Noometry

Model comparison

Grok-2 (Dec 2024) vs Llama 3.1-70B

Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 29.6 on the Noometry Index.

Last verified . 23 shared benchmarks.

Grok-2 (Dec 2024) xAI

33.7

Rank #239 Confirmed

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

Summary

  • They share 23 benchmarks with published results for both. Grok-2 (Dec 2024) scores higher in 7 categories and Llama 3.1-70B in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Grok-2 (Dec 2024) leads 48.6 to 35.4.
  • The biggest single-benchmark swing is MATH Level 5: 63.5% for Grok-2 (Dec 2024) and 36.7% for Llama 3.1-70B.
  • Llama 3.1-70B has downloadable open weights; the other is API-only.

Side by side

Grok-2 (Dec 2024)Llama 3.1-70B
ProviderxAIMeta
Noometry Index33.729.6
Released2024-08-132024-07-23
WeightsProprietaryOpen
Context window—128K
Max output—4K
Input $ / M tokens—$0.40
Output $ / M tokens—$0.40
Results tracked3435

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Category by category

Coding Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 33.3 (#258), Llama 3.1-70B: 30.3 (#296)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
WeirdML22.2%9%
LMArena Coding12871260
BigCodeBench Instruct—46.1%
LiveBench Coding46.4%—
BigCodeBench Complete—54.8%

Agentic & Tool Use Not comparable

Grok-2 (Dec 2024): —, Llama 3.1-70B: 25.1 (#112)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
TheAgentCompany—6.9%
BALROG—27.9%

Reasoning Llama 3.1-70B leads

Grok-2 (Dec 2024): 16.9 (#299), Llama 3.1-70B: 21.6 (#220)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
LMArena Hard Prompts12721241
DTBench65.2%60%
Epoch Capabilities Index130.48125.92
SimpleBench22.7%—
LiveBench Reasoning54.8%—
LiveBench Data Analysis54.5%—
LMCA—14.8%
LiveBench54.3%—

Math Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 20.8 (#284), Llama 3.1-70B: 13.5 (#304)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
OTIS Mock AIME 2024-202511.5%3.6%
LMArena Math12831252
MATH Level 563.5%36.7%
Omni-MATH—21%
LiveBench Math54.9%—
FrontierMath (Feb 2025 set)0.7%—

Knowledge Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 29.8 (#233), Llama 3.1-70B: 24.2 (#269)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
GPQA Diamond53.8%44.2%
LMArena Expert12541209
MMLU-Pro—65.3%
Confabulations20.1%—
GPQA (HELM)—42.6%
MMLU—80.1%

Multilingual Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 43.1 (#188), Llama 3.1-70B: 38.8 (#225)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
LMArena Non-English12821219
LMArena Chinese12891215
LMArena French13181261
LMArena German12871222
LMArena Japanese12441132
LMArena Korean12371140
LMArena Russian12861234
LMArena Spanish12811253

Instruction Following Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 66.9 (#202), Llama 3.1-70B: 65.3 (#223)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
LMArena Instruction Following12701231
LiveBench Instruction Following69.6%—
IFEval—82.1%

Long Context Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 38.8 (#190), Llama 3.1-70B: 37.6 (#214)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
LMArena Longer Query12761241

Writing & Preference Grok-2 (Dec 2024) leads

Grok-2 (Dec 2024): 48.6 (#198), Llama 3.1-70B: 35.4 (#267)

BenchmarkGrok-2 (Dec 2024)Llama 3.1-70B
LMArena Text13051261
LMArena Creative Writing12841232
LMArena Multi-Turn12901256
Short-Story Creative Writing63.6%—
EQ-Bench Creative Writing—784
WildBench—75.8%
LiveBench Language45.6%—

Frequently asked questions

Is Grok-2 (Dec 2024) better than Llama 3.1-70B?

Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 29.6 on the Noometry Index.

Is Grok-2 (Dec 2024) or Llama 3.1-70B better for coding?

Grok-2 (Dec 2024) scores higher on coding benchmarks: 33.3 versus 30.3 in the Noometry coding category.

How many benchmarks do Grok-2 (Dec 2024) and Llama 3.1-70B share?

23 benchmarks have published results for both models. Grok-2 (Dec 2024) has 34 scored results on Noometry and Llama 3.1-70B has 35.

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