Model Comparison

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

Step-3.5-Flash significantly outperforms across most benchmarks.

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
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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

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.