+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Llama 3.1 8B Instruct vs Qwen2-VL-72B-Instruct
Comprehensive side-by-side LLM comparison
Qwen2-VL-72B-Instruct supports multimodal inputs. Llama 3.1 8B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
+
+
+
+
Meta
Llama 3.1 8B was developed as an efficient open-source model, designed to bring capable instruction-following to applications with limited computational resources. Built with 8 billion parameters, it provides a lightweight option for developers seeking reliable performance without the overhead of larger models.
+
+
+
+
Alibaba Cloud / Qwen Team
Qwen2-VL 72B was developed as a large vision-language model, designed to handle multimodal tasks combining visual and textual understanding. Built with 72 billion parameters for integrated vision and language processing, it enables applications requiring sophisticated analysis of images alongside text.
1 month newer
Llama 3.1 8B Instruct
Meta
2024-07-23
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
2024-08-29
+
+
+
+
+
+
+
+
+
+
+
+
Performance Metrics
Context window and performance specifications
+
+
+
+
Knowledge Cutoff
Training data recency comparison
Qwen2-VL-72B-Instruct
2023-06-30
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
+
+
+
+
Llama 3.1 8B Instruct
9 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Cerebras
Throughput: 2047 tok/s
Latency: 0.2ms
DeepInfra
Throughput: 118 tok/s
Latency: 0.5ms
Fireworks
Throughput: 292 tok/s
Latency: 0.5ms
Groq
+
+
+
+
Llama 3.1 8B Instruct
Avg Score:0.0%
Providers:9
+
+
+
+
Qwen2-VL-72B-Instruct
Avg Score:0.0%
Providers:0