Model Comparison

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

Meta

Llama 3.3 70B Instruct

Meta

Llama 3.3 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 79.9% across 9 benchmarks. It excels particularly in IFEval (92.1%), MGSM (91.1%), HumanEval (88.4%). The model shows particular specialization in code tasks with an average performance of 89.4%. 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.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

Qwen2.5-Coder 32B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 64.9% across 15 benchmarks. It excels particularly in HumanEval (92.7%), GSM8k (91.1%), MBPP (90.2%). The model shows particular specialization in reasoning tasks with an average performance of 78.1%. It supports a 256K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

2024-09-19

Meta

Llama 3.3 70B Instruct

Meta

2024-12-06

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.3 70B Instruct

Input:$0.20
Output:$0.20
Alibaba

Qwen2.5-Coder 32B Instruct

$0.22 cheaper
Input:$0.09
Output:$0.09

Performance Metrics

Context window and performance specifications

Meta

Llama 3.3 70B Instruct

Max Context:256.0K
Parameters:70.0B
Alibaba

Qwen2.5-Coder 32B Instruct

Max Context:256.0K
Parameters:32.0B

Average performance across 4 common benchmarks

Meta

Llama 3.3 70B Instruct

+11.2%
Average Score:80.1%
Alibaba

Qwen2.5-Coder 32B Instruct

Average Score:68.8%

Performance comparison across key benchmark categories

Meta

Llama 3.3 70B Instruct

code
+31.2%
89.4%
math
+9.9%
84.0%
general
+9.1%
70.7%
Alibaba

Qwen2.5-Coder 32B Instruct

code
58.2%
math
74.2%
general
61.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.3 70B Instruct

9 providers

Sambanova

Throughput: 1096 tok/s
Latency: 0.65ms

Together

Throughput: 65 tok/s
Latency: 0.65ms

Hyperbolic

Throughput: 42 tok/s
Latency: 0.65ms

DeepInfra

Throughput: 37 tok/s
Latency: 0.65ms

Fireworks

Throughput: 197 tok/s
Latency: 0.65ms

Groq

Throughput: 268 tok/s
Latency: 0.65ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms

Lambda

Throughput: 42 tok/s
Latency: 0.65ms

Cerebras

Throughput: 2220 tok/s
Latency: 0.65ms
Alibaba

Qwen2.5-Coder 32B Instruct

4 providers

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 44 tok/s
Latency: 0.5ms

Fireworks

Throughput: 110 tok/s
Latency: 0.26ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms
Meta

Llama 3.3 70B Instruct

+11.2%
Avg Score:80.1%
Providers:9
Alibaba

Qwen2.5-Coder 32B Instruct

Avg Score:68.8%
Providers:4