Model Comparison

Mistral NeMo Instruct vs Qwen2.5-Omni-7B

Comparing Mistral NeMo Instruct and Qwen2.5-Omni-7B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Mistral NeMo Instruct and Qwen2.5-Omni-7B 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
Tue Apr 14 2026 • llm-stats.com
Mistral AI
Mistral NeMo Instruct
Input tokens$0.15
Output tokens$0.15
Best providerGoogle
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

5.0B diff

Mistral NeMo Instruct has 5.0B more parameters than Qwen2.5-Omni-7B, making it 71.4% larger.

Mistral AI
Mistral NeMo Instruct
12.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
12.0B
Mistral NeMo Instruct
7.0B
Qwen2.5-Omni-7B

Context Window

Maximum input and output token capacity

Only Mistral NeMo Instruct specifies input context (128,000 tokens). Only Mistral NeMo Instruct specifies output context (128,000 tokens).

Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5-Omni-7B supports multimodal inputs, whereas Mistral NeMo Instruct does not.

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

Mistral NeMo Instruct

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Mistral NeMo Instruct

Apache 2.0

Open weights

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mistral NeMo Instruct was released on 2024-07-18, while Qwen2.5-Omni-7B was released on 2025-03-27.

Qwen2.5-Omni-7B is 8 months newer than Mistral NeMo Instruct.

Mistral NeMo Instruct

Jul 18, 2024

1.7 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.0 years 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

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Key Takeaways

Mistral AI
Larger context window (128,000 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5-Omni-7B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Mistral NeMo Instruct
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B

FAQ

Common questions about Mistral NeMo Instruct vs Qwen2.5-Omni-7B

Mistral NeMo Instruct (Mistral AI) 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.
Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%. Qwen2.5-Omni-7B scores DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%, ChartQA: 85.3%.
Mistral NeMo Instruct supports 128K 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.
Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.
Mistral NeMo Instruct is developed by Mistral AI and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.