Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Meta

Llama 3.1 8B Instruct

Meta

Llama 3.1 8B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 61.3% across 18 benchmarks. It excels particularly in GSM-8K (CoT) (84.5%), ARC-C (83.4%), API-Bank (82.6%). It supports a 262K token context window for handling large documents. The model is available through 9 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.

Mistral AI

Mistral NeMo Instruct

Mistral AI

Mistral NeMo Instruct is a language model developed by Mistral AI. It achieves strong performance with an average score of 64.3% across 8 benchmarks. It excels particularly in HellaSwag (83.5%), Winogrande (76.8%), TriviaQA (73.8%). The model shows particular specialization in reasoning tasks with an average performance of 80.2%. It supports a 256K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Mistral AI's latest advancement in AI technology.

Mistral AI

Mistral NeMo Instruct

Mistral AI

2024-07-18

Meta

Llama 3.1 8B Instruct

Meta

2024-07-23

5 days newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.1 8B Instruct

$0.24 cheaper
Input:$0.03
Output:$0.03
Mistral AI

Mistral NeMo Instruct

Input:$0.15
Output:$0.15

Performance Metrics

Context window and performance specifications

Meta

Llama 3.1 8B Instruct

Larger context
Max Context:262.1K
Parameters:8.0B
Mistral AI

Mistral NeMo Instruct

Max Context:256.0K
Parameters:12.0B

Average performance across 1 common benchmarks

Meta

Llama 3.1 8B Instruct

+1.4%
Average Score:69.4%
Mistral AI

Mistral NeMo Instruct

Average Score:68.0%

Performance comparison across key benchmark categories

Meta

Llama 3.1 8B Instruct

reasoning
+3.2%
83.4%
general
54.0%
Mistral AI

Mistral NeMo Instruct

reasoning
80.2%
general
+6.8%
60.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.1 8B Instruct

2023-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.1 8B Instruct

9 providers

Sambanova

Throughput: 1050 tok/s
Latency: 0.5ms

Together

Throughput: 194 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 200 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 118 tok/s
Latency: 0.5ms

Fireworks

Throughput: 292 tok/s
Latency: 0.5ms

Groq

Throughput: 750 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms

Cerebras

Throughput: 2047 tok/s
Latency: 0.2ms
Mistral AI

Mistral NeMo Instruct

2 providers

Google

Throughput: 42 tok/s
Latency: 0.4ms

Mistral AI

Throughput: 0.1 tok/s
Latency: 0.5ms
Meta

Llama 3.1 8B Instruct

+1.4%
Avg Score:69.4%
Providers:9
Mistral AI

Mistral NeMo Instruct

Avg Score:68.0%
Providers:2