AI Infrastructure & APIs comparison · 2026

Blackbox vs Zep

Compare Blackbox and Zep as AI Infrastructure & APIs tools on fit, pricing, and the capabilities that actually overlap in 2026. Pick Blackbox for teams serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads and consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoice. Pick Zep for teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query.

Updated Aug 22, 2026

Blackbox
blackbox.ai

Encrypted single-tenant inference plus a 300+ model router behind one endpoint

Starts at Custom (annual per-token commit; no published entry price)·AI Infrastructure & APIs

Zep
getzep.com

Agent memory at enterprise scale, built on temporal context graphs

Starts at $0/month·AI Infrastructure & APIs

At a glance

BlackboxZep
CategoryAI Infrastructure & APIsAI Infrastructure & APIs
PricingStarts at Custom (annual per-token commit; no published entry price)Starts at $0/month
Free tierNoYes
PlatformsWebWeb
Suitable forTeams serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads and consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoiceTeams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
CompanyBlackbox AI Technologies Inc.Zep AI, Inc.
Founded—2023

How they differ

Shared AI Infrastructure & APIs rubric, filled from each listing. Not a score.

Model catalog

BlackboxZep
Text modelsYesNo
Image modelsNot publishedNo
Video modelsNot publishedNo
Speech modelsNot publishedNo
Open-weight modelsYesNo
Pinned versionsLimitedNot published

Serving

BlackboxZep
One unified APIYesNo
OpenAI-compatible APIYesNo
Streaming responsesYesNot published
Batch jobsNot publishedNot published
Provider fallbackYesNot published
Published rate limitsNot publishedNot published

Build & tune

BlackboxZep
Fine-tuningNot publishedNot published
EmbeddingsNot publishedNot published
Vector storeNot publishedNot published
RAG pipelinesNot publishedLimited
Agent frameworkYesNo
Tool / function callingNot publishedLimited

Observe & control

BlackboxZep
Usage dashboardYesYes
Per-request costsLimitedNot published
Traces / loggingNot publishedYes
EvalsNot publishedNo
Prompt managementNot publishedNot published
Zero-retention optionYesLimited

Access

BlackboxZep
Public APIYesYes
Official SDKLimitedYes
Self-serve signupLimitedYes
Free trialNot publishedNot published
Team workspaceLimitedNot published
SSO / SAMLYesNot published
Mobile appsNoNo
Browser extensionNot publishedNo
Self-host / on-premNoYes

Commercial

BlackboxZep
Commercial licenseNot publishedNot published
Usage-based pricingYesNot published
Invoice / POLimitedNot published
SOC 2Not publishedYes
GDPR / DPAYesNot published
Audit logYesYes
Role-based accessYesLimited

Features

These listings describe different capabilities. What each one ships:

Only Blackbox

  • Blackbox Router exposes 300+ hosted open and closed models through one OpenAI-compatible endpoint with one key, one bill, and one dashboard
  • Blackbox Enterprise Inference runs the open-weight model you choose on reserved, single-tenant GPU capacity
  • End-to-end encryption on every connection plus encryption at rest
  • Zero data retention enforced at the gateway, contractual under the Enterprise DPA
  • PII removed before prompts reach closed models on Enterprise
  • Smart routing, failover, and prompt caching included at no extra platform fee
  • OpenAI-compatible REST and streaming, so only the base URL changes
  • Agents API for cloud coding agents and multi-agent workflows

Only Zep

  • Temporal context graphs that record facts with a validity window
  • Fact invalidation when new information contradicts the graph, with old facts kept as history
  • Point-in-time queries: ask what is true now or what was true on a past date
  • Multi-source ingest from chat history, business data (JSON) and user interactions
  • Automated context assembly returning token-efficient context blocks
  • Observations: patterns, recurrences and co-occurrences detected across the graph
  • Provenance on every fact, traced back to the source episode
  • Context Lake architecture governing millions of context graphs as one system

Use cases

These listings describe different use cases. What each one ships:

Only Blackbox

  • Serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads
  • Consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoice
  • Passing a security review that requires contractual zero retention and no model training on prompts
  • Cutting inference bills by routing cost-sensitive tasks to cheaper open-weight models with prompt caching
  • Running cloud coding agents and Remote Agent sandboxes on the same token budget as production inference
  • Migrating an existing OpenAI-compatible codebase to a new provider by swapping the base URL
  • Standardizing developer AI access across an organization with SSO, RBAC, and audit logs
  • Keeping negotiated provider rates while gaining failover and centralized observability

Only Zep

  • Giving a production customer-support agent persistent memory of a user's prior issues and stated preferences
  • Fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
  • Answering point-in-time questions such as what a customer's plan or preference was on a specific date
  • Reducing prompt token spend by replacing full chat transcripts with an assembled context block
  • Auditing why an agent said something by tracing the underlying fact back to its source episode
  • Detecting behavioural patterns, such as repeat upgrade timing, and feeding them to an agent as Observations
  • Running agent memory inside a regulated customer's own VPC via Bring Your Own Cloud
  • Exposing agent memory to IDEs and assistants through the Memory MCP Server

