www.gocodeo.com
Claude AI by Anthropic: What Developers Need to Know in 2025
Excerpt
##### 6. Limitations and Considerations Despite its strengths, Claude still has limitations: - **No plug-and-play vision model** as of Q2 2025 (compared to GPT-4V). - **Model weights are not open-source**, limiting on-premise deployment. - **Fine-tuning is not developer-facing**, unlike some open models like Mistral or LLaMA 3. - **Latency** for Opus can spike under load, especially with 200K context inputs.
Source URL
https://www.gocodeo.com/post/claude-ai-by-anthropic-what-developers-need-to-know-in-2025-gocodeoRelated Pain Points
High latency on Opus model under load with large context
5Claude Opus experiences significant latency spikes when processing requests with 200K token context windows during periods of high load, impacting real-time application responsiveness.
Lack of open-source model weights limits on-premise deployment
5Claude model weights are not open-source, preventing developers from deploying models on-premise or customizing them for specific use cases, unlike competitors like Mistral or LLaMA 3.
Limited Multimodal Capabilities Beyond Vision
5Claude 3.5 Sonnet lacks audio processing, video analysis, and advanced image generation capabilities. Businesses requiring comprehensive multimodal AI must integrate additional tools, increasing complexity and costs compared to more versatile competitors.