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Together AI vs Vectorize

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

Together AI compared with Vectorize
DetailTogether AI logo Together AIVectorize logo Vectorize
What it doesThe AI Native Cloud Agent memory that learns from experience
StageNot given Startup
FoundedNot given 2024
Based inNot given US
Pricing modelFreemium Freemium
PricingServerless inference with pay-per-use token pricing ($0.0015 to $4.50 per 1M tokens for chat/vision models). Provisioned throughput with reserved PTUs for committed capacity. Dedicated GPU endpoints at $5.49-$8.99 per hour. Fine-tuning from $0.34-$40 per 1M tokens. GPU clusters at $1.99-$9.99 per GP Self-hosted: Free, MIT licensed. Hindsight Cloud: Pay-as-you-go with free credits to start. Retain (store memories) $10.00 per million tokens, Recall (retrieve memories) $0.75 per million tokens, Reflect (synthesize patterns) $0.05 per call, Iris Extract (structured extraction) $7.50 per million tok
Key features
  • GPU clusters at scale with autoscaling
  • Voice agent infrastructure with sub-second latency
  • Comprehensive model library with 25+ regions
  • Per-user persistent memory with preferences, history and decisions kept separate
  • Cross-session persistence allows context to survive weeks between interactions
  • Fast parallel retrieval in under 100ms through four strategies running simultaneously
  • Works with any LLM without losing learned context when swapping models
  • Learns from mistakes and corrects behavior on repeated problems
  • Automatic pattern detection synthesizes individual facts into consolidated knowledge
  • Conflict detection preserves both old and new states with timestamps when facts change
  • Integrates with 20+ coding agents including Claude Code, Cursor, and Copilot
What makes it different
  • 2x faster inference powered by cutting-edge research optimization
  • 60% lower cost with workload-specific optimization
  • 90% faster pre-training with Together Kernel Collection
  • Research-optimized infrastructure with proprietary kernels
  • Single unified API across multiple model providers
  • 94.6% retrieval accuracy on LongMemEval-S, beating next-best system at 74.0%
  • MIT licensed open source with no usage limits, telemetry or restrictions
  • Reflection layer automatically builds judgment and mental models over time without manual tagging
  • Entity resolution handles hundreds of entities with 99.5% query reduction
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)82 +1 (up) since last check68 +1 (up) since last check
Trust Flow (Majestic)3618
Citation Flow (Majestic)5647
Referring domains (Majestic)81951378

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