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TokenGO vs BitsRun

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 BitsRun
DetailTokenGO logo TokenGOBitsRun logo BitsRun
What it doesSelf-operated inference API for open-weight LLMs and video models Deploy any open model from Ollama or Hugging Face as a private, OpenAI-compatible API
StageNot given Not given
FoundedNot given Not given
Based inUS US
Pricing modelPaid Paid
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): Pay as you go: $0/month with prepaid credits from $10. Pro: $29/month with $29 monthly credits. Business: $299/month with $299 monthly credits. GPU pricing: NVIDIA L4 $0.95/hour ($0.000264/second, $1,180/month always-on); NVIDIA L40S $3.20/hour ($0.000889/second, $3,974/month always-on); 4x NVIDIA L
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
  • Deploy models with one command via CLI
  • OpenAI and Ollama API compatibility
  • Scales to zero with configurable idle timeout (60 seconds to 60 minutes)
  • Private endpoints with no prompt logging
  • Supports GGUF and safetensors model formats
  • Free model storage (10GB to 1TB depending on plan)
  • Always-on option for no cold starts
  • Batch jobs pricing 30-50% cheaper
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
  • No Dockerfile or server management required
  • Use your existing OpenAI or Ollama client with one URL change
  • Pay only for actual compute seconds used, not monthly subscription
  • Cold start time never billed and requests wait instead of failing
  • Prompts and outputs never logged or used for training
Community votes00
DR (Domain Rating by Ahrefs)17 no change since last checkNot checked yet no change since last check
Trust Flow (Majestic)40
Citation Flow (Majestic)270
Referring domains (Majestic)770

6 details filled in for both companies.

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