Model comparison

DeepSeek-V3.2-Exp vs Step 3.5 Flash

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 42.3 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 October 10, 2026. 19 shared benchmarks.

DeepSeek-V3.2-Exp

DeepSeek

44.3

Rank #78 Confirmed

Step 3.5 Flash

StepFun

42.3

Rank #116 Confirmed

Summary

They share 19 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 6 categories and Step 3.5 Flash in 2 categories; 6 gaps are clear of the uncertainty.
The widest gap is in knowledge, where DeepSeek-V3.2-Exp leads 51.7 to 39.6.
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-Exp	Step 3.5 Flash
Provider	DeepSeek	StepFun
Noometry Index	44.3	42.3
Released	2025-09-29	2026-01-29
Weights	Open	Open
Context window	164K	256K
Max output	66K	256K
Input $ / M tokens	$0.26	$0.10
Output $ / M tokens	$0.38	$0.30
Results tracked	49	19

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Category by category

Coding DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 46.5 (#65), Step 3.5 Flash: 42.4 (#105)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
LMArena Coding	1454	1436
SWE-bench Verified (bash only)	70%	—
Aider Polyglot	74.2%	—
LMArena WebDev	1362	—
SWE-bench Multilingual	59%	—
SciCode	38.9%	—
WeirdML	39.5%	—

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Exp: 32.7 (#59), Step 3.5 Flash: —

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
Terminal-Bench	39.6%	—
APEX-Agents	21.3%	—
Berkeley Function Calling Leaderboard	56.7%	—
TheAgentCompany	42.9%	—
Vending-Bench 2	1,034	—

Reasoning Too close to call

DeepSeek-V3.2-Exp: 22.1 (#208), Step 3.5 Flash: 22.2 (#202)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
NYT Connections (extended)	36.7%	28.4%
LMArena Hard Prompts	1434	1411
ARC-AGI-2	4%	—
Kagi LLM Benchmark	52.2%	—
ARC-AGI-1	57%	—
CritPt	2.9%	—
Chess Puzzles	14%	—
Thematic Generalization	65%	—
DTBench	87.7%	—
LMCA	29.1%	—
Epoch Capabilities Index	146.27	—

Math Too close to call

DeepSeek-V3.2-Exp: 41.7 (#87), Step 3.5 Flash: 42.6 (#84)

Math benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
MathArena Final-Answer Competitions	57.7%	66.8%
LMArena Math	1435	1408
OTIS Mock AIME 2024-2025	87.8%	—
ProofBench	8%	—
FrontierMath (Feb 2025 set)	22.1%	—
FrontierMath Tier 4 (v1)	2.1%	—

Knowledge DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 51.7 (#66), Step 3.5 Flash: 39.6 (#132)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
LMArena Expert	1436	1421
GPQA Diamond	83.4%	—
Vectara Hallucination Rate	5.3%	—

Multilingual DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 52.2 (#90), Step 3.5 Flash: 50.5 (#119)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
LMArena Non-English	1409	1385
LMArena Chinese	1461	1447
LMArena French	1433	1421
LMArena German	1440	1405
LMArena Japanese	1374	1354
LMArena Korean	1371	1352
LMArena Russian	1424	1385
LMArena Spanish	1440	1419

Instruction Following DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 74.5 (#93), Step 3.5 Flash: 73.1 (#124)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
LMArena Instruction Following	1413	1385

Long Context DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 47.6 (#16), Step 3.5 Flash: 42.8 (#117)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
LMArena Longer Query	1428	1402
Fiction.LiveBench	83.3%	—
CL-bench	13.2%	—
CL-bench Life	9.5%	—

Writing & Preference DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 62.4 (#77), Step 3.5 Flash: 58.8 (#113)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Exp	Step 3.5 Flash
LMArena Text	1425	1403
LMArena Creative Writing	1403	1357
LMArena Multi-Turn	1427	1405
EQ-Bench Creative Writing	1515	—

Frequently asked questions

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

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: 46.5 versus 42.4 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 49 scored results on Noometry and Step 3.5 Flash has 19.