benchmarks do GPT-4 and Llama 3.1-405B share?

30 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Llama 3.1-405B has 42.

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