Model Comparison

DeepSeek-R1 vs Step-3.5-Flash

Comparing DeepSeek-R1 and Step-3.5-Flash across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Step-3.5-Flash don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Step-3.5-Flash costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 5.5x more expensive than Step-3.5-Flash ($0.10/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 5.5x more expensive than Step-3.5-Flash ($0.40/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than Step-3.5-Flash.*

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

Lowest available price from all providers
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
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-R1 has 475.0B more parameters than Step-3.5-Flash, making it 242.3% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
StepFun
Step-3.5-Flash
196.0Bparameters
671.0B
DeepSeek-R1
196.0B
Step-3.5-Flash

Context Window

Maximum input and output token capacity

DeepSeek-R1 accepts 131,072 input tokens compared to Step-3.5-Flash's 65,536 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Step-3.5-Flash is limited to 8,192 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
StepFun
Step-3.5-Flash
Input65,536 tokens
Output8,192 tokens
Fri Apr 17 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 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-R1

MIT

Open weights

Step-3.5-Flash

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Step-3.5-Flash was released on 2026-02-02.

Step-3.5-Flash is 13 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

Step-3.5-Flash

Feb 2, 2026

2 months ago

1.0yr 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-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Step-3.5-Flash is available from StepFun.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
StepFun
Step-3.5-Flash

FAQ

Common questions about DeepSeek-R1 vs Step-3.5-Flash

DeepSeek-R1 (DeepSeek) and Step-3.5-Flash (StepFun) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
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 5.5x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Step-3.5-Flash costs $0.10/M input and $0.40/M output via stepfun.
DeepSeek-R1 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 ($0.55 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1 is developed by DeepSeek and Step-3.5-Flash is developed by StepFun.