Noometry

Model comparison

DeepSeek V4 Flash vs Qwen2-72B

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 29.5 on the Noometry Index.

Last verified . 20 shared benchmarks.

DeepSeek V4 Flash DeepSeek

53.6

Rank #32 Confirmed

Qwen2-72B Alibaba (Qwen)

29.5

Rank #294 Confirmed

Summary

  • They share 20 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Qwen2-72B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where DeepSeek V4 Flash leads 55.5 to 21.2.
  • The biggest single-benchmark swing is WeirdML: 63% for DeepSeek V4 Flash and 11.3% for Qwen2-72B.

Side by side

DeepSeek V4 FlashQwen2-72B
ProviderDeepSeekAlibaba (Qwen)
Noometry Index53.629.5
Released2026-04-242024-06-07
WeightsOpenOpen
Context window1M—
Max output393K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.60—
Results tracked4126

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Category by category

Coding DeepSeek V4 Flash leads

DeepSeek V4 Flash: 47.6 (#56), Qwen2-72B: 28.7 (#303)

BenchmarkDeepSeek V4 FlashQwen2-72B
WeirdML63%11.3%
LMArena Coding14571196
FrontierCode18.8%—
LMArena WebDev1581—
SciCode49.9%—
BigCodeBench Instruct—38.5%
BigCodeBench Complete—54%
ALE-Bench1,306—

Agentic & Tool Use Not comparable

DeepSeek V4 Flash: —, Qwen2-72B: 16.9 (#138)

BenchmarkDeepSeek V4 FlashQwen2-72B
TheAgentCompany—1.1%
METR Time Horizons—29.9%

Reasoning DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.7 (#25), Qwen2-72B: 22.2 (#184)

BenchmarkDeepSeek V4 FlashQwen2-72B
LMArena Hard Prompts14431191
Epoch Capabilities Index154.51125.27
ARC-AGI-261.4%—
SimpleBench61.1%—
Kagi LLM Benchmark52.2%—
NYT Connections (extended)89.6%—
ARC-AGI-189%—
CritPt16.6%—
Chess Puzzles33%—
Mystery Game Puzzles34%—
DTBench90.9%—
LMCA41.7%—

Math DeepSeek V4 Flash leads

DeepSeek V4 Flash: 60.0 (#31), Qwen2-72B: 27.9 (#232)

BenchmarkDeepSeek V4 FlashQwen2-72B
LMArena Math14271235
FrontierMath (Tiers 1-3)57.5%—
FrontierMath Tier 424.4%—
MathArena Final-Answer Competitions76.5%—
OTIS Mock AIME 2024-202594.4%—
ProofBench56%—
MATH Level 5—39.1%

Knowledge DeepSeek V4 Flash leads

DeepSeek V4 Flash: 55.5 (#43), Qwen2-72B: 21.2 (#270)

BenchmarkDeepSeek V4 FlashQwen2-72B
GPQA Diamond91%40.8%
LMArena Expert14411171
SimpleQA Verified33.6%—
MMLU—82.4%

Multilingual DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.2 (#71), Qwen2-72B: 36.0 (#239)

BenchmarkDeepSeek V4 FlashQwen2-72B
LMArena Non-English14201176
LMArena Chinese14671240
LMArena French14381169
LMArena German14181151
LMArena Japanese14031111
LMArena Korean13831083
LMArena Russian14281169
LMArena Spanish14371168

Instruction Following DeepSeek V4 Flash leads

DeepSeek V4 Flash: 75.1 (#76), Qwen2-72B: 62.0 (#236)

BenchmarkDeepSeek V4 FlashQwen2-72B
LMArena Instruction Following14211181

Long Context DeepSeek V4 Flash leads

DeepSeek V4 Flash: 43.8 (#81), Qwen2-72B: 36.1 (#230)

BenchmarkDeepSeek V4 FlashQwen2-72B
LMArena Longer Query14351193

Writing & Preference DeepSeek V4 Flash leads

DeepSeek V4 Flash: 64.0 (#59), Qwen2-72B: 41.0 (#236)

BenchmarkDeepSeek V4 FlashQwen2-72B
LMArena Text14321203
LMArena Creative Writing14031181
LMArena Multi-Turn14491195
EQ-Bench Creative Writing1559—

Frequently asked questions

Is DeepSeek V4 Flash better than Qwen2-72B?

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 29.5 on the Noometry Index.

Is DeepSeek V4 Flash or Qwen2-72B better for coding?

DeepSeek V4 Flash scores higher on coding benchmarks: 47.6 versus 28.7 in the Noometry coding category.

How many benchmarks do DeepSeek V4 Flash and Qwen2-72B share?

20 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Qwen2-72B has 26.

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