Model Comparison

DeepSeek-R1 vs Qwen3 VL 4B Thinking

Comparing DeepSeek-R1 and Qwen3 VL 4B Thinking 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 Qwen3 VL 4B Thinking 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

Qwen3 VL 4B Thinking costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 5.5x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 2.2x more expensive than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than Qwen3 VL 4B Thinking.*

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

Lowest available price from all providers

Tue May 05 2026 • llm-stats.com

DeepSeek-R1

Input tokens$0.55

Output tokens$2.19

Best providerDeepSeek

Qwen3 VL 4B Thinking

Input tokens$0.10

Output tokens$1.00

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

667.0B diff

DeepSeek-R1 has 667.0B more parameters than Qwen3 VL 4B Thinking, making it 16675.0% larger.

DeepSeek-R1

671.0Bparameters

Qwen3 VL 4B Thinking

4.0Bparameters

671.0B

DeepSeek-R1

4.0B

Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to DeepSeek-R1's 131,072 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while DeepSeek-R1 is limited to 131,072 tokens.

DeepSeek-R1

Input131,072 tokens

Output131,072 tokens

Qwen3 VL 4B Thinking

Input262,144 tokens

Output262,144 tokens

Tue May 05 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas DeepSeek-R1 does not.

Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1

Text

Images

Audio

Video

Qwen3 VL 4B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while Qwen3 VL 4B Thinking 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

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 8 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.3 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

7 months ago

8mo 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. Qwen3 VL 4B Thinking is available from DeepInfra.

DeepSeek-R1

DeepSeek

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Deepinfra

Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M

Together

Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M

Fireworks

Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Qwen3 VL 4B Thinking

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek-R1

View details

DeepSeek

No standout differentiators in the data we have for this pair.

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Supports multimodal inputs

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-R1	Qwen3 VL 4B Thinking

FAQ

Common questions about DeepSeek-R1 vs Qwen3 VL 4B Thinking.

Which is better, DeepSeek-R1 or Qwen3 VL 4B Thinking?

DeepSeek-R1 (DeepSeek) and Qwen3 VL 4B Thinking (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-R1 compare to Qwen3 VL 4B Thinking in benchmarks?

Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Is DeepSeek-R1 cheaper than Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking is 5.5x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra.

What are the context window sizes for DeepSeek-R1 and Qwen3 VL 4B Thinking?

DeepSeek-R1 supports 131K tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-R1 and Qwen3 VL 4B Thinking?

Key differences include context window (131K vs 262K), input pricing ($0.55 vs $0.10/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1 and Qwen3 VL 4B Thinking?

DeepSeek-R1 is developed by DeepSeek and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.