Blackbox AI
Blackbox AI routes 300+ models through one OpenAI-compatible endpoint with zero data retention and end-to-end encryption.
If your bottleneck is agent throughput on compliance-sensitive code, Blackbox pairs verified top-end tokens/sec (454 t/s on Nemotron 3 Ultra, July 2026) with zero data retention, PII stripping, and end-to-end encryption on the same endpoint — a combination OpenRouter and Together don't match on the compliance side, and managed Bedrock/Vertex don't match on the coding-agent surface. The catch is the annual committed token balance: unused commitment expires at period end and there's no month-to-month path to the discount, so this rewards teams already spending real money on inference. Teams comparing on sticker price alone will find cheaper single-model hosts, and anyone who just wants inline
Verified 7d ago · liveness 87/100 · cite: rightaichoice.com/tools/blackbox-ai
- Enterprise DevOps and platform teams needing high-throughput inference with zero data retention
- Compliance-sensitive organizations (HIPAA, SOC 2) requiring PII stripping and audit logs
- Teams running multiple coding agents at scale via the Agents API and agentic CLI
- Cost engineers chasing verified throughput — 454 t/s on Nemotron 3 Ultra at 2.7x lower cost per token than the #2
- Individual developers who want inline autocomplete or chat without wiring up an API
- Non-engineering teams that live in GUI tools and never touch a terminal
- Projects with low inference volume, where an annual token commit costs more than a flat monthly plan
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Skip Blackbox if you can't forecast an annual inference volume — the commit doesn't carry forward, so low or spiky usage is cheaper on a flat monthly plan than on a metered token balance that expires at period end.
Unused commitment expires at the end of the billing period, so tokens you over-committed for simply disappear instead of rolling forward — Blackbox sends spend alerts at 75% and 90% to warn you.
Blackbox fits organizations committing real annual inference spend — priced per token with no platform fees and no seats, quoted as Custom Annual on PO burn-down against published list rates (e.g. deepseek-v4.1-flash at $0.30 input / $1.20 output per 1M tokens; moonshotai kimi-k3 at $3.00 / $15.00). Cheaper single-model hosts exist if price alone is the criterion; managed Bedrock or Vertex cost more in procurement friction but offer a vetted hyperscaler contract. Blackbox's differentiation is
In short
Blackbox AI — Blackbox AI routes 300+ models through one OpenAI-compatible endpoint with zero data retention and end-to-end encryption. Best for Enterprise DevOps and platform teams needing high-throughput inference with zero data retention, Compliance-sensitive organizations (HIPAA, SOC 2) requiring PII stripping and audit logs, Teams running multiple coding agents at scale via the Agents API and agentic CLI. Free to use.
What's new in Blackbox AI
Checked 7 days agoAcross the latest 3 updates: 1 launch and 2 news mentions.
Announcing Nemotron 3.5 Lightning: reasoning at 1,200 tokens/sec
Nemotron 3.5 Lightning starts in about one second and reasons at 1,200 tokens/sec, holding that speed across 20 straight runs.
TB v2.1 Blackbox: GPT-5.6 Sol + Opus 4.8 (90% pass@1)
A two-model Blackbox configuration reaches 90.2% pass@1 on Terminal-Bench v2.1 on the Artificial Analysis basis, leading that leaderboard.
Benchmark Performance: Faster Inference, Reference-Level Model Quality
Blackbox publishes benchmark results claiming higher throughput and lower latency when serving a model through its API, with no observed quality regression against reference runs.
