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

Qwen3 32B

Alibaba

Qwen3 32B is a language model developed by Alibaba. It achieves strong performance with an average score of 75.3% across 9 benchmarks. It excels particularly in CodeForces (95.2%), Arena Hard (93.8%), AIME 2024 (81.4%). The model shows particular specialization in code tasks with an average performance of 80.4%. It supports a 256K token context window for handling large documents. The model is available through 3 API providers. 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 3.1 8B Instruct

Meta

2024-07-23

Alibaba

Qwen3 32B

Alibaba

2025-04-29

9 months newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.1 8B Instruct

$0.34 cheaper
Input:$0.03
Output:$0.03
Alibaba

Qwen3 32B

Input:$0.10
Output:$0.30

Performance Metrics

Context window and performance specifications

Meta

Llama 3.1 8B Instruct

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

Qwen3 32B

Max Context:256.0K
Parameters:32.8B

Average performance across 1 common benchmarks

Meta

Llama 3.1 8B Instruct

+5.8%
Average Score:76.1%
Alibaba

Qwen3 32B

Average Score:70.3%

Performance comparison across key benchmark categories

Meta

Llama 3.1 8B Instruct

code
65.8%
general
54.0%
Alibaba

Qwen3 32B

code
+14.6%
80.4%
general
+19.6%
73.6%
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

Qwen3 32B

3 providers

Sambanova

Throughput: 327.7 tok/s
Latency: 1.08ms

DeepInfra

Throughput: 26.95 tok/s
Latency: 1.19ms

Novita

Throughput: 32.43 tok/s
Latency: 0.93ms
Meta

Llama 3.1 8B Instruct

+5.8%
Avg Score:76.1%
Providers:9
Alibaba

Qwen3 32B

Avg Score:70.3%
Providers:3