Model Comparison
DeepSeek-V2.5 vs Llama 3.3 70B InstructWhich is better in 2026?
Llama 3.3 70B Instruct shows notably better performance in the majority of benchmarks. DeepSeek-V2.5 is 1.1x cheaper per token.
Verdict: DeepSeek-V2.5 vs Llama 3.3 70B Instruct — which is better?
DeepSeek-V2.5 (by DeepSeek) and Llama 3.3 70B Instruct (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V2.5 outperforms in 1 benchmarks (HumanEval), while Llama 3.3 70B Instruct is better at 2 benchmarks (MATH, MMLU). Llama 3.3 70B Instruct shows notably better performance in the majority of benchmarks.
On price, DeepSeek-V2.5 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 3.3 70B Instruct also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V2.5 if…
- cost matters — it's about 1.1x cheaper per token
Choose Llama 3.3 70B Instruct if…
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Dec 2024
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 1 benchmarks (HumanEval), while Llama 3.3 70B Instruct is better at 2 benchmarks (MATH, MMLU).
Llama 3.3 70B Instruct shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.4x cheaper than Llama 3.3 70B Instruct ($0.20/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.4x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).
In conclusion, Llama 3.3 70B Instruct is more expensive than DeepSeek-V2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V2.5 has 166.0B more parameters than Llama 3.3 70B Instruct, making it 237.1% larger.
Context Window
Maximum input and output token capacity
Llama 3.3 70B Instruct accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Llama 3.3 70B Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Llama 3.3 Community License Agreement
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Llama 3.3 70B Instruct was released on 2024-12-06.
Llama 3.3 70B Instruct is 7 months newer than DeepSeek-V2.5.
May 8, 2024
2.1 years ago
Dec 6, 2024
1.5 years ago
7mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.
DeepSeek-V2.5
Llama 3.3 70B Instruct
Outputs Comparison
Key Takeaways
DeepSeek-V2.5
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about DeepSeek-V2.5 vs Llama 3.3 70B Instruct.