Model Comparison

DeepSeek-V2.5 vs DeepSeek R1 Distill Llama 70B

Comparing DeepSeek-V2.5 and DeepSeek R1 Distill Llama 70B across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V2.5 and DeepSeek R1 Distill Llama 70B 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 R1 Distill Llama 70B costs less

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.4x more expensive than DeepSeek R1 Distill Llama 70B ($0.10/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.4x cheaper than DeepSeek R1 Distill Llama 70B ($0.40/1M tokens).

In conclusion, DeepSeek-V2.5 and DeepSeek R1 Distill Llama 70B cost the same.*

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

Lowest available price from all providers
Mon Apr 20 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
DeepSeek
DeepSeek R1 Distill Llama 70B
Input tokens$0.10
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

165.4B diff

DeepSeek-V2.5 has 165.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 234.3% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
236.0B
DeepSeek-V2.5
70.6B
DeepSeek R1 Distill Llama 70B

Context Window

Maximum input and output token capacity

DeepSeek R1 Distill Llama 70B accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. DeepSeek R1 Distill Llama 70B 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
DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Mon Apr 20 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while DeepSeek R1 Distill Llama 70B uses MIT.

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

DeepSeek-V2.5

deepseek

Open weights

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while DeepSeek R1 Distill Llama 70B was released on 2025-01-20.

DeepSeek R1 Distill Llama 70B is 9 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.2 years ago

8mo 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. DeepSeek R1 Distill Llama 70B is available from DeepInfra.

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

DeepSeek R1 Distill Llama 70B

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive output tokens
Larger context window (128,000 tokens)
Less expensive input tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
DeepSeek
DeepSeek R1 Distill Llama 70B

FAQ

Common questions about DeepSeek-V2.5 vs DeepSeek R1 Distill Llama 70B

DeepSeek-V2.5 (DeepSeek) and DeepSeek R1 Distill Llama 70B (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 R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%.
DeepSeek R1 Distill Llama 70B is 1.4x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. DeepSeek R1 Distill Llama 70B costs $0.10/M input and $0.40/M output via deepinfra.
DeepSeek-V2.5 supports 8K tokens and DeepSeek R1 Distill Llama 70B 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 $0.10/M), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.