Model Comparison

DeepSeek-V2.5 vs Mistral NeMo Instruct

DeepSeek-V2.5 significantly outperforms across most benchmarks. Mistral NeMo Instruct is 1.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V2.5 outperforms in 1 benchmarks (MMLU), while Mistral NeMo Instruct is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Mon Apr 13 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-V2.5 ($0.14/1M tokens) is 1.1x cheaper than Mistral NeMo Instruct ($0.15/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.9x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

In conclusion, DeepSeek-V2.5 is more expensive than Mistral NeMo Instruct.*

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

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
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

224.0B diff

DeepSeek-V2.5 has 224.0B more parameters than Mistral NeMo Instruct, making it 1866.7% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
236.0B
DeepSeek-V2.5
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

Mistral NeMo Instruct accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Mistral NeMo Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Mon Apr 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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-V2.5

deepseek

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Mistral NeMo Instruct was released on 2024-07-18.

Mistral NeMo Instruct is 2 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

1.9 years ago

Mistral NeMo Instruct

Jul 18, 2024

1.7 years ago

2mo 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

Provider Availability

DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Mistral NeMo Instruct is available from Google, Mistral AI.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

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
Higher MMLU score (80.4% vs 68.0%)
Mistral AI
Larger context window (128,000 tokens)
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about DeepSeek-V2.5 vs Mistral NeMo Instruct

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 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-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.
DeepSeek-V2.5 is 1.1x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. Mistral NeMo Instruct costs $0.15/M input and $0.15/M output via google.
DeepSeek-V2.5 supports 8K 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 (8K vs 128K), input pricing ($0.14 vs $0.15/M), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.