Viability Score
How well maintained and how widely used is Blackbox AI? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- 300+ open and closed models through one OpenAI-compatible endpoint
- End-to-end encryption (ECDH + AES-256-GCM) on every connection
- Zero data retention enforced at the gateway, contractual with DPA on Enterprise
- PII stripped before prompts reach closed models (Enterprise)
- Training suppressed on routed traffic via provider terms and per-request flags
- Agents API: send coding agents to any repository over HTTP, stream logs, open PRs
- Agentic CLI terminal that reads your repository conventions
- /multi-agent orchestration with a Chairman LLM
- Metered Remote Agent cloud sandboxes with dedicated runners and SSO on Enterprise
- Dedicated single-tenant deployment on reserved capacity (Enterprise Inference)
- Per-token billing — input, output, and cached reads metered separately, no seat fees
- Smart routing, failover, and prompt caching extend a commit 10-20%
- Guaranteed TPM and custom rate limits on Enterprise
- Connect your own OpenAI, Anthropic, or Google accounts and route through them
- Just change the base URL to move existing OpenAI code onto Blackbox
About Blackbox AI
Blackbox AI is an inference platform for engineering teams that need frontier model access without shipping readable prompts to a third party. One OpenAI-compatible endpoint reaches 300+ open and closed models, and moving existing OpenAI-style code onto Blackbox is mostly a base-URL change. The gateway enforces zero data retention and no-training flags on routed traffic wherever the provider API supports it, and on Enterprise it strips PII before prompts reach a closed model. Prompts are encrypted before they leave your machine and decrypted only where the model runs. Two deployment shapes matter. Blackbox Router is the shared, multi-tenant path with smart routing, failover, and prompt caching. Enterprise Inference is the dedicated version: your chosen open-weight model on reserved single-tenant capacity, no shared pools, with data residency and guaranteed TPM. For teams running coding agents rather than chat, the Agents API sends runs to any repository over HTTP — create runs, stream logs, open PRs — alongside an agentic CLI terminal that reads your repository conventions and /multi-agent orchestration with a Chairman LLM plus metered Remote Agent cloud sandboxes. Speed is the other half of the pitch. Artificial Analysis verified Blackbox as the #1 Nemotron 3 Ultra provider at 454 tokens/sec in July 2026 — 2.7x cheaper per token than the #2 fastest provider — and a two-model configuration (GPT-5.6 Sol + Opus 4.8) posted 90.2% pass@1 on Terminal-Bench v2.1. Nemotron 3.5 Lightning, announced August 11 2026, starts in about a second and reasons at 1,200 tokens/sec. Billing is per token — input, output, and cached reads metered separately — with no platform fees and no seat charges. You pay through an annual committed token balance signed as a purchase order, metered at published per-model list rates, with the rate improving as committed spend grows. Positioning sits between OpenRouter-style routing and a managed Bedrock or Vertex deployment on compliance, bundled with a coding-agent surface.
Behind the Verdict
Blackbox is best understood as two products sharing one bill. The first is a router: 300+ open and closed models behind an OpenAI-compatible endpoint, with smart routing, failover, and prompt caching that Blackbox says extends a commit 10-20%. If you already run OpenAI-style code, the migration is largely a base-URL change, and the published per-model rates are visible on the pricing page - for example deepseek-v4.1-flash at $0.30 input / $1.20 output per 1M tokens, and moonshotai kimi-k3 at $3.00 / $15.00. The second product is the compliance layer: zero data retention enforced at the gateway and contractual with a DPA on Enterprise, no-training enforcement via provider terms and per-request flags, PII stripped before prompts reach a closed model, end-to-end encryption (ECDH + AES-256-GCM) where nothing readable crosses the wire, plus SAML SSO, SCIM, RBAC, audit logs, and data residency. Where it genuinely differentiates is verified speed. Artificial Analysis named Blackbox the #1 Nemotron 3 Ultra provider at 454 tokens/sec in July 2026, 2.7x cheaper per token than the #2 fastest provider. A two-model config of GPT-5.6 Sol + Opus 4.8 hit 90.2% pass@1 on Terminal-Bench v2.1. Nemotron 3.5 Lightning, announced August 11 2026, starts in roughly a second and reasons at 1,200 tokens/sec. Those are third-party and benchmark numbers, not marketing claims, which is unusually clean for this category. The coding-agent surface is what separates Blackbox from a plain gateway. The Agents API sends coding agents to any repository over HTTP - create runs, stream logs, open PRs - and the agentic CLI reads your repository conventions rather than requiring you to restate them; /multi-agent adds Chairman LLM orchestration and metered Remote Agent cloud sandboxes, with dedicated runners and SSO on Enterprise. The weaknesses are commercial more than technical. Enterprise is the only listed plan, quoted as Custom Annual with PO burn-down, so the pricing page has no self-serve monthly number to compare against. Unused commitment expires at the end of the billing period - Blackbox sends spend alerts at 75% and 90% of your commit, but you still have to size it to minimum usage. Zero data retention and no-training enforcement apply only where the provider API supports them, which is a real boundary when you route to third-party closed models. And agent-produced code can be incorrect or insecure if nobody reviews it. This is a platform for teams with someone to own API keys, routing configs, and agent runs - not a drop-in for a solo developer who wants autocomplete.
