Model comparison

DeepSeek-V2.5 (Sep 2024) vs Llama 2-13B

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 29.6 on the Noometry Index.

Last verified . 17 shared benchmarks.

DeepSeek-V2.5 (Sep 2024) DeepSeek

37.6

Rank #200 Confirmed

Llama 2-13B Meta

29.6

Rank #309 Confirmed

Summary

  • They share 17 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 8 categories and Llama 2-13B in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where DeepSeek-V2.5 (Sep 2024) leads 49.8 to 29.8.

Side by side

DeepSeek-V2.5 (Sep 2024) and Llama 2-13B specifications
DeepSeek-V2.5 (Sep 2024)Llama 2-13B
ProviderDeepSeekMeta
Noometry Index37.629.6
Released2024-09-062023-07-18
WeightsOpenOpen
Context window——
Max output——
Input $ / M tokens——
Output $ / M tokens——
Results tracked2232

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Category by category

Coding Too close to call

DeepSeek-V2.5 (Sep 2024): 31.7 (#281), Llama 2-13B: 30.9 (#291)

Coding benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Coding13091062
Aider Polyglot17.8%—
BigCodeBench Instruct48.6%—
BigCodeBench Complete53.2%—
HumanEval+83.5%—
MBPP+74.1%—

Reasoning DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 25.6 (#145), Llama 2-13B: 12.8 (#337)

Reasoning benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Hard Prompts12891051
Chess Puzzles—0%
DTBench—42.2%
BIG-Bench Hard—58.2%
Epoch Capabilities Index—106.17
HellaSwag—80.7%
LAMBADA—76.5%
PIQA—80.8%
WinoGrande—72.8%

Math DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 35.9 (#177), Llama 2-13B: 31.1 (#229)

Math benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Math12881065
GSM8K—36.9%

Knowledge DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 34.8 (#193), Llama 2-13B: 28.1 (#249)

Knowledge benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Expert12661030
ARC (AI2) Challenge—60.3%
BoolQ—82.4%
MMLU—55.6%
OpenBookQA—57%
TriviaQA—79.6%

Multimodal Not comparable

DeepSeek-V2.5 (Sep 2024): —, Llama 2-13B: —

Multimodal benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
ScienceQA—55.8%

Multilingual DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 42.5 (#193), Llama 2-13B: 26.5 (#279)

Multilingual benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Non-English12731024
LMArena Chinese13181001
LMArena French12891044
LMArena German12581009
LMArena Japanese1228894
LMArena Korean1209953
LMArena Russian12891055
LMArena Spanish12481087

Instruction Following DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 67.5 (#194), Llama 2-13B: 53.3 (#287)

Instruction Following benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Instruction Following12801045

Long Context DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 39.5 (#174), Llama 2-13B: 32.3 (#269)

Long Context benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Longer Query13011064

Writing & Preference DeepSeek-V2.5 (Sep 2024) leads

DeepSeek-V2.5 (Sep 2024): 49.8 (#187), Llama 2-13B: 29.8 (#289)

Writing & Preference benchmarks
BenchmarkDeepSeek-V2.5 (Sep 2024)Llama 2-13B
LMArena Text12941084
LMArena Creative Writing12851047
LMArena Multi-Turn12971050

Frequently asked questions

Is DeepSeek-V2.5 (Sep 2024) better than Llama 2-13B?

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 29.6 on the Noometry Index.

Is DeepSeek-V2.5 (Sep 2024) or Llama 2-13B better for coding?

They score almost the same on coding (31.7 vs 30.9); test both on your own repository before choosing.

How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Llama 2-13B share?

17 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Llama 2-13B has 32.

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