Noometry

Model comparison

DeepSeek V4.1 Flash vs Qwen2.5 32B Instruct

DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 29.7 on the Noometry Index.

Last verified . 1 shared benchmarks.

DeepSeek V4.1 Flash DeepSeek

50.3

Rank #40 Confirmed

Qwen2.5 32B Instruct Alibaba (Qwen)

29.7

Rank #291 Confirmed

Summary

  • They share 1 benchmark with published results for both. DeepSeek V4.1 Flash scores higher in 4 categories and Qwen2.5 32B Instruct in 0 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in math, where DeepSeek V4.1 Flash leads 48.4 to 15.3.
  • DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
  • DeepSeek V4.1 Flash accepts more context: 1M tokens versus 131K.

Side by side

DeepSeek V4.1 FlashQwen2.5 32B Instruct
ProviderDeepSeekAlibaba (Qwen)
Noometry Index50.329.7
Released2026-09-092024-09
WeightsOpenOpen
Context window1M131K
Max output393K8K
Input $ / M tokens$0.15$0.70
Output $ / M tokens$0.60$2.80
Results tracked257

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Category by category

Coding DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 52.8 (#29), Qwen2.5 32B Instruct: 38.1 (#165)

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
LMArena WebDev1620—
SciCode51.9%—
BigCodeBench Instruct—45%
LMArena Coding1511—
BigCodeBench Complete—52.3%
ALE-Bench1,092—

Reasoning DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 46.2 (#39), Qwen2.5 32B Instruct: 18.5 (#262)

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
Epoch Capabilities Index155.01128.52
NYT Connections (extended)89.6%—
CritPt14.3%—
Chess Puzzles—0%
LMArena Hard Prompts1485—
DTBench89.9%—
LMCA47%—
Surface Evolver Bench46.3%—

Math DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 48.4 (#52), Qwen2.5 32B Instruct: 15.3 (#289)

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
OTIS Mock AIME 2024-2025—7.4%
ProofBench54%—
LMArena Math1493—
MATH Level 5—56.1%

Knowledge DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 41.6 (#97), Qwen2.5 32B Instruct: 24.9 (#259)

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
GPQA Diamond—46.1%
LMArena Expert1505—

Multilingual Not comparable

DeepSeek V4.1 Flash: 55.5 (#29), Qwen2.5 32B Instruct: —

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
LMArena Non-English1452—
LMArena Chinese1506—
LMArena French1448—
LMArena Russian1473—
LMArena Spanish1499—

Instruction Following Not comparable

DeepSeek V4.1 Flash: 77.6 (#24), Qwen2.5 32B Instruct: —

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
LMArena Instruction Following1475—

Long Context Not comparable

DeepSeek V4.1 Flash: 45.2 (#46), Qwen2.5 32B Instruct: —

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
LMArena Longer Query1476—

Writing & Preference Not comparable

DeepSeek V4.1 Flash: 65.8 (#43), Qwen2.5 32B Instruct: —

BenchmarkDeepSeek V4.1 FlashQwen2.5 32B Instruct
LMArena Text1465—
LMArena Creative Writing1436—
EQ-Bench Creative Writing1540—
LMArena Multi-Turn1460—

Frequently asked questions

Is DeepSeek V4.1 Flash better than Qwen2.5 32B Instruct?

DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 29.7 on the Noometry Index.

Which is cheaper, DeepSeek V4.1 Flash or Qwen2.5 32B Instruct?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen2.5 32B Instruct lists at $0.70 and $2.80.

Is DeepSeek V4.1 Flash or Qwen2.5 32B Instruct better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.8 versus 38.1 in the Noometry coding category.

Which has the bigger context window?

DeepSeek V4.1 Flash does, with 1M tokens against 131K.

How many benchmarks do DeepSeek V4.1 Flash and Qwen2.5 32B Instruct share?

1 benchmark has published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Qwen2.5 32B Instruct has 7.

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