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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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SiliconFlow
✓ verified
Developer platform serving 200+ optimized LLMs via APIs; high traffic.
434K visits/mo1.1K saves
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DeepSeek
✓ verifiedFreemium
Chinese AI lab DeepSeek offering free chat apps and low-cost API access to its frontier V-series and R-series reasoning models.
430M visits/mo
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Code Arena
✓ verifiedFree
Side-by-side arena to compare AI coding models and build multi-file apps, with a public leaderboard and battle mode.
35M visits/mo201 saves
Pricing
No public pricing
No public pricing
No public pricing
Core features
- ✦Access over 200 optimized models, including LLMs, image, video, and audio processing.
- ✦Achieve low-latency, high-throughput inference with SiliconFlow's self-developed acceleration frameworks.
- ✦Deploy models via serverless inference, dedicated endpoints, or reserved GPUs to suit various workloads.
- ✦Customize models to your data with built-in monitoring and elastic compute resources.
- ✦Ensure data privacy and business security with dynamic scaling and fault tolerance mechanisms.
- ✦Free DeepSeek chat (web and app)
- ✦Open API platform
- ✦V-series and R-series reasoning models
- ✦DeepSeek-V4 with long context and stronger agent ability
- ✦OpenAI/Anthropic-compatible API
- ✦Extensive published model lineup
- ✦Head-to-head model comparison
- ✦Battle mode matchups
- ✦Public model leaderboard
- ✦Multi-file app generation
- ✦File uploads as input
Use cases
- →Quickly deploy various AI models via a simple API, supporting tasks like text, image, audio, and video processing.
- →Utilize serverless GPUs to automatically scale AI applications, ensuring flexibility and cost-efficiency.
- →Access high-performance GPUs for demanding workloads, such as large-scale inference and video generation.
- →Deploy custom models with guaranteed performance and scalability, tailored to specific business needs.
- →Free AI chat and assistance
- →Building apps via API
- →Reasoning and coding tasks
- →Low-cost LLM inference
- →Choosing the best coding model
- →Benchmarking AI code quality
- →Prototyping small apps
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