Model Comparison

DeepSeek-V3.1 vs Llama 3.1 8B Instruct

DeepSeek-V3.1 significantly outperforms across most benchmarks. Llama 3.1 8B Instruct is 15.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.1 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Llama 3.1 8B Instruct is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Fri May 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.1 8B Instruct costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 9.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 33.3x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

In conclusion, DeepSeek-V3.1 is more expensive than Llama 3.1 8B Instruct.*

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

Lowest available price from all providers

Fri May 08 2026 • llm-stats.com

DeepSeek-V3.1

Input tokens$0.27

Output tokens$1.00

Best providerDeepinfra

Llama 3.1 8B Instruct

Input tokens$0.03

Output tokens$0.03

Best providerLambda

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

663.0B diff

DeepSeek-V3.1 has 663.0B more parameters than Llama 3.1 8B Instruct, making it 8287.5% larger.

DeepSeek-V3.1

671.0Bparameters

Llama 3.1 8B Instruct

8.0Bparameters

671.0B

DeepSeek-V3.1

8.0B

Llama 3.1 8B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3.1 accepts 163,840 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Llama 3.1 8B Instruct is limited to 131,072 tokens.

DeepSeek-V3.1

Input163,840 tokens

Output163,840 tokens

Llama 3.1 8B Instruct

Input131,072 tokens

Output131,072 tokens

Fri May 08 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Llama 3.1 8B Instruct uses Llama 3.1 Community License.

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

DeepSeek-V3.1

MIT

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Llama 3.1 8B Instruct was released on 2024-07-23.

DeepSeek-V3.1 is 6 months newer than Llama 3.1 8B Instruct.

DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

5mo newer

Llama 3.1 8B Instruct

Jul 23, 2024

1.8 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek-V3.1's cutoff date is not specified.

We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-V3.1's cutoff date.

DeepSeek-V3.1

—

Llama 3.1 8B Instruct

Dec 2023

Provider Availability

DeepSeek-V3.1 is available from DeepInfra, Novita. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.

DeepSeek-V3.1

Deepinfra

Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Novita

Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Llama 3.1 8B Instruct

Lambda

Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M

Deepinfra

Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M

Groq

Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M

Sambanova

Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M

Cerebras

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Hyperbolic

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Together

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

Fireworks

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

AWS Bedrock

Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek-V3.1

View details

DeepSeek

Larger context window (163,840 tokens)

Higher GPQA score (74.9% vs 30.4%)

Higher MMLU-Pro score (83.7% vs 48.3%)

Llama 3.1 8B Instruct

View details

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-V3.1	Llama 3.1 8B Instruct

FAQ

Common questions about DeepSeek-V3.1 vs Llama 3.1 8B Instruct.

Which is better, DeepSeek-V3.1 or Llama 3.1 8B Instruct?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 is made by DeepSeek and Llama 3.1 8B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.1 compare to Llama 3.1 8B Instruct in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Llama 3.1 8B Instruct scores GSM-8K (CoT): 84.5%, ARC-C: 83.4%, API-Bank: 82.6%, IFEval: 80.4%, BFCL: 76.1%.

Is DeepSeek-V3.1 cheaper than Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct is 9.0x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output via lambda.

What are the context window sizes for DeepSeek-V3.1 and Llama 3.1 8B Instruct?

DeepSeek-V3.1 supports 164K tokens and Llama 3.1 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.1 and Llama 3.1 8B Instruct?

Key differences include context window (164K vs 131K), input pricing ($0.27 vs $0.03/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.1 and Llama 3.1 8B Instruct?

DeepSeek-V3.1 is developed by DeepSeek and Llama 3.1 8B Instruct is developed by Meta.