Model comparison

Llama 2-70B vs Phi-4

Phi-4 is the stronger model overall, scoring 31.2 to 24.4 on the Noometry Index.

Last verified . 22 shared benchmarks.

Llama 2-70B Meta

24.4

Rank #349 Confirmed

Phi-4 Microsoft

31.2

Rank #279 Confirmed

Summary

  • They share 22 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Phi-4 in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Phi-4 leads 32.6 to 7.4.
  • The biggest single-benchmark swing is MATH Level 5: 3.3% for Llama 2-70B and 64.9% for Phi-4.

Side by side

Llama 2-70B and Phi-4 specifications
Llama 2-70BPhi-4
ProviderMetaMicrosoft
Noometry Index24.431.2
Released2023-07-182024-12-11
WeightsOpenOpen
Context window—128K
Max output—4K
Input $ / M tokens—$0.07
Output $ / M tokens—$0.14
Results tracked3537

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Category by category

Coding Phi-4 leads

Llama 2-70B: 31.4 (#286), Phi-4: 34.4 (#239)

Coding benchmarks
BenchmarkLlama 2-70BPhi-4
LMArena Coding10791231
BigCodeBench Instruct—45.5%
LiveBench Coding—30.7%
BigCodeBench Complete—55.4%

Agentic & Tool Use Not comparable

Llama 2-70B: —, Phi-4: 22.8 (#128)

Agentic & Tool Use benchmarks
BenchmarkLlama 2-70BPhi-4
Berkeley Function Calling Leaderboard—28.8%
BALROG—11.6%

Reasoning Phi-4 leads

Llama 2-70B: 14.4 (#325), Phi-4: 17.7 (#291)

Reasoning benchmarks
BenchmarkLlama 2-70BPhi-4
LMArena Hard Prompts10731220
Epoch Capabilities Index113.79130.42
Chess Puzzles—1%
LiveBench Reasoning—47.8%
DTBench41.6%—
LiveBench Data Analysis—45.2%
BIG-Bench Hard64.9%—
CommonsenseQA 2.050%—
ForecastBench51.4—
HellaSwag85.3%—
LAMBADA78.9%—
LiveBench—41.6%
PIQA82.8%—
WinoGrande80.2%—

Math Phi-4 leads

Llama 2-70B: 8.1 (#326), Phi-4: 20.8 (#285)

Math benchmarks
BenchmarkLlama 2-70BPhi-4
OTIS Mock AIME 2024-20250%13.8%
LMArena Math10911246
MATH Level 53.3%64.9%
LiveBench Math—42%
GSM8K69.6%—

Knowledge Phi-4 leads

Llama 2-70B: 7.4 (#310), Phi-4: 32.6 (#209)

Knowledge benchmarks
BenchmarkLlama 2-70BPhi-4
GPQA Diamond26.3%56.1%
LMArena Expert10391203
MMLU69.9%84.8%
Confabulations—29.4%
Vectara Hallucination Rate—3.7%
ARC (AI2) Challenge78.3%—
BoolQ88.6%—
OpenBookQA60.2%—
TriviaQA87.6%—

Multilingual Phi-4 leads

Llama 2-70B: 27.7 (#274), Phi-4: 37.2 (#237)

Multilingual benchmarks
BenchmarkLlama 2-70BPhi-4
LMArena Non-English10451197
LMArena Chinese9951212
LMArena French10901224
LMArena German10411222
LMArena Japanese9271158
LMArena Korean9641151
LMArena Russian10831209
LMArena Spanish11431234

Instruction Following Phi-4 leads

Llama 2-70B: 54.9 (#278), Phi-4: 60.4 (#251)

Instruction Following benchmarks
BenchmarkLlama 2-70BPhi-4
LMArena Instruction Following10711201
LiveBench Instruction Following—58.4%

Long Context Phi-4 leads

Llama 2-70B: 32.3 (#270), Phi-4: 36.9 (#226)

Long Context benchmarks
BenchmarkLlama 2-70BPhi-4
LMArena Longer Query10621217

Writing & Preference Phi-4 leads

Llama 2-70B: 32.3 (#279), Phi-4: 40.5 (#244)

Writing & Preference benchmarks
BenchmarkLlama 2-70BPhi-4
LMArena Text11151217
LMArena Creative Writing10751182
LMArena Multi-Turn10881206
Short-Story Creative Writing—62.6%
LiveBench Language—25.6%

Frequently asked questions

Is Llama 2-70B better than Phi-4?

Phi-4 is the stronger model overall, scoring 31.2 to 24.4 on the Noometry Index.

Is Llama 2-70B or Phi-4 better for coding?

Phi-4 scores higher on coding benchmarks: 34.4 versus 31.4 in the Noometry coding category.

How many benchmarks do Llama 2-70B and Phi-4 share?

22 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Phi-4 has 37.

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