Model comparison

DeepSeek-V3.2-Exp vs Step 3.5 Flash

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.9 to 41.7 on the Noometry Index. Step 3.5 Flash costs 1.9× less per token, which makes it the better buy when DeepSeek-V3.2-Exp's lead doesn't matter for your workload.

Last verified . 19 shared benchmarks.

DeepSeek-V3.2-Exp DeepSeek

44.9

Rank #68 Confirmed

Step 3.5 Flash StepFun

41.7

Rank #116 Confirmed

Summary

  • They share 19 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 8 categories and Step 3.5 Flash in 0 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where DeepSeek-V3.2-Exp leads 51.6 to 39.0.
  • The biggest single-benchmark swing is MathArena Final-Answer Competitions: 57.7% for DeepSeek-V3.2-Exp and 66.8% for Step 3.5 Flash.
  • Step 3.5 Flash is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.26 / $0.38 for DeepSeek-V3.2-Exp.
  • Step 3.5 Flash accepts more context: 256K tokens versus 164K.

Side by side

DeepSeek-V3.2-Exp and Step 3.5 Flash specifications
DeepSeek-V3.2-ExpStep 3.5 Flash
ProviderDeepSeekStepFun
Noometry Index44.941.7
Released2025-09-292026-01-29
WeightsOpenOpen
Context window164K256K
Max output66K256K
Input $ / M tokens$0.26$0.10
Output $ / M tokens$0.38$0.30
Results tracked4819

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 46.4 (#61), Step 3.5 Flash: 41.7 (#106)

Coding benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
LMArena Coding14541436
SWE-bench Verified (bash only)70%—
Aider Polyglot74.2%—
LMArena WebDev1362—
SWE-bench Multilingual59%—
SciCode38.9%—
WeirdML39.5%—

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Exp: 37.9 (#31), Step 3.5 Flash: —

Agentic & Tool Use benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
Terminal-Bench39.6%—
Berkeley Function Calling Leaderboard56.7%—
TheAgentCompany42.9%—
Vending-Bench 21,034—

Reasoning Too close to call

DeepSeek-V3.2-Exp: 22.0 (#185), Step 3.5 Flash: 21.2 (#202)

Reasoning benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
NYT Connections (extended)36.7%28.4%
LMArena Hard Prompts14331411
ARC-AGI-24%—
Kagi LLM Benchmark52.2%—
ARC-AGI-157%—
CritPt2.9%—
Chess Puzzles14%—
Thematic Generalization65%—
DTBench87.7%—
LMCA29.1%—
Epoch Capabilities Index146.28—

Math Too close to call

DeepSeek-V3.2-Exp: 40.8 (#75), Step 3.5 Flash: 40.6 (#77)

Math benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
MathArena Final-Answer Competitions57.7%66.8%
LMArena Math14351408
OTIS Mock AIME 2024-202587.8%—
ProofBench8%—
FrontierMath (Feb 2025 set)22.1%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 51.6 (#61), Step 3.5 Flash: 39.0 (#127)

Knowledge benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
LMArena Expert14361422
GPQA Diamond83.4%—
Vectara Hallucination Rate5.3%—

Multilingual DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 52.4 (#85), Step 3.5 Flash: 50.7 (#115)

Multilingual benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
LMArena Non-English14091386
LMArena Chinese14611448
LMArena French14351421
LMArena German14401404
LMArena Japanese13771353
LMArena Korean13721350
LMArena Russian14231385
LMArena Spanish14411419

Instruction Following DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 74.7 (#89), Step 3.5 Flash: 73.3 (#119)

Instruction Following benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
LMArena Instruction Following14131385

Long Context DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 47.6 (#15), Step 3.5 Flash: 42.8 (#112)

Long Context benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
LMArena Longer Query14281402
Fiction.LiveBench83.3%—
CL-bench13.2%—
CL-bench Life9.5%—

Writing & Preference DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 62.5 (#73), Step 3.5 Flash: 59.0 (#108)

Writing & Preference benchmarks
BenchmarkDeepSeek-V3.2-ExpStep 3.5 Flash
LMArena Text14251403
LMArena Creative Writing14031357
LMArena Multi-Turn14271405
EQ-Bench Creative Writing1515—

Frequently asked questions

Is DeepSeek-V3.2-Exp better than Step 3.5 Flash?

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.9 to 41.7 on the Noometry Index. Step 3.5 Flash costs 1.9× less per token, which makes it the better buy when DeepSeek-V3.2-Exp's lead doesn't matter for your workload.

Which is cheaper, DeepSeek-V3.2-Exp or Step 3.5 Flash?

Step 3.5 Flash is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; DeepSeek-V3.2-Exp lists at $0.26 and $0.38.

Is DeepSeek-V3.2-Exp or Step 3.5 Flash better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.4 versus 41.7 in the Noometry coding category.

Which has the bigger context window?

Step 3.5 Flash does, with 256K tokens against 164K.

How many benchmarks do DeepSeek-V3.2-Exp and Step 3.5 Flash share?

19 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 48 scored results on Noometry and Step 3.5 Flash has 19.

Related comparisons

Go deeper