Model Comparison

DeepSeek-V2.5 vs Mistral Large 2

Both models are evenly matched across the benchmarks. DeepSeek-V2.5 is 17.1x cheaper per token.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V2.5 outperforms in 2 benchmarks (GSM8k, MT-Bench), while Mistral Large 2 is better at 2 benchmarks (HumanEval, MMLU).

Both models are evenly matched across the benchmarks.

Mon Mar 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V2.5 costs less

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 14.3x cheaper than Mistral Large 2 ($2.00/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 21.4x cheaper than Mistral Large 2 ($6.00/1M tokens).

In conclusion, Mistral Large 2 is more expensive than DeepSeek-V2.5.*

* 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-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Mistral AI
Mistral Large 2
Input tokens$2.00
Output tokens$6.00
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

113.0B diff

DeepSeek-V2.5 has 113.0B more parameters than Mistral Large 2, making it 91.9% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Mistral AI
Mistral Large 2
123.0Bparameters
236.0B
DeepSeek-V2.5
123.0B
Mistral Large 2

Context Window

Maximum input and output token capacity

Mistral Large 2 accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Mistral Large 2 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 Large 2
Input128,000 tokens
Output128,000 tokens
Mon Mar 30 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Mistral Large 2 uses Mistral Research License.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V2.5

deepseek

Open weights

Mistral Large 2

Mistral Research License

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Mistral Large 2 was released on 2024-07-24.

Mistral Large 2 is 3 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

1.9 years ago

Mistral Large 2

Jul 24, 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 Large 2 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 Large 2

google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Higher GSM8k score (95.1% vs 93.0%)
Higher MT-Bench score (90.2% vs 86.3%)
Mistral AI
Larger context window (128,000 tokens)
Higher HumanEval score (92.0% vs 89.0%)
Higher MMLU score (84.0% vs 80.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Mistral AI
Mistral Large 2

FAQ

Common questions about DeepSeek-V2.5 vs Mistral Large 2

Both models are evenly matched across the benchmarks. DeepSeek-V2.5 is made by DeepSeek and Mistral Large 2 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 Large 2 scores GSM8k: 93.0%, HumanEval: 92.0%, MT-Bench: 86.3%, MMLU: 84.0%, MMLU French: 82.8%.
DeepSeek-V2.5 is 14.3x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. Mistral Large 2 costs $2.00/M input and $6.00/M output via google.
DeepSeek-V2.5 supports 8K tokens and Mistral Large 2 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 $2.00/M), licensing (deepseek vs Mistral Research License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Mistral Large 2 is developed by Mistral AI.