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DeepSeek-R1 vs Qwen2.5-Omni-7B

Comparing DeepSeek-R1 and Qwen2.5-Omni-7B across benchmarks, pricing, and capabilities.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-R1 and Qwen2.5-Omni-7B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-R1

  • you want predictable pricing at $0.55/M input and $2.19/M output

Choose Qwen2.5-Omni-7B

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

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.55 / M
— / M
Output price
$2.19 / M
— / M
Context window
131,072

Individual benchmarks

0 reported for DeepSeek-R1 · 45 for Qwen2.5-Omni-7B

No common benchmarks found

DeepSeek-R1 and Qwen2.5-Omni-7Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

664.0B diff

DeepSeek-R1 has 664.0B more parameters than Qwen2.5-Omni-7B, making it 9485.7% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
671.0B
DeepSeek-R1
7.0B
Qwen2.5-Omni-7B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input- tokens
Output- tokens
Mon Sep 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen2.5-Omni-7B supports multimodal inputs, whereas DeepSeek-R1 does not.

Qwen2.5-Omni-7B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while Qwen2.5-Omni-7B 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

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Qwen2.5-Omni-7B was released on 2025-03-27.

Qwen2.5-Omni-7B is 2 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.6 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.5 years ago

2mo 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 and Qwen2.5-Omni-7B side-by-side, then vote on the output you prefer.

DeepSeek-R1
✓ Preferred
Qwen2.5-Omni-7B
Open in Playground

FAQ

Common questions about DeepSeek-R1 vs Qwen2.5-Omni-7B.

Which is better, DeepSeek-R1 or Qwen2.5-Omni-7B?

DeepSeek-R1 (DeepSeek) and Qwen2.5-Omni-7B (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 Qwen2.5-Omni-7B in benchmarks?

Qwen2.5-Omni-7B scores FLEURS: 95.9%, DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%.

What are the context window sizes for DeepSeek-R1 and Qwen2.5-Omni-7B?

DeepSeek-R1 supports 131K tokens and Qwen2.5-Omni-7B supports an unknown number of 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 Qwen2.5-Omni-7B?

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 and Qwen2.5-Omni-7B?

DeepSeek-R1 is developed by DeepSeek and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.