Noometry

Model comparison

Deepseek Coder v2 vs Llama 3.1-405B

Deepseek Coder v2 is the stronger model overall, scoring 35.9 to 30.7 on the Noometry Index.

Last verified . 19 shared benchmarks.

Deepseek Coder v2 DeepSeek

35.9

Rank #220 Confirmed

Llama 3.1-405B Meta

30.7

Rank #288 Confirmed

Summary

  • They share 19 benchmarks with published results for both. Deepseek Coder v2 scores higher in 4 categories and Llama 3.1-405B in 4 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in math, where Deepseek Coder v2 leads 34.9 to 18.4.

Side by side

Deepseek Coder v2Llama 3.1-405B
ProviderDeepSeekMeta
Noometry Index35.930.7
Released2024-06-172024-07-23
WeightsOpenOpen
Context window——
Max output——
Input $ / M tokens——
Output $ / M tokens——
Results tracked2442

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Category by category

Coding Deepseek Coder v2 leads

Deepseek Coder v2: 38.1 (#183), Llama 3.1-405B: 33.1 (#262)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Coding12511291
WeirdML—21.4%
BigCodeBench Instruct48.2%—
BigCodeBench Complete59.7%—
HumanEval+82.3%—
MBPP+75.1%—

Agentic & Tool Use Not comparable

Deepseek Coder v2: —, Llama 3.1-405B: 21.0 (#140)

BenchmarkDeepseek Coder v2Llama 3.1-405B
TheAgentCompany—7.4%
Cybench—7.5%

Reasoning Deepseek Coder v2 leads

Deepseek Coder v2: 23.6 (#176), Llama 3.1-405B: 16.8 (#300)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Hard Prompts12071269
WinoGrande83.7%89.2%
SimpleBench—23%
Kagi LLM Benchmark—45%
DTBench—61.4%
BIG-Bench Hard—82.9%
Epoch Capabilities Index—128.75
ForecastBench—59.9
HellaSwag—89.2%
PIQA—85.9%

Math Deepseek Coder v2 leads

Deepseek Coder v2: 34.9 (#190), Llama 3.1-405B: 18.4 (#290)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Math12411281
OTIS Mock AIME 2024-2025—9.7%
Omni-MATH—24.9%
MATH Level 5—49.8%
GSM8K94.5%—

Knowledge Deepseek Coder v2 leads

Deepseek Coder v2: 32.3 (#212), Llama 3.1-405B: 30.4 (#227)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Expert11811243
ARC (AI2) Challenge64.3%95.3%
GPQA Diamond—50.9%
MMLU-Pro—72.3%
Confabulations—17.6%
GPQA (HELM)—52.2%
MMLU—84.5%
TriviaQA—82.7%

Multilingual Llama 3.1-405B leads

Deepseek Coder v2: 36.3 (#240), Llama 3.1-405B: 40.7 (#214)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Non-English11821248
LMArena Chinese12011242
LMArena French11851279
LMArena German11641252
LMArena Japanese11261208
LMArena Korean11041184
LMArena Russian11881265
LMArena Spanish11531260

Instruction Following Llama 3.1-405B leads

Deepseek Coder v2: 61.7 (#242), Llama 3.1-405B: 65.9 (#214)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Instruction Following11801259
IFEval—81.1%

Long Context Llama 3.1-405B leads

Deepseek Coder v2: 37.0 (#224), Llama 3.1-405B: 38.4 (#197)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Longer Query12191266

Writing & Preference Too close to call

Deepseek Coder v2: 38.2 (#253), Llama 3.1-405B: 38.9 (#251)

BenchmarkDeepseek Coder v2Llama 3.1-405B
LMArena Text11911284
LMArena Creative Writing11201262
LMArena Multi-Turn11771297
EQ-Bench Creative Writing—870
WildBench—78.3%

Frequently asked questions

Is Deepseek Coder v2 better than Llama 3.1-405B?

Deepseek Coder v2 is the stronger model overall, scoring 35.9 to 30.7 on the Noometry Index.

Is Deepseek Coder v2 or Llama 3.1-405B better for coding?

Deepseek Coder v2 scores higher on coding benchmarks: 38.1 versus 33.1 in the Noometry coding category.

How many benchmarks do Deepseek Coder v2 and Llama 3.1-405B share?

19 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and Llama 3.1-405B has 42.

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