Model Comparison

DeepSeek-V3 vs Mistral NeMo Instruct

DeepSeek-V3 significantly outperforms across most benchmarks. Mistral NeMo Instruct is 3.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (MMLU), while Mistral NeMo Instruct is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mistral NeMo Instruct costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 1.8x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 7.3x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Mistral NeMo Instruct.*

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

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
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-V3 has 659.0B more parameters than Mistral NeMo Instruct, making it 5491.7% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
671.0B
DeepSeek-V3
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Mistral NeMo Instruct's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Mistral NeMo Instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Sat Apr 18 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), 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-V3

MIT + Model License (Commercial use allowed)

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Mistral NeMo Instruct was released on 2024-07-18.

DeepSeek-V3 is 5 months newer than Mistral NeMo Instruct.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

5mo 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-V3 is available from DeepSeek. Mistral NeMo Instruct is available from Google, Mistral AI.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher MMLU score (88.5% vs 68.0%)
Mistral AI
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about DeepSeek-V3 vs Mistral NeMo Instruct

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Mistral NeMo Instruct is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.
Mistral NeMo Instruct is 1.8x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Mistral NeMo Instruct costs $0.15/M input and $0.15/M output via google.
DeepSeek-V3 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.
Key differences include context window (131K vs 128K), input pricing ($0.27 vs $0.15/M), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.