Model Comparison

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

Llama 3.1 70B Instruct

Meta

Llama 3.1 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 74.7% across 18 benchmarks. It excels particularly in GSM-8K (CoT) (95.1%), ARC-C (94.8%), API-Bank (90.0%). It supports a 256K 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.

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.

Llama 3.1 70B Instruct

Meta

2024-07-23

Llama 3.1 8B Instruct

Meta

2024-07-23

0 days newer

Pricing Comparison

Cost per million tokens (USD)

Llama 3.1 70B Instruct

Input:$0.20

Output:$0.20

Llama 3.1 8B Instruct

$0.34 cheaper

Input:$0.03

Output:$0.03

Performance Metrics

Context window and performance specifications

Llama 3.1 70B Instruct

Max Context:256.0K

Parameters:70.0B

Llama 3.1 8B Instruct

Larger context

Max Context:262.1K

Parameters:8.0B

Average performance across 17 common benchmarks

Llama 3.1 70B Instruct

+13.4%

Average Score:74.0%

Llama 3.1 8B Instruct

Average Score:60.6%

Performance comparison across key benchmark categories

Llama 3.1 70B Instruct

reasoning

+11.4%

94.8%

math

+14.9%

83.3%

code

+10.5%

76.3%

general

+14.7%

68.7%

Llama 3.1 8B Instruct

reasoning

83.4%

math

68.4%

code

65.8%

general

54.0%

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

Llama 3.1 70B Instruct

9 providers

Sambanova

Throughput: 74 tok/s

Latency: 0.5ms

Together

Throughput: 94 tok/s

Latency: 0.5ms

Hyperbolic

Throughput: 100 tok/s

Latency: 0.5ms

DeepInfra

Throughput: 25 tok/s

Latency: 0.5ms

Fireworks

Throughput: 32 tok/s

Latency: 0.5ms

Groq

Throughput: 250 tok/s

Latency: 0.5ms

Bedrock

Throughput: 100 tok/s

Latency: 0.5ms

Lambda

Throughput: 42 tok/s

Latency: 0.5ms

Cerebras

Throughput: 1204 tok/s

Latency: 0.2ms

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

Llama 3.1 70B Instruct

+13.4%

Avg Score:74.0%

Providers:9

Llama 3.1 8B Instruct

Avg Score:60.6%

Providers:9