Model Comparison

DeepSeek-V3 vs Step-3.5-Flash

Step-3.5-Flash significantly outperforms across most benchmarks. Step-3.5-Flash is 2.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while Step-3.5-Flash is better at 1 benchmark (SWE-Bench Verified).

Step-3.5-Flash significantly outperforms across most benchmarks.

Tue Apr 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Step-3.5-Flash costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 2.7x more expensive than Step-3.5-Flash ($0.10/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 2.8x more expensive than Step-3.5-Flash ($0.40/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Step-3.5-Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
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

475.0B diff

DeepSeek-V3 has 475.0B more parameters than Step-3.5-Flash, making it 242.3% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
StepFun
Step-3.5-Flash
196.0Bparameters
671.0B
DeepSeek-V3
196.0B
Step-3.5-Flash

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Step-3.5-Flash's 65,536 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Step-3.5-Flash is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
StepFun
Step-3.5-Flash
Input65,536 tokens
Output8,192 tokens
Tue Apr 21 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), 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

MIT + Model License (Commercial use allowed)

Open weights

Step-3.5-Flash

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Step-3.5-Flash was released on 2026-02-02.

Step-3.5-Flash is 13 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

Step-3.5-Flash

Feb 2, 2026

2 months ago

1.1yr 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

Provider Availability

DeepSeek-V3 is available from DeepSeek. Step-3.5-Flash is available from StepFun.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Step-3.5-Flash

stepfun logo
StepFun
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
StepFun
Less expensive input tokens
Less expensive output tokens
Higher SWE-Bench Verified score (74.4% vs 42.0%)

Detailed Comparison

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

FAQ

Common questions about DeepSeek-V3 vs Step-3.5-Flash

Step-3.5-Flash significantly outperforms across most benchmarks. DeepSeek-V3 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 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. 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%.
Step-3.5-Flash is 2.7x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Step-3.5-Flash costs $0.10/M input and $0.40/M output via stepfun.
DeepSeek-V3 supports 131K 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 context window (131K vs 66K), input pricing ($0.27 vs $0.10/M), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Step-3.5-Flash is developed by StepFun.