Model Comparison

DeepSeek R1 Distill Qwen 14B vs Mistral NeMo Instruct

Comparing DeepSeek R1 Distill Qwen 14B and Mistral NeMo Instruct 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 Distill Qwen 14B and Mistral NeMo Instruct 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 01 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 14B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Mistral AI
Mistral NeMo Instruct
Input tokens$0.15
Output tokens$0.15
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

2.8B diff

DeepSeek R1 Distill Qwen 14B has 2.8B more parameters than Mistral NeMo Instruct, making it 23.3% larger.

DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
14.8B
DeepSeek R1 Distill Qwen 14B
12.0B
Mistral NeMo Instruct

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).

DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Wed Apr 01 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 14B is licensed under MIT, while Mistral NeMo Instruct 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

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while Mistral NeMo Instruct was released on 2024-07-18.

DeepSeek R1 Distill Qwen 14B is 6 months newer than Mistral NeMo Instruct.

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.2 years ago

6mo newer
Mistral NeMo Instruct

Jul 18, 2024

1.7 years ago

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
Mistral AI
Larger context window (128,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 14B
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B vs Mistral NeMo Instruct

DeepSeek R1 Distill Qwen 14B (DeepSeek) and Mistral NeMo Instruct (Mistral AI) 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 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.
DeepSeek R1 Distill Qwen 14B supports an unknown number of tokens and Mistral NeMo Instruct supports 128K 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 14B is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.