Model Comparison

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

Meta

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.

Alibaba

QwQ-32B-Preview

Alibaba

QwQ-32B-Preview is a language model developed by Alibaba. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). 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.

Meta

Llama 3.1 70B Instruct

Meta

2024-07-23

Alibaba

QwQ-32B-Preview

Alibaba

2024-11-28

4 months newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.1 70B Instruct

Input:$0.20
Output:$0.20
Alibaba

QwQ-32B-Preview

$0.05 cheaper
Input:$0.15
Output:$0.20

Performance Metrics

Context window and performance specifications

Meta

Llama 3.1 70B Instruct

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

QwQ-32B-Preview

Max Context:65.5K
Parameters:32.5B

Average performance across 1 common benchmarks

Meta

Llama 3.1 70B Instruct

Average Score:41.7%
Alibaba

QwQ-32B-Preview

+23.5%
Average Score:65.2%

Performance comparison across key benchmark categories

Meta

Llama 3.1 70B Instruct

math
83.3%
code
+26.3%
76.3%
general
+11.1%
68.7%
Alibaba

QwQ-32B-Preview

math
+7.3%
90.6%
code
50.0%
general
57.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

QwQ-32B-Preview

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 3.1 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
Alibaba

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms
Meta

Llama 3.1 70B Instruct

Avg Score:41.7%
Providers:9
Alibaba

QwQ-32B-Preview

+23.5%
Avg Score:65.2%
Providers:4