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DeepSeek R1 Distill Qwen 14B vs Qwen3 VL 235B A22B Thinking

Comparing DeepSeek R1 Distill Qwen 14B and Qwen3 VL 235B A22B Thinking across benchmarks, pricing, and capabilities.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek R1 Distill Qwen 14B and Qwen3 VL 235B A22B Thinking trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek R1 Distill Qwen 14B

  • you are already invested in the DeepSeek ecosystem

Choose Qwen3 VL 235B A22B Thinking

  • you want the most recent training data — it shipped Sep 2025

At a glance

The differences that matter most.

Benchmark wins
Input price
— / M
$0.45 / M
Output price
— / M
$3.49 / M
Context window
262,144
Released
Jan 2025
Sep 2025
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 14B and Qwen3 VL 235B A22B Thinkingdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

221.2B diff

Qwen3 VL 235B A22B Thinking has 221.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 1494.6% larger.

DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
14.8B
DeepSeek R1 Distill Qwen 14B
236.0B
Qwen3 VL 235B A22B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 235B A22B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Thinking specifies output context (262,144 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Tue Aug 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 14B does not.

Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Qwen 14B

Text
Images
Audio
Video

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 14B is licensed under MIT, while Qwen3 VL 235B A22B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek R1 Distill Qwen 14B

MIT

Open weights

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 8 months newer than DeepSeek R1 Distill Qwen 14B.

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.6 years ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

11 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Qwen 14B and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 14B
✓ Preferred
Qwen3 VL 235B A22B Thinking
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B vs Qwen3 VL 235B A22B Thinking.

Which is better, DeepSeek R1 Distill Qwen 14B or Qwen3 VL 235B A22B Thinking?

DeepSeek R1 Distill Qwen 14B (DeepSeek) and Qwen3 VL 235B A22B 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 Distill Qwen 14B compare to Qwen3 VL 235B A22B Thinking in benchmarks?

DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%. Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.

What are the context window sizes for DeepSeek R1 Distill Qwen 14B and Qwen3 VL 235B A22B Thinking?

DeepSeek R1 Distill Qwen 14B supports an unknown number of tokens and Qwen3 VL 235B A22B 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 Distill Qwen 14B and Qwen3 VL 235B A22B Thinking?

Key differences include 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 Distill Qwen 14B and Qwen3 VL 235B A22B Thinking?

DeepSeek R1 Distill Qwen 14B is developed by DeepSeek and Qwen3 VL 235B A22B Thinking is developed by Alibaba Cloud / Qwen Team.