01enterprise · live
OpenRouter
enterprise tier · drop-in
“Drop-in OpenAI-compatible endpoint with verifiable, no-log routing. The receipt is the audit trail.”
18B+ tokens
no-log · verified routing
Private inferentie
Inference zonder de prompt bloot te geven.
OpenAI-compatibel. Ondertekende ontvangstbewijzen. Geen logs, by design.
je gedachten blijven van jou
Private LLM catalog
Frontier models with private runtime.
OpenAI-compatible models with hardware-backed privacy and ACI verification. Keep your SDK flow, change the endpoint, and copy the real call when you need it.
DeepSeek: DeepSeek V4.1 Flash 1017
Beta
1.0M context
$0.75/M input
$1.60/M output
$0.15/M cache read
Phala: Qwen3.8 27B Uncensored (Aggressive)
262K context
$0.30/M input
$1.50/M output
$0.05/M cache read
Z.ai: GLM 5.3 Flash
Beta
1.0M context
$0.15/M input
$0.50/M output
$0.03/M cache read
Qwen: Qwen3.8 27B
Beta
1M context
$0.20/M input
$2.50/M output
$0.05/M cache read
DeepSeek: DeepSeek V4 Flash 0731
1.0M context
$0.44/M input
$1.32/M output
$0.028/M cache read
MoonshotAI: Kimi K3
1.0M context
$3.00/M input
$15.00/M output
$0.30/M cache read
Google: Gemma 4 31B
262K context
$0.15/M input
$0.46/M output
$0.075/M cache read
Model requests are routed through confidential AI providers with TEE support.
Check allPrivate inference, by construction.
What you say to the model stays between your client and an attested CVM. Three primitives — encryption, TEE, no-logs — make that a property of the build, not a promise.
Encrypted into the TEE
- Encrypted on both hops, each channel key bound to attestation
- RA-TLS terminates inside the CVM, not at a load balancer
- No plaintext intermediary on the host
Hoe het werkt
Loop stap voor stap door één request, end-to-end.
Schakel dstack uit om precies te zien welke garantie verdwijnt.
Private inference op dstack
ACI gateway attestation, signed receipts, and verified upstream model sessions
actieve edgeinactiefnieuw in stap
stap 1 of 5 · scroll-aware1
Stap 1 / 5Verifieer de build vóórdat u één byte verzendt
Client SDK fetches the gateway’s TDX quote with a fresh nonce and runs dcap-qvl locally — when the caller pins accepted compose hashes, it confirms the measured release is one of them. The trust decision is client-side; Phala is not asked to vouch for itself.
With dstack: De gebruiker houdt de trust root vast, verankerd in de hardware-handtekening van Intel TDX.
Zelfde SDK. Zelfde endpoints. Confidential by default.
cURL · direct inzetbaar
Hit inference.phala.com/v1/chat/completions with the OpenAI request shape. Receipt headers come back on every response — even from curl.
cURL
$ curl https://inference.phala.com \/v1/chat/completions \-H "Authorization: …" \-d '{"model":…}'x-receipt-id: rcpt-e0ee..x-aci-keyset-digest: sha256:3eff..
PYTHON
from openai import OpenAIc = OpenAI(base_url="…phala.com/v1",api_key=os.environ["PHALA_AI_API_KEY"])r = c.chat.completions.create(…)
OpenAI Python SDK
`base_url="https://inference.phala.com/v1"` and you’re done. Existing code keeps working; capture x-receipt-id from the raw response when you need proof.
Eén uniforme verifier
Every route returns the same ACI artifacts: a gateway attestation report, a signed receipt, and an attested-session reference for the serving upstream.
UNIFIED PROOF
unified verifierall match
TinfoilDeepSeek V4.1 Flash 1017PhalaKev 4B
0G Private ComputerGLM 5.3
Near AIGLM 5.3 Flash
ChutesQwen3.8 27Bone format · any provider
OPENROUTER
openrouter · phala2026-10-26
41.2Btokens / day
models with traffic10
sourceopenrouter.ai/provider/phala
Live on OpenRouter
Phala serves confidential models as a provider on OpenRouter. The daily token count comes from OpenRouter’s public Phala provider page.
two-hop RA-TLS · TLS key bound to TDX quote
tunneled · no plaintext intermediary
hop 01 · client → gateway
inference.phala.comSPKI in gateway report
hop 02 · gateway → model CVM
Phala model CVMSPKI in model quote
RA-TLSSPKI pinX.509tunneled
RA-TLS over twee hops, helemaal tot aan het model
The first TLS hop terminates inside the gateway CVM, whose TLS key is bound to its TDX quote. For Phala-hosted models, the second terminates inside the model CVM, whose TLS key is bound to its own quote. Other providers bind the second hop to keys from their own evidence. There is no plaintext intermediary on the host.
response · /v1/chat/completions
200x-receipt-idrcpt-e0eefe…x-aci-identitysha256:3def…x-aci-keyset-digestsha256:3eff…sessionupstream.verified
verify receiptmatches attestation
Signed receipt + attested session, every response
Every response carries x-receipt-id. Fetch the ACI receipt, verify its signature and response hash against a fresh gateway attestation, then follow upstream.verified.session_id when you need deeper audit evidence.
in production today · 3 live partners
Confidential inference, in production.
OpenRouter routes its enterprise tier through Phala. NEAR AI ships verifiable agent inference. OODA AI runs decentralized GPU TEE.
02web3 · live
NEAR AI
verifiable agent inference
“Verifiable agent inference for autonomous, on-chain workflows. Every model call lands on-chain with proof.”
100% receipts
on-chain verified · zk inference
03public-co · live
OODA AI
NASDAQ-listed · decentralized GPUs
“Decentralized GPUs with hardware attestation guarantees. No host root, no off-band access, no policy promises.”
12M tokens / day
TDX + H100 · hardware-attested
OpenAI-compatible
drop-in /v1 surface
TDX + H100/H200/B300
CPU + GPU TEE
5–15% overhead
vs bare-metal
No host root
compose-hash IS the policy
AI-oplossingspaden
Gebruik privé-modellen waar AI met geheimen werkt.
Het endpoint voor het privé-model is het eerste toegangspunt. Hetzelfde privacy-gebouwblok breidt zich uit naar agents, datastromen en training.
Agents
Privé AI-agents
Laat agents draaien met sleutels, tools, geheugen en acties binnen een geverifieerde runtime in plaats van een zichtbare automation cloud.
Training
Privémodeltraining
Pas modellen aan op propriëtaire data terwijl datasets, gradients, checkpoints en evaluatietraces binnen de grens blijven.
private training run
Observe without exposing weights.
01
dataset
sealed
02
fine-tune
running
03
eval
private
04
checkpoint
verified
loss curve
proof attached
attestation.json
Data
Privé AI-data
Verplaats modellen naar gevoelige records en geef goedgekeurde outputs terug zonder ruwe data bloot te stellen aan de modeloperator.
source
EHR data
source
Customer records
source
Internal docs
TEE clean room
query without raw access
approved output
aggregate only
no row exportproof linked
Deploy private inference
OpenAI-compatible. Attested. Receipt-backed.
Drop in with the OpenAI SDK you already use. Point at inference.phala.com and capture x-receipt-id for the signed ACI receipt.
- 01OpenAI-compatible base URL
- 02TDX + H100 / H200 / Blackwell
- 03Signed ACI receipt per response
- 04Gateway attestation + upstream sessions
- 055–15% TEE overhead vs bare-metal
Private uitvoering. Verifieerbare resultaten.
Nieuwsbrief
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