Model Comparison

DeepSeek R1 Distill Qwen 32B vs Mistral NeMo Instruct

Comparing DeepSeek R1 Distill Qwen 32B and Mistral NeMo Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 32B 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

DeepSeek R1 Distill Qwen 32B costs less

For input processing, DeepSeek R1 Distill Qwen 32B ($0.12/1M tokens) is 1.3x cheaper than Mistral NeMo Instruct ($0.15/1M tokens).

For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 1.2x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

In conclusion, Mistral NeMo Instruct is more expensive than DeepSeek R1 Distill Qwen 32B.*

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

Lowest available price from all providers
Mon Mar 30 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 32B
Input tokens$0.12
Output tokens$0.18
Best providerDeepinfra
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

20.8B diff

DeepSeek R1 Distill Qwen 32B has 20.8B more parameters than Mistral NeMo Instruct, making it 173.3% larger.

DeepSeek
DeepSeek R1 Distill Qwen 32B
32.8Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
32.8B
DeepSeek R1 Distill Qwen 32B
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.

DeepSeek
DeepSeek R1 Distill Qwen 32B
Input128,000 tokens
Output128,000 tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Mon Mar 30 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 32B 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 32B

MIT

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while Mistral NeMo Instruct was released on 2024-07-18.

DeepSeek R1 Distill Qwen 32B is 6 months newer than Mistral NeMo Instruct.

DeepSeek R1 Distill Qwen 32B

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

Provider Availability

DeepSeek R1 Distill Qwen 32B is available from DeepInfra. Mistral NeMo Instruct is available from Google, Mistral AI.

DeepSeek R1 Distill Qwen 32B

deepinfra logo
Deepinfra
Input Price:Input: $0.12/1MOutput Price:Output: $0.18/1M

Mistral NeMo Instruct

google logo
Google
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
mistral logo
Mistral
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Mistral AI
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 32B
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about DeepSeek R1 Distill Qwen 32B vs Mistral NeMo Instruct

DeepSeek R1 Distill Qwen 32B (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 32B scores MATH-500: 94.3%, AIME 2024: 83.3%, GPQA: 62.1%, LiveCodeBench: 57.2%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.
DeepSeek R1 Distill Qwen 32B is 1.3x cheaper for input tokens. DeepSeek R1 Distill Qwen 32B costs $0.12/M input and $0.18/M output via deepinfra. Mistral NeMo Instruct costs $0.15/M input and $0.15/M output via google.
DeepSeek R1 Distill Qwen 32B supports 128K 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 input pricing ($0.12 vs $0.15/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Qwen 32B is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.