Llama 3.1 8B Instruct vs Nova Pro Comparison

Comparing Llama 3.1 8B Instruct and Nova Pro across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Llama 3.1 8B Instruct outperforms in 1 benchmarks (BFCL), while Nova Pro is better at 6 benchmarks (ARC-C, DROP, GPQA, HumanEval, IFEval, MMLU).

Nova Pro significantly outperforms across most benchmarks.

Sat Mar 14 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, Llama 3.1 8B Instruct ($0.03/1M tokens) is 26.7x cheaper than Nova Pro ($0.80/1M tokens).

For output processing, Llama 3.1 8B Instruct ($0.03/1M tokens) is 106.7x cheaper than Nova Pro ($3.20/1M tokens).

In conclusion, Nova Pro 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
Sat Mar 14 2026 • llm-stats.com
Meta
Llama 3.1 8B Instruct
Input tokens$0.03
Output tokens$0.03
Best providerLambda
Amazon
Nova Pro
Input tokens$0.80
Output tokens$3.20
Best providerAWS Bedrock
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Nova Pro accepts 300,000 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. Nova Pro can generate longer responses up to 300,000 tokens, while Llama 3.1 8B Instruct is limited to 131,072 tokens.

Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Amazon
Nova Pro
Input300,000 tokens
Output300,000 tokens
Sat Mar 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Nova Pro supports multimodal inputs, whereas Llama 3.1 8B Instruct does not.

Nova Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama 3.1 8B Instruct

Text
Images
Audio
Video

Nova Pro

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.1 8B Instruct is licensed under Llama 3.1 Community License, while Nova Pro uses a proprietary license.

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

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Nova Pro

Proprietary

Closed source

Release Timeline

When each model was launched

Llama 3.1 8B Instruct was released on 2024-07-23, while Nova Pro was released on 2024-11-20.

Nova Pro is 4 months newer than Llama 3.1 8B Instruct.

Llama 3.1 8B Instruct

Jul 23, 2024

1.6 years ago

Nova Pro

Nov 20, 2024

1.3 years ago

4mo newer

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while Nova Pro'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 Nova Pro's cutoff date.

Llama 3.1 8B Instruct

Dec 2023

Nova Pro

Provider Availability

Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock. Nova Pro is available from Bedrock. The availability of providers can affect quality of the model and reliability.

Llama 3.1 8B Instruct

lambda logo
Lambda
Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M
groq logo
Groq
Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M
sambanova logo
Sambanova
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
together logo
Together
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M

Nova Pro

bedrock logo
AWS Bedrock
Input Price:Input: $0.80/1MOutput Price:Output: $3.20/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive input tokens
Less expensive output tokens
Has open weights
Higher BFCL score (76.1% vs 68.4%)
Larger context window (300,000 tokens)
Supports multimodal inputs
Higher ARC-C score (94.8% vs 83.4%)
Higher DROP score (85.4% vs 59.5%)
Higher GPQA score (46.9% vs 30.4%)
Higher HumanEval score (89.0% vs 72.6%)
Higher IFEval score (92.1% vs 80.4%)
Higher MMLU score (85.9% vs 69.4%)

Detailed Comparison

AI Model Comparison Table
Feature
Meta
Llama 3.1 8B Instruct
Amazon
Nova Pro