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Real-world workflow fit
Concrete scenarios for the personas Blackbox AI actually fits — and what changes day-one when you adopt it.
You point your existing OpenAI SDK code at Blackbox by changing the base URL, then connect your own OpenAI, Anthropic, and Google accounts so traffic routes through them under the gateway's retention flags.
Outcome: One endpoint and one bill replace three provider accounts, and zero data retention plus end-to-end encryption is enforced on every connection rather than argued provider by provider.
You review the Enterprise contract for zero data retention with DPA, PII removal before closed models, SAML SSO, SCIM, RBAC, audit logs, and data residency, then size a committed token balance to your team's minimum usage.
Outcome: The security review closes on documented gateway controls rather than per-provider assurances, and spend alerts at 75% and 90% of the commit keep you from letting balance expire.
You send agent runs to a repository through the Agents API over HTTP — create runs, stream logs, open PRs — while the agentic CLI reads the repo's own conventions and /multi-agent orchestrates with a Chairman LLM.
Outcome: Refactors, test generation, and PRs run unattended at verified throughput (454 t/s on Nemotron 3 Ultra), with a two-model GPT-5.6 Sol + Opus 4.8 config hitting 90.2% pass@1 on Terminal-Bench v2.1.
Use Cases
- Run autonomous coding agents that refactor large codebases, generate tests, and open PRs
- Process sensitive code or data through models with zero retention and end-to-end encryption
- Deploy your chosen open-weight model on single-tenant reserved capacity for compliance
- Route to 300+ models through one endpoint and one bill instead of managing provider accounts
- Integrate coding agent functionality into your own products via the Agents API
- Analyze datasets with a Remote Agent in metered cloud sandboxes
- Track per-token cost across input, output, and cached reads for cost engineering
- Enforce SAML SSO, SCIM, RBAC, and audit logs across inference traffic on Enterprise
Models Under the Hood
as of 2026-09-21
Limitations
- Blackbox is sold as an annual committed token balance under a Custom Annual / PO burn-down contract, so the discount structure assumes you already know your inference volume.
- Unused commitment expires at the end of the billing period — spend alerts fire at 75% and 90% of the commit, but the commitment does not carry forward, so you must size it to your minimum usage.
- Zero data retention and no-training enforcement apply only where the provider API supports them, which matters when you route to third-party closed models.
- PII stripping and end-to-end encryption attributes are tied to the Enterprise agreement, and dedicated deployments, customer-managed keys, and custom contracts require sales engagement.
- Agent workflows (Agents API, agentic CLI) may produce incorrect or insecure code if not reviewed by a human.
as of 2026-10-01
Verification history
We have re-verified Blackbox AI 19 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
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12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Blackbox AI tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
One developer or a small team kicking the tires on the OpenAI-compatible endpoint before committing any budget.
What this tier adds
Starting tier: account creation, API key issuance, Router model catalog access, and CLI/SDK quickstarts.
Enterprise
Custom Annual · PO burn-down
Ideal for
Engineering orgs with a forecastable annual inference volume and a security review to pass — HIPAA/SOC 2 territory with SAML SSO, SCIM, RBAC, and data residency requirements.
What this tier adds
Committed annual token spend metered at published per-model rates, plus closed models −5%+ / open models −10%+ off list, single-tenant Enterprise Inference, PII stripping, PII-free retained-zero contractual terms, and a dedicated forward-deployed engineer at $0.
Where the pricing makes sense
The company stage and team size where Blackbox AI's pricing actually pencils out — and where peers do it cheaper.
