Noometry

Model comparison

GPT-4.1 mini vs Llama 3.1-405B

GPT-4.1 mini is the stronger model overall, scoring 33.5 to 30.4 on the Noometry Index.

Last verified . 30 shared benchmarks.

GPT-4.1 mini OpenAI

33.5

Rank #232 Confirmed

Llama 3.1-405B Meta

30.4

Rank #279 Confirmed

Summary

  • They share 30 benchmarks with published results for both. GPT-4.1 mini scores higher in 6 categories and Llama 3.1-405B in 3 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in agentic & tool use, where GPT-4.1 mini leads 33.0 to 20.9.
  • The biggest single-benchmark swing is MATH Level 5: 87.3% for GPT-4.1 mini 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-4.1 miniLlama 3.1-405B
ProviderOpenAIMeta
Noometry Index33.530.4
Released2025-04-142024-07-23
WeightsProprietaryOpen
Context window1.05M—
Max output33K—
Input $ / M tokens$0.40—
Output $ / M tokens$1.60—
Results tracked4742

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Category by category

Coding Llama 3.1-405B leads

GPT-4.1 mini: 30.4 (#286), Llama 3.1-405B: 32.7 (#257)

BenchmarkGPT-4.1 miniLlama 3.1-405B
WeirdML37.6%21.4%
LMArena Coding13671291
SWE-bench Verified (bash only)23.9%—
Aider Polyglot32.4%—
SciCode40.4%—
BigCodeBench Instruct48.9%—
CadEval16%—

Agentic & Tool Use GPT-4.1 mini leads

GPT-4.1 mini: 33.0 (#52), Llama 3.1-405B: 20.9 (#131)

BenchmarkGPT-4.1 miniLlama 3.1-405B
Berkeley Function Calling Leaderboard50.5%—
TheAgentCompany—7.4%
Cybench—7.5%

Reasoning Llama 3.1-405B leads

GPT-4.1 mini: 10.9 (#335), Llama 3.1-405B: 16.4 (#293)

BenchmarkGPT-4.1 miniLlama 3.1-405B
Kagi LLM Benchmark48.6%45%
LMArena Hard Prompts13491270
DTBench68.8%61.4%
Epoch Capabilities Index135.01128.76
ARC-AGI-20%—
SimpleBench—23%
ARC-AGI-13.5%—
CritPt0%—
Chess Puzzles7%—
Mystery Game Puzzles7%—
LMCA21.1%—
BIG-Bench Hard—82.9%
ForecastBench—59.9
HellaSwag—89.2%
PIQA—85.9%
WinoGrande—89.2%

Math GPT-4.1 mini leads

GPT-4.1 mini: 23.1 (#264), Llama 3.1-405B: 17.3 (#283)

BenchmarkGPT-4.1 miniLlama 3.1-405B
OTIS Mock AIME 2024-202544.7%9.7%
Omni-MATH49.1%24.9%
LMArena Math13431281
MATH Level 587.3%49.8%
FrontierMath (Tiers 1-3)6.7%—
FrontierMath (Feb 2025 set)4.5%—

Knowledge GPT-4.1 mini leads

GPT-4.1 mini: 34.7 (#183), Llama 3.1-405B: 30.4 (#221)

BenchmarkGPT-4.1 miniLlama 3.1-405B
GPQA Diamond65.8%50.9%
MMLU-Pro78.3%72.3%
GPQA (HELM)61.4%52.2%
LMArena Expert13381243
SimpleQA Verified12.7%—
Confabulations—17.6%
ARC (AI2) Challenge—95.3%
MMLU—84.5%
TriviaQA—82.7%

Multimodal Not comparable

GPT-4.1 mini: 35.2 (#77), Llama 3.1-405B: —

BenchmarkGPT-4.1 miniLlama 3.1-405B
LMArena Vision1181—

Multilingual GPT-4.1 mini leads

GPT-4.1 mini: 45.9 (#161), Llama 3.1-405B: 40.9 (#209)

BenchmarkGPT-4.1 miniLlama 3.1-405B
LMArena Non-English13181248
LMArena Chinese13291242
LMArena French13571278
LMArena German13491252
LMArena Japanese12911208
LMArena Korean12981184
LMArena Russian13241265
LMArena Spanish13191259

Instruction Following GPT-4.1 mini leads

GPT-4.1 mini: 73.9 (#113), Llama 3.1-405B: 66.1 (#209)

BenchmarkGPT-4.1 miniLlama 3.1-405B
IFEval90.4%81.1%
LMArena Instruction Following13321259

Long Context Llama 3.1-405B leads

GPT-4.1 mini: 31.8 (#270), Llama 3.1-405B: 38.4 (#192)

BenchmarkGPT-4.1 miniLlama 3.1-405B
LMArena Longer Query13441266
Fiction.LiveBench44.4%—

Writing & Preference GPT-4.1 mini leads

GPT-4.1 mini: 48.8 (#193), Llama 3.1-405B: 39.1 (#246)

BenchmarkGPT-4.1 miniLlama 3.1-405B
LMArena Text13411284
LMArena Creative Writing13001262
EQ-Bench Creative Writing1147870
WildBench83.8%78.3%
LMArena Multi-Turn13541297

Frequently asked questions

Is GPT-4.1 mini better than Llama 3.1-405B?

GPT-4.1 mini is the stronger model overall, scoring 33.5 to 30.4 on the Noometry Index.

Is GPT-4.1 mini or Llama 3.1-405B better for coding?

Llama 3.1-405B scores higher on coding benchmarks: 32.7 versus 30.4 in the Noometry coding category.

How many benchmarks do GPT-4.1 mini and Llama 3.1-405B share?

30 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Llama 3.1-405B has 42.

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