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

QwQ-32B

Alibaba

QwQ-32B is a language model developed by Alibaba. It achieves strong performance with an average score of 74.6% across 7 benchmarks. It excels particularly in MATH-500 (90.6%), IFEval (83.9%), AIME 2024 (79.5%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Meta

Llama 3.3 70B Instruct

Meta

2024-12-06

Alibaba

QwQ-32B

Alibaba

2025-03-05

2 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.3 70B Instruct

Larger context
Max Context:256.0K
Parameters:70.0B
Alibaba

QwQ-32B

Max Context:-
Parameters:32.5B

Average performance across 2 common benchmarks

Meta

Llama 3.3 70B Instruct

Average Score:71.3%
Alibaba

QwQ-32B

+3.3%
Average Score:74.6%

Performance comparison across key benchmark categories

Meta

Llama 3.3 70B Instruct

math
84.0%
code
+15.7%
89.4%
general
+0.3%
70.7%
Alibaba

QwQ-32B

math
+6.6%
90.6%
code
73.6%
general
70.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

QwQ-32B

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

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

QwQ-32B

0 providers
Meta

Llama 3.3 70B Instruct

Avg Score:71.3%
Providers:9
Alibaba

QwQ-32B

+3.3%
Avg Score:74.6%
Providers:0