Model comparison

Gemini 2.5 Flash-Lite vs Llama 13b

Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 24.4 on the Noometry Index.

Last verified . 9 shared benchmarks.

Gemini 2.5 Flash-Lite Google

37.0

Rank #211 Confirmed

Llama 13b Meta

24.4

Rank #348 Confirmed

Summary

  • They share 9 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 6 categories and Llama 13b in 0 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Gemini 2.5 Flash-Lite leads 56.8 to 13.8.
  • Llama 13b has downloadable open weights; the other is API-only.

Side by side

Gemini 2.5 Flash-Lite and Llama 13b specifications
Gemini 2.5 Flash-LiteLlama 13b
ProviderGoogleMeta
Noometry Index37.024.4
Released2025-06-172023-02-24
WeightsProprietaryOpen
Context window1.05M—
Max output66K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.40—
Results tracked3321

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Category by category

Coding Gemini 2.5 Flash-Lite leads

Gemini 2.5 Flash-Lite: 38.5 (#173), Llama 13b: 21.4 (#337)

Coding benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Coding1373683
WeirdML35.2%—
ALE-Bench325.9—

Agentic & Tool Use Not comparable

Gemini 2.5 Flash-Lite: 28.0 (#96), Llama 13b: —

Agentic & Tool Use benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
Berkeley Function Calling Leaderboard36.9%—

Reasoning Gemini 2.5 Flash-Lite leads

Gemini 2.5 Flash-Lite: 22.2 (#205), Llama 13b: 14.0 (#329)

Reasoning benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Hard Prompts1377728
Epoch Capabilities Index133.94100.58
Kagi LLM Benchmark40.5%—
DTBench62.8%—
LMCA18.1%—
BIG-Bench Hard—37.9%
HellaSwag—79.2%
LAMBADA—75.2%
PIQA—80.1%
WinoGrande—73%

Math Gemini 2.5 Flash-Lite leads

Gemini 2.5 Flash-Lite: 38.0 (#144), Llama 13b: 26.7 (#256)

Math benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Math1373838
Omni-MATH48%—
GSM8K—20.6%

Knowledge Not comparable

Gemini 2.5 Flash-Lite: 32.5 (#210), Llama 13b: —

Knowledge benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
MMLU-Pro53.7%—
Vectara Hallucination Rate3.3%—
GPQA (HELM)30.9%—
LMArena Expert1373—
ARC (AI2) Challenge—52.7%
BoolQ—78.7%
MMLU—47.7%
OpenBookQA—56.4%
TriviaQA—77.9%

Multimodal Not comparable

Gemini 2.5 Flash-Lite: 29.1 (#114), Llama 13b: —

Multimodal benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Vision1198—
VPCT30%—
ScienceQA—43.3%

Multilingual Gemini 2.5 Flash-Lite leads

Gemini 2.5 Flash-Lite: 49.3 (#134), Llama 13b: 16.6 (#297)

Multilingual benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Non-English1369819
LMArena Chinese1404—
LMArena French1388—
LMArena German1389—
LMArena Japanese1359—
LMArena Korean1360—
LMArena Russian1373—
LMArena Spanish1396—

Instruction Following Gemini 2.5 Flash-Lite leads

Gemini 2.5 Flash-Lite: 70.0 (#168), Llama 13b: 36.7 (#305)

Instruction Following benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Instruction Following1367781
IFEval81%—

Long Context Not comparable

Gemini 2.5 Flash-Lite: 33.3 (#262), Llama 13b: —

Long Context benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
Fiction.LiveBench47.2%—
LMArena Longer Query1373—

Writing & Preference Gemini 2.5 Flash-Lite leads

Gemini 2.5 Flash-Lite: 56.8 (#135), Llama 13b: 13.8 (#312)

Writing & Preference benchmarks
BenchmarkGemini 2.5 Flash-LiteLlama 13b
LMArena Text1379834
LMArena Creative Writing1367794
LMArena Multi-Turn1366753
WildBench81.8%—

Frequently asked questions

Is Gemini 2.5 Flash-Lite better than Llama 13b?

Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 24.4 on the Noometry Index.

Is Gemini 2.5 Flash-Lite or Llama 13b better for coding?

Gemini 2.5 Flash-Lite scores higher on coding benchmarks: 38.5 versus 21.4 in the Noometry coding category.

How many benchmarks do Gemini 2.5 Flash-Lite and Llama 13b share?

9 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and Llama 13b has 21.

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