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.

Alibaba

Qwen2.5 32B Instruct

Alibaba

Qwen2.5 32B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 74.3% across 18 benchmarks. It excels particularly in GSM8k (95.9%), HumanEval (88.4%), HellaSwag (85.2%). The model shows particular specialization in math tasks with an average performance of 89.5%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Meta

Llama 3.1 8B Instruct

Meta

2024-07-23

Alibaba

Qwen2.5 32B Instruct

Alibaba

2024-09-19

1 month newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.1 8B Instruct

Larger context
Max Context:262.1K
Parameters:8.0B
Alibaba

Qwen2.5 32B Instruct

Max Context:-
Parameters:32.5B

Average performance across 5 common benchmarks

Meta

Llama 3.1 8B Instruct

Average Score:60.8%
Alibaba

Qwen2.5 32B Instruct

+11.3%
Average Score:72.1%

Performance comparison across key benchmark categories

Meta

Llama 3.1 8B Instruct

math
68.4%
reasoning
+4.2%
83.4%
code
65.8%
general
54.0%
Alibaba

Qwen2.5 32B Instruct

math
+21.1%
89.5%
reasoning
79.2%
code
+7.2%
73.0%
general
+17.3%
71.3%
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
Alibaba

Qwen2.5 32B Instruct

0 providers
Meta

Llama 3.1 8B Instruct

Avg Score:60.8%
Providers:9
Alibaba

Qwen2.5 32B Instruct

+11.3%
Avg Score:72.1%
Providers:0