Model Comparison

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

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

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.

Meta

Llama 3.1 8B Instruct

Meta

2024-07-23

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

2025-09-29

1 year newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.2-Exp

Input:$0.27
Output:$0.41
Meta

Llama 3.1 8B Instruct

$0.62 cheaper
Input:$0.03
Output:$0.03

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.2-Exp

Max Context:229.4K
Parameters:685.0B
Meta

Llama 3.1 8B Instruct

Larger context
Max Context:262.1K
Parameters:8.0B

Average performance across 30 common benchmarks

DeepSeek

DeepSeek-V3.2-Exp

Average Score:30.8%
Meta

Llama 3.1 8B Instruct

+5.9%
Average Score:36.8%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.2-Exp

math
+18.0%
86.5%
code
64.3%
general
+8.1%
62.1%
Meta

Llama 3.1 8B Instruct

math
68.4%
code
+1.5%
65.8%
general
54.0%
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

DeepSeek

DeepSeek-V3.2-Exp

2 providers

Novita

ZeroEval

Throughput: 100 tok/s
Latency: 0.7ms
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

Cerebras

Throughput: 2047 tok/s
Latency: 0.2ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms
DeepSeek

DeepSeek-V3.2-Exp

Avg Score:30.8%
Providers:2
Meta

Llama 3.1 8B Instruct

+5.9%
Avg Score:36.8%
Providers:9