Blackbox fits organizations committing real annual inference spend — priced per token with no platform fees and no seats, quoted as Custom Annual on PO burn-down against published list rates (e.g. deepseek-v4.1-flash at $0.30 input / $1.20 output per 1M tokens; moonshotai kimi-k3 at $3.00 / $15.00). Cheaper single-model hosts exist if price alone is the criterion; managed Bedrock or Vertex cost more in procurement friction but offer a vetted hyperscaler contract. Blackbox's differentiation is
Setup time & first value
How long it actually takes to get something useful out of Blackbox AI — broken out by persona, not the marketing-page minute.
For API users already running OpenAI-style code: minutes to first token, since moving onto Blackbox is mostly a base-URL change plus key issuance. For AI platform teams wiring the Agents API, agentic CLI, smart routing, and failover against a real repository: roughly a day of engineering. For Enterprise Inference — dedicated single-tenant deployment, data residency, SAML SSO, SCIM, RBAC, audit
Switching to or from Blackbox AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From OpenRouter: point the same OpenAI-compatible client at Blackbox, then move model strings onto the 300+ model catalog and pick up gateway-enforced zero data retention.
- →From OpenAI directly: change the base URL, keep your request shapes, and optionally connect your existing OpenAI account so traffic routes through it under Blackbox's retention flags.
- →From a managed Bedrock or Vertex deployment: replace the hyperscaler-specific SDK calls with the OpenAI-compatible endpoint and carry over the compliance requirements (data residency, SSO, audit logs) as Enterprise
- →From self-hosted vLLM or TGI: move to Enterprise Inference for the same open-weight model on reserved single-tenant capacity with guaranteed TPM and no pool contention.
- →From a per-seat AI coding assistant: replace seats with the Agents API and agentic CLI, metered per token instead of per head.
- ↗To OpenRouter: keep OpenAI-compatible client code, swap the base URL, and lose the contractual zero-retention guarantee and PII stripping that came with Enterprise.
- ↗To a single-model host: keep the OpenAI-style request format but rebuild routing, failover, and prompt caching yourself, and re-negotiate retention terms with the new provider.
- ↗To managed Bedrock or Vertex: re-implement against hyperscaler SDKs and absorb the procurement that the Blackbox contract avoided.
- ↗To self-hosted open-weight inference: take the same checkpoint you ran on Enterprise Inference and stand it up on your own GPUs, trading guaranteed TPM for operational ownership.
Integrations
Resources & Guides
- Resourceblackbox.ai
BLACKBOX AI
BLACKBOX AI - The Universal Agent Platform. Orchestrate Claude, Codex, Gemini & Blackbox agents from one interface. 30M users, 4.7M+ VS Code installs, 300+ AI models. Free to start.
- Resourceblackbox.ai
Blog
Product news and best practices for teams building with BLACKBOX AI.
- Resourceblackbox.ai
Pricing
Choose a plan that matches your team size and delivery velocity, from individual to enterprise.
Tutorials & Learning
YouTube returned 6 videos for “Blackbox AI”, and we withheld 6: 6 could not be judged, because “Blackbox AI” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Blackbox AI.
Official links
Tools that pair well with Blackbox AI
Common stack mates teams adopt alongside Blackbox AI, with the specific reason each pairing earns its keep.
Cherry Studio
Free open-source desktop AI workbench that runs 300+ cloud and local models in one app
Agnes AI
Free multimodal API gateway from Singapore's Sapiens AI with in-house text, image, video and audio models behind OpenAI-compatible endpoints
OrcaRouter
One OpenAI-compatible endpoint in front of 200+ models, with per-prompt grading that routes each call — and no markup on tokens.
Alternatives to Blackbox AI
View all
Cherry Studio
Free open-source desktop AI workbench that runs 300+ cloud and local models in one app
Agnes AI
Free multimodal API gateway from Singapore's Sapiens AI with in-house text, image, video and audio models behind OpenAI-compatible endpoints
OrcaRouter
One OpenAI-compatible endpoint in front of 200+ models, with per-prompt grading that routes each call — and no markup on tokens.
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