Model Comparison

DeepSeek-V3 vs Llama 3.1 70B InstructWhich is better in 2026?

DeepSeek-V3 significantly outperforms across most benchmarks. Llama 3.1 70B Instruct is 2.4x cheaper per token.

Verdict: DeepSeek-V3 vs Llama 3.1 70B Instruct — which is better?

DeepSeek-V3 (by DeepSeek) and Llama 3.1 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-V3 outperforms in 4 benchmarks (DROP, GPQA, MMLU, MMLU-Pro), while Llama 3.1 70B Instruct is better at 1 benchmark (IFEval). DeepSeek-V3 significantly outperforms across most benchmarks.

On price, Llama 3.1 70B Instruct is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V3 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-V3 if…

  • you want the strongest raw capability — it leads on 4 of 5 shared benchmarks
  • you process long inputs — it offers a 131,072 token context window
  • you want the most recent training data — it shipped Dec 2024

Choose Llama 3.1 70B Instruct if…

  • cost matters — it's about 2.4x cheaper per token
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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek-V3 outperforms in 4 benchmarks (DROP, GPQA, MMLU, MMLU-Pro), while Llama 3.1 70B Instruct is better at 1 benchmark (IFEval).

DeepSeek-V3 significantly outperforms across most benchmarks.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.1 70B Instruct costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 1.4x more expensive than Llama 3.1 70B Instruct ($0.20/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 5.5x more expensive than Llama 3.1 70B Instruct ($0.20/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Llama 3.1 70B Instruct.*

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

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Meta
Llama 3.1 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

601.0B diff

DeepSeek-V3 has 601.0B more parameters than Llama 3.1 70B Instruct, making it 858.6% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Meta
Llama 3.1 70B Instruct
70.0Bparameters
671.0B
DeepSeek-V3
70.0B
Llama 3.1 70B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Llama 3.1 70B Instruct's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Llama 3.1 70B Instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Meta
Llama 3.1 70B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Jun 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Llama 3.1 70B Instruct uses Llama 3.1 Community License.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Llama 3.1 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Llama 3.1 70B Instruct was released on 2024-07-23.

DeepSeek-V3 is 5 months newer than Llama 3.1 70B Instruct.

DeepSeek-V3

Dec 25, 2024

1.5 years ago

5mo newer
Llama 3.1 70B Instruct

Jul 23, 2024

1.9 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-V3 is available from DeepSeek. Llama 3.1 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Cerebras, Together, Fireworks, Bedrock, Sambanova.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Llama 3.1 70B Instruct

lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
groq logo
Groq
Input Price:Input: $0.59/1MOutput Price:Output: $0.78/1M
cerebras logo
Cerebras
Input Price:Input: $0.60/1MOutput Price:Output: $0.60/1M
together logo
Together
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
sambanova logo
Sambanova
Input Price:Input: $5.00/1MOutput Price:Output: $10.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher DROP score (91.6% vs 79.6%)
Higher GPQA score (59.1% vs 41.7%)
Higher MMLU score (88.5% vs 83.6%)
Higher MMLU-Pro score (75.9% vs 66.4%)
Meta
Less expensive input tokens
Less expensive output tokens
Higher IFEval score (87.5% vs 86.1%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Meta
Llama 3.1 70B Instruct

FAQ

Common questions about DeepSeek-V3 vs Llama 3.1 70B Instruct.

Which is better, DeepSeek-V3 or Llama 3.1 70B Instruct?

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Llama 3.1 70B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3 compare to Llama 3.1 70B Instruct in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Llama 3.1 70B Instruct scores GSM-8K (CoT): 95.1%, ARC-C: 94.8%, API-Bank: 90.0%, IFEval: 87.5%, Multilingual MGSM (CoT): 86.9%.

Is DeepSeek-V3 cheaper than Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct is 1.4x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Llama 3.1 70B Instruct costs $0.20/M input and $0.20/M output via lambda.

What are the context window sizes for DeepSeek-V3 and Llama 3.1 70B Instruct?

DeepSeek-V3 supports 131K tokens and Llama 3.1 70B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3 and Llama 3.1 70B Instruct?

Key differences include context window (131K vs 128K), input pricing ($0.27 vs $0.20/M), licensing (MIT + Model License (Commercial use allowed) vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Llama 3.1 70B Instruct?

DeepSeek-V3 is developed by DeepSeek and Llama 3.1 70B Instruct is developed by Meta.

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