Plans

Blackbox

  • Enterprise Custom/mo or Custom/yr

    Annual PO burn-down, committed spend sized with your team · Closed models −5%+, open-weight models −10%+ discounts · Dedicated forward-deployed engineer; implementation included, $0 · Dedicated single-tenant deployment (Enterprise Inference) · Data residency · SAML SSO, SCIM, RBAC, audit logs · Zero data retention, contractual DPA · PII removed before closed models · End-to-end encryption on every connection · Guaranteed TPM / custom rate limits · Dedicated Remote Agent runners with SSO · Agents API: cloud coding agents

Zep

  • Free $0/mo or $0/yr

    10,000 credits per month (no rollover or auto top-up) · 2 projects · Memory MCP Server seat · Custom entity/edge types · Variable rate limits depending on service-wide load · Lower priority Episode processing · Community support

  • Flex $125/mo or $1250/yr

    50,000 credits per month included, then $25 per 10,000 credits · Auto top-up at 20% (10,000 credits / $25) · 30-day credit rollover · 600 requests per minute · 5 projects · 5 Memory MCP Server seats · 10 custom entity/edge types · API logs retained 1 day · Unlimited memories and retrieval users · Community support · Cloud deployment

  • Flex Plus $375/mo or $3750/yr

    200,000 credits per month included, then $75 per 40,000 credits · Auto top-up at 20% (40,000 credits / $75) · 60-day credit rollover · 1,000 requests per minute · 10 projects · 15 Memory MCP Server seats · 20 custom entity/edge types · Observations, custom extraction instructions, webhooks, analytics · API logs retained 7 days · Unlimited memories and retrieval users · Priority support

Blackbox strengths

  • One OpenAI-compatible endpoint reaches 300+ models, so migration is a base URL change rather than a rewrite
  • Blackbox publishes per-1M-token list rates for input, output, and cached reads instead of hiding all numbers behind sales
  • Blackbox states there is no platform fee, no credit-purchase fee, and no per-seat charge
  • Single-tenant deployments on Blackbox GPUs give isolation that shared multi-tenant routers cannot offer
  • The same commit covers Enterprise Inference, the Router, the API, the CLI, the Agents API, and the VS Code extension
  • Implementation with a dedicated forward-deployed engineer is included at $0 on Enterprise
  • Bring-your-own provider accounts preserve existing negotiated rates while keeping routing and dashboards
  • Blackbox cites an independent Artificial Analysis measurement of 454 tokens per second on Nemotron Ultra rather than a self-reported figure

Watch-outs

  • Unused committed spend expires at the end of the billing period and does not roll over; Blackbox only warns at 75% and 90% of the commit
  • No published $0 tier, no free credits, and no self-serve signup: Blackbox says engagement starts "with conversation, not signup"
  • Every plan is custom-quoted, so no buyer can compare an entry price without contacting Blackbox sales
  • PII removal before closed models, data residency, dedicated Remote Agent runners, custom SLAs, and the dedicated engineer are Enterprise-only
  • Zero retention and training suppression on routed traffic are qualified by Blackbox as applying "wherever the provider API supports it," so guarantees vary by upstream provider
  • Chairman LLM orchestration is listed as included but metered, which adds consumption on top of standard token spend
  • Vendor contradiction: the Blackbox homepage says 30% faster than the #2 provider on Nemotron Ultra, while the Blackbox contact page says 47% faster at the same 454 t/s and 2.7x price figures
  • Vendor contradiction: Blackbox structured data names the legal entity Blackbox AI Technologies Inc., while the Blackbox privacy policy names Cours Connecte Inc. doing business as Blackbox AI Technologies

Zep strengths

  • Zep publishes concrete p95 latency figures across graph sizes (148ms at 10K to 168ms at 100M) rather than a vague speed claim
  • Z
  • Temporal context graphs that record facts with a validity window
  • Fact invalidation when new information contradicts the graph, with old facts kept as history
  • Point-in-time queries: ask what is true now or what was true on a past date
  • Multi-source ingest from chat history, business data (JSON) and user interactions
  • Automated context assembly returning token-efficient context blocks
  • Observations: patterns, recurrences and co-occurrences detected across the graph

Watch-outs

  • Zep plan limits come from the published pricing table.
  • Zep packaging is recorded from the vendor pages available at analysis time.

Blackbox vs Zep verdict

Who each product is for, then labeled AI takes. Not a generic winner.

Bottom line

Pick Blackbox for teams serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads and consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoice. Pick Zep for teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query.

Who Blackbox is for

Teams serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads and consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoice

Encrypted single-tenant inference plus a 300+ model router behind one endpoint

Who Zep is for

Teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query

Agent memory at enterprise scale, built on temporal context graphs

AI take on Blackbox

In August 2026, Blackbox stands out for dedicated open-weight inference and broad routing, but its commit-only sales model demands careful validation.

AI take on Zep

As of August 2026, Zep stands out where agent memory must be temporal, governed, and auditable rather than a thin wrapper around transcript retrieval.

Blackbox vs Zep FAQ

Common questions when choosing between Blackbox and Zep.

Is Blackbox or Zep the better AI Infrastructure & APIs tool?

Pick Blackbox for teams serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads and consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoice. Pick Zep for teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query.

Which is cheaper, Blackbox or Zep?

Blackbox starts at Custom (annual per-token commit; no published entry price). Zep starts at $0/month. Confirm current pricing on each vendor site.

Who should choose Blackbox?

Teams serving open-weight frontier models such as Nemotron Ultra on isolated capacity for regulated workloads and consolidating scattered OpenAI, Anthropic, and Google spend behind one endpoint and one invoice

Who should choose Zep?

Teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query

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