Model Comparison

DeepSeek-R1-0528 vs Mistral NeMo Instruct

Comparing DeepSeek-R1-0528 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-R1-0528 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

Mistral NeMo Instruct costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 3.3x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 14.3x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

In conclusion, DeepSeek-R1-0528 is more expensive than Mistral NeMo Instruct.*

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

Lowest available price from all providers
Sat May 09 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
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

659.0B diff

DeepSeek-R1-0528 has 659.0B more parameters than Mistral NeMo Instruct, making it 5491.7% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
671.0B
DeepSeek-R1-0528
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

DeepSeek-R1-0528 accepts 131,072 input tokens compared to Mistral NeMo Instruct's 128,000 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while Mistral NeMo Instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Sat May 09 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 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-R1-0528

MIT

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Mistral NeMo Instruct was released on 2024-07-18.

DeepSeek-R1-0528 is 10 months newer than Mistral NeMo Instruct.

DeepSeek-R1-0528

May 28, 2025

11 months ago

10mo newer
Mistral NeMo Instruct

Jul 18, 2024

1.8 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-R1-0528 is available from DeepInfra, DeepSeek, Novita. Mistral NeMo Instruct is available from Google, Mistral AI.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

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
Larger context window (131,072 tokens)
Mistral AI
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Mistral NeMo Instruct.

Which is better, DeepSeek-R1-0528 or Mistral NeMo Instruct?

DeepSeek-R1-0528 (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.

How does DeepSeek-R1-0528 compare to Mistral NeMo Instruct in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.

Is DeepSeek-R1-0528 cheaper than Mistral NeMo Instruct?

Mistral NeMo Instruct is 3.3x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. Mistral NeMo Instruct costs $0.15/M input and $0.15/M output via google.

What are the context window sizes for DeepSeek-R1-0528 and Mistral NeMo Instruct?

DeepSeek-R1-0528 supports 131K tokens and Mistral NeMo Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-R1-0528 and Mistral NeMo Instruct?

Key differences include context window (131K vs 128K), input pricing ($0.50 vs $0.15/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1-0528 and Mistral NeMo Instruct?

DeepSeek-R1-0528 is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.