Model Comparison

DeepSeek-R1 vs DeepSeek-V2.5

Comparing DeepSeek-R1 and DeepSeek-V2.5 across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and DeepSeek-V2.5 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-V2.5 costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 3.9x more expensive than DeepSeek-V2.5 ($0.14/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 7.8x more expensive than DeepSeek-V2.5 ($0.28/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than DeepSeek-V2.5.*

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

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

435.0B diff

DeepSeek-R1 has 435.0B more parameters than DeepSeek-V2.5, making it 184.3% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
671.0B
DeepSeek-R1
236.0B
DeepSeek-V2.5

Context Window

Maximum input and output token capacity

DeepSeek-R1 accepts 131,072 input tokens compared to DeepSeek-V2.5's 8,192 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Tue Apr 21 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while DeepSeek-V2.5 uses deepseek.

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

DeepSeek-R1

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while DeepSeek-V2.5 was released on 2024-05-08.

DeepSeek-R1 is 9 months newer than DeepSeek-V2.5.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

8mo newer
DeepSeek-V2.5

May 8, 2024

2.0 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 is available from DeepSeek, DeepInfra, Together, Fireworks. DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

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
* 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)
DeepSeek
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about DeepSeek-R1 vs DeepSeek-V2.5

DeepSeek-R1 (DeepSeek) and DeepSeek-V2.5 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%.
DeepSeek-V2.5 is 3.9x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek.
DeepSeek-R1 supports 131K tokens and DeepSeek-V2.5 supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 8K), input pricing ($0.55 vs $0.14/M), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.