Model Comparison

DeepSeek-V3.2-Exp vs Step-3.5-Flash

Step-3.5-Flash significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3.2-Exp outperforms in 0 benchmarks, while Step-3.5-Flash is better at 3 benchmarks (AIME 2025, BrowseComp, SWE-Bench Verified).

Step-3.5-Flash significantly outperforms across most benchmarks.

Mon Apr 27 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Mon Apr 27 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
StepFun
Step-3.5-Flash
Input tokens$0.10
Output tokens$0.40
Best providerStepFun
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

489.0B diff

DeepSeek-V3.2-Exp has 489.0B more parameters than Step-3.5-Flash, making it 249.5% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
StepFun
Step-3.5-Flash
196.0Bparameters
685.0B
DeepSeek-V3.2-Exp
196.0B
Step-3.5-Flash

Context Window

Maximum input and output token capacity

Only Step-3.5-Flash specifies input context (65,536 tokens). Only Step-3.5-Flash specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input- tokens
Output- tokens
StepFun
Step-3.5-Flash
Input65,536 tokens
Output8,192 tokens
Mon Apr 27 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while Step-3.5-Flash uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2-Exp

MIT

Open weights

Step-3.5-Flash

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Step-3.5-Flash was released on 2026-02-02.

Step-3.5-Flash is 4 months newer than DeepSeek-V3.2-Exp.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

Step-3.5-Flash

Feb 2, 2026

2 months ago

4mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
StepFun
Larger context window (65,536 tokens)
Higher AIME 2025 score (97.3% vs 89.3%)
Higher BrowseComp score (69.0% vs 40.1%)
Higher SWE-Bench Verified score (74.4% vs 67.8%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
StepFun
Step-3.5-Flash

FAQ

Common questions about DeepSeek-V3.2-Exp vs Step-3.5-Flash

Step-3.5-Flash significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Step-3.5-Flash is made by StepFun. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Step-3.5-Flash scores AIME 2025: 97.3%, Tau-bench: 88.2%, LiveCodeBench v6: 86.4%, IMO-AnswerBench: 85.4%, SWE-Bench Verified: 74.4%.
DeepSeek-V3.2-Exp supports an unknown number of tokens and Step-3.5-Flash supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Step-3.5-Flash is developed by StepFun.