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Confidential AI vs BenchRouter

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Confidential AI compared with BenchRouter
DetailConfidential AI logo Confidential AIBenchRouter logo BenchRouter
What it doesPrivate AI inference and confidential GPU computing infrastructure Pick your AI model based on evaluation results, not intuition
StageNot given Not given
FoundedNot given Not given
Based inUS US
Pricing modelPaid Not given
PricingConfidential Inference: DeepSeek V4.1 Flash $0.30 input and $1.20 output per 1M tokens; Kimi K3 $3.00 input and $15.00 output per 1M tokens; GLM 5.3 $1.40 input and $4.40 output per 1M tokens; Qwen3.8 27B $0.30 input and $1.80 output per 1M tokens. Confidential VMs: B300 at $7.50 per GPU-hour, B200 Not given
Key features
  • OpenAI-compatible endpoint for private LLM inference
  • Hardware-encrypted VMs on Intel TDX, AMD SEV-SNP and NVIDIA GPUs
  • Client attestation verification before sending requests
  • Support for multiple open-weight models including DeepSeek, Kimi, GLM, Qwen
  • Confidential Kubernetes for data center scale deployments
  • Confidential training and fine-tuning on licensed stack
  • Root access over SSH to confidential VMs
  • Encrypted GPU communications with NVLink encryption on B200 and B300
  • Confidential agents runtime support
  • Prompt caching with cached input billing
  • Automatic model routing based on evaluation results
  • GitHub repository integration for eval workflows
  • Stores evidence of evaluation results
  • Automatic re-evaluation when new models are released
  • Dashboard for monitoring routes
  • MCP server integration with ChatGPT, Claude, and Cursor
  • Configurable evaluation checks and criteria
What makes it different
  • Prompts and model weights verified by clients with cryptographic attestation before any data is sent
  • Operator-blind inference: data remains unreadable to the company and hosting provider
  • Flexible deployment: choice of hosted cloud, rented VMs, or licensed stack on own infrastructure
  • Open-weight models only, no closed-source frontier models
  • Full cryptographic verification stack including open-source tools
  • Test your own LLM applications against real models automatically
  • Routes requests to the best-performing model in real time
  • Automatically updates routing when new models are released
  • Keeps your eval results and configurations under your control
Community votes00
DR (Domain Rating by Ahrefs)12 +1 (up) since last checkNot checked yet no change since last check
Trust Flow (Majestic)70
Citation Flow (Majestic)260
Referring domains (Majestic)360

4 details filled in for both companies.

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