Noometry

Model comparison

DeepSeek V4 Flash vs Llama 2-13B

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 29.1 on the Noometry Index.

Last verified . 20 shared benchmarks.

DeepSeek V4 Flash DeepSeek

53.6

Rank #32 Confirmed

Llama 2-13B Meta

29.1

Rank #304 Confirmed

Summary

  • They share 20 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Llama 2-13B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where DeepSeek V4 Flash leads 53.7 to 12.3.
  • The biggest single-benchmark swing is DTBench: 90.9% for DeepSeek V4 Flash and 42.2% for Llama 2-13B.

Side by side

DeepSeek V4 FlashLlama 2-13B
ProviderDeepSeekMeta
Noometry Index53.629.1
Released2026-04-242023-07-18
WeightsOpenOpen
Context window1M—
Max output393K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.60—
Results tracked4132

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Category by category

Coding DeepSeek V4 Flash leads

DeepSeek V4 Flash: 47.6 (#56), Llama 2-13B: 30.4 (#287)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Coding14571062
FrontierCode18.8%—
LMArena WebDev1581—
SciCode49.9%—
WeirdML63%—
ALE-Bench1,306—

Reasoning DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.7 (#25), Llama 2-13B: 12.3 (#333)

BenchmarkDeepSeek V4 FlashLlama 2-13B
Chess Puzzles33%0%
LMArena Hard Prompts14431051
DTBench90.9%42.2%
Epoch Capabilities Index154.51105.8
ARC-AGI-261.4%—
SimpleBench61.1%—
Kagi LLM Benchmark52.2%—
NYT Connections (extended)89.6%—
ARC-AGI-189%—
CritPt16.6%—
Mystery Game Puzzles34%—
LMCA41.7%—
BIG-Bench Hard—58.2%
HellaSwag—80.7%
LAMBADA—76.5%
PIQA—80.8%
WinoGrande—72.8%

Math DeepSeek V4 Flash leads

DeepSeek V4 Flash: 60.0 (#31), Llama 2-13B: 28.7 (#226)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Math14271065
FrontierMath (Tiers 1-3)57.5%—
FrontierMath Tier 424.4%—
MathArena Final-Answer Competitions76.5%—
OTIS Mock AIME 2024-202594.4%—
ProofBench56%—
GSM8K—36.9%

Knowledge DeepSeek V4 Flash leads

DeepSeek V4 Flash: 55.5 (#43), Llama 2-13B: 27.5 (#244)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Expert14411030
GPQA Diamond91%—
SimpleQA Verified33.6%—
ARC (AI2) Challenge—60.3%
BoolQ—82.4%
MMLU—55.6%
OpenBookQA—57%
TriviaQA—79.6%

Multimodal Not comparable

DeepSeek V4 Flash: —, Llama 2-13B: —

BenchmarkDeepSeek V4 FlashLlama 2-13B
ScienceQA—55.8%

Multilingual DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.2 (#71), Llama 2-13B: 26.7 (#274)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Non-English14201024
LMArena Chinese14671001
LMArena French14381043
LMArena German14181009
LMArena Japanese1403894
LMArena Korean1383953
LMArena Russian14281055
LMArena Spanish14371086

Instruction Following DeepSeek V4 Flash leads

DeepSeek V4 Flash: 75.1 (#76), Llama 2-13B: 53.5 (#282)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Instruction Following14211046

Long Context DeepSeek V4 Flash leads

DeepSeek V4 Flash: 43.8 (#81), Llama 2-13B: 32.3 (#264)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Longer Query14351064

Writing & Preference DeepSeek V4 Flash leads

DeepSeek V4 Flash: 64.0 (#59), Llama 2-13B: 30.0 (#284)

BenchmarkDeepSeek V4 FlashLlama 2-13B
LMArena Text14321085
LMArena Creative Writing14031047
LMArena Multi-Turn14491050
EQ-Bench Creative Writing1559—

Frequently asked questions

Is DeepSeek V4 Flash better than Llama 2-13B?

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 29.1 on the Noometry Index.

Is DeepSeek V4 Flash or Llama 2-13B better for coding?

DeepSeek V4 Flash scores higher on coding benchmarks: 47.6 versus 30.4 in the Noometry coding category.

How many benchmarks do DeepSeek V4 Flash and Llama 2-13B share?

20 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Llama 2-13B has 32.

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