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TokenGO vs Tenki

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

TokenGO compared with Tenki
DetailTokenGO logo TokenGOTenki logo Tenki
What it doesSelf-operated inference API for open-weight LLMs and video models Cloud infrastructure for your code and agents
StageNot given Startup
FoundedNot given 2024
Based inUS US
Pricing modelPaid Freemium
PricingStandard (pay-as-you-go, under $1K/month): List price with unified API, cost monitoring, usage limits, unlimited seats. Growth ($1K-$15K/month): 20% volume discount, quarterly billing, priority support, SLA. Scale ($15K-$40K/month): 30% volume discount, dedicated support, DPA. Custom ($40K+/month): Starter: Free with $100 in credits; Team: $200/mo (annual) or $250/mo (monthly) with $100/mo credits. Usage-based rates: Code Reviews $1.00 per review, x64 Runners $0.002 per vCPU/minute, macOS Runners $0.020 per vCPU/minute, Sandbox vCPU $0.000014 per second, Sandbox Memory $0.0000045 per GiB/secon
Key features
  • Zero-retention privacy policy
  • Smart routing optimization
  • Hardware adaptation per request
  • Inference engine kernel optimization
  • KV cache layer for token reuse
  • Unified API across model catalog
  • Cost and usage monitoring
  • Volume-based tiered discounting
  • Data Processing Agreement available
  • Instant sandboxes that boot in under one second
  • GitHub Actions runners for x64 and macOS
  • AI-powered code review on every pull request
  • Support for Go, TypeScript, and Python SDKs
  • Git operations including clone, checkout, and diff
  • Persistent volumes and snapshots
  • Outbound domain and CIDR allowlists
  • Pre-built container images
  • OpenCode integration for AI workflows
  • Configurable CPU and memory options
What makes it different
  • Single API key for access to leading models like DeepSeek, Kimi, and Qwen
  • Enterprise uptime and service guarantees without separate integrations
  • Zero-retention privacy with US governance and DPA support
  • Cost-efficiency through kernel optimization adopted by frontier labs
  • No integration rewrite required for teams already using OpenAI-compatible APIs
  • Bare-metal infrastructure for 30% faster performance and up to 60% cheaper than alternatives
  • Sandboxes boot in under one second, enabling instant isolation for AI agents
  • AI code review that reads your full codebase and reviews every PR
  • Drop-in GitHub Actions replacement requiring no configuration changes
  • Infrastructure built specifically for AI agents to write, run, and ship code
Community votes00
DR (Domain Rating by Ahrefs)17 no change since last check47 no change since last check
Trust Flow (Majestic)410
Citation Flow (Majestic)2734
Referring domains (Majestic)77222

6 details filled in for both companies.

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