Noometry

Model comparison

DeepSeek V4.1 Flash vs Llama 2-70B

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 24.4 on the Noometry Index.

Last verified . 21 shared benchmarks.

DeepSeek V4.1 Flash DeepSeek

52.8

Rank #38 Confirmed

Llama 2-70B Meta

24.4

Rank #349 Confirmed

Summary

  • They share 21 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 8 categories and Llama 2-70B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where DeepSeek V4.1 Flash leads 66.7 to 8.1.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.3% for DeepSeek V4.1 Flash and 0% for Llama 2-70B.

Side by side

DeepSeek V4.1 FlashLlama 2-70B
ProviderDeepSeekMeta
Noometry Index52.824.4
Released2026-09-092023-07-18
WeightsOpenOpen
Context window1M—
Max output393K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.60—
Results tracked3735

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Category by category

Coding DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 52.9 (#32), Llama 2-70B: 31.4 (#286)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Coding15061079
LMArena WebDev1619—
SciCode51.9%—
ALE-Bench1,092—

Agentic & Tool Use Not comparable

DeepSeek V4.1 Flash: 31.2 (#69), Llama 2-70B: —

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
APEX-Agents39.5%—
GDP.pdf19.8%—

Reasoning DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 50.2 (#36), Llama 2-70B: 14.4 (#325)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Hard Prompts14831073
DTBench89.9%41.6%
Epoch Capabilities Index154.9113.79
NYT Connections (extended)89.6%—
CritPt14.3%—
Mystery Game Puzzles43%—
LMCA47%—
Surface Evolver Bench46.3%—
BIG-Bench Hard—64.9%
CommonsenseQA 2.0—50%
ForecastBench—51.4
HellaSwag—85.3%
LAMBADA—78.9%
PIQA—82.8%
WinoGrande—80.2%

Math DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 66.7 (#25), Llama 2-70B: 8.1 (#326)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
OTIS Mock AIME 2024-202598.3%0%
LMArena Math14771091
FrontierMath (Tiers 1-3)67.4%—
FrontierMath Tier 426.8%—
ProofBench54%—
MATH Level 5—3.3%
GSM8K—69.6%

Knowledge DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 57.9 (#38), Llama 2-70B: 7.4 (#310)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
GPQA Diamond89.8%26.3%
LMArena Expert15061039
ARC (AI2) Challenge—78.3%
BoolQ—88.6%
MMLU—69.9%
OpenBookQA—60.2%
TriviaQA—87.6%

Multimodal Not comparable

DeepSeek V4.1 Flash: 39.1 (#61), Llama 2-70B: —

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Vision1277—
Furniture Assembly34.2%—

Multilingual DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 55.0 (#35), Llama 2-70B: 27.7 (#274)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Non-English14481045
LMArena Chinese1497995
LMArena French14521090
LMArena German14841041
LMArena Japanese1412927
LMArena Korean1452964
LMArena Russian14711083
LMArena Spanish14591143

Instruction Following DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 77.3 (#26), Llama 2-70B: 54.9 (#278)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Instruction Following14741071

Long Context DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 45.2 (#47), Llama 2-70B: 32.3 (#270)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Longer Query14751062

Writing & Preference DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 65.4 (#48), Llama 2-70B: 32.3 (#279)

BenchmarkDeepSeek V4.1 FlashLlama 2-70B
LMArena Text14621115
LMArena Creative Writing14351075
LMArena Multi-Turn14571088
EQ-Bench Creative Writing1540—

Frequently asked questions

Is DeepSeek V4.1 Flash better than Llama 2-70B?

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 24.4 on the Noometry Index.

Is DeepSeek V4.1 Flash or Llama 2-70B better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 31.4 in the Noometry coding category.

How many benchmarks do DeepSeek V4.1 Flash and Llama 2-70B share?

21 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and Llama 2-70B has 35.

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