Model Comparison

DeepSeek R1 Distill Qwen 7B vs Step-3.5-Flash

Comparing DeepSeek R1 Distill Qwen 7B and Step-3.5-Flash across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 7B 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

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 7B
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

188.4B diff

Step-3.5-Flash has 188.4B more parameters than DeepSeek R1 Distill Qwen 7B, making it 2472.2% larger.

DeepSeek
DeepSeek R1 Distill Qwen 7B
7.6Bparameters
StepFun
Step-3.5-Flash
196.0Bparameters
7.6B
DeepSeek R1 Distill Qwen 7B
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 R1 Distill Qwen 7B
Input- tokens
Output- tokens
StepFun
Step-3.5-Flash
Input65,536 tokens
Output8,192 tokens
Wed Apr 15 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 7B 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 Distill Qwen 7B

MIT

Open weights

Step-3.5-Flash

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 7B 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 Distill Qwen 7B.

DeepSeek R1 Distill Qwen 7B

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
StepFun
Larger context window (65,536 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 7B
StepFun
Step-3.5-Flash

FAQ

Common questions about DeepSeek R1 Distill Qwen 7B vs Step-3.5-Flash

DeepSeek R1 Distill Qwen 7B (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.
DeepSeek R1 Distill Qwen 7B scores MATH-500: 92.8%, AIME 2024: 83.3%, GPQA: 49.1%, LiveCodeBench: 37.6%. 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 R1 Distill Qwen 7B 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 R1 Distill Qwen 7B is developed by DeepSeek and Step-3.5-Flash is developed by StepFun.