Neuron registration trends
The alpha price in τ, day by day, and what moved it each way.
Log change over the last 30 days −28.69%: protocol buys +7.74%, root sells −26.86%, users net −20.32%, cross-subnet +10.76%, unattributed +0.0002%.
The chart follows the alpha price in τ. Each period starts at its opening price and steps through the mechanisms below, in a fixed order, to its closing price: a step that rises pushed the price up, one that falls pushed it down, and its height is how far it moved the price. A thin line carries each close into the next period’s open; it is dashed where the two differ. The faint candle behind each period is the market’s own open, high, low and close, for context.
With many periods on screen (90 days, or hours), the steps would be too thin to read, so the chart draws the price as a line instead and colours each period by the mechanism that moved it most. Hover a period for the full step-by-step breakdown.
Not here, because they do not move the spot price: the per-block TAO injection into the pool, and burns.
All figures are log changes, not simple percentage changes, so the parts add up exactly to the total; on big moves the two differ (a 10% log fall is a 9.5% price fall).
2026-11-09 UTC, as of ≈23:39 UTC (block 9,471,983)
The day isn’t over yet, so these figures keep changing. They are in no daily total, average or rank.
Enterprises running sensitive AI workloads face a choice between security, cost, and trust. Proprietary cloud infrastructure exposes models and data in memory; centralized providers are single points of failure; custom on-premise deployments require capital and expertise. A decentralized network of hardware-isolated compute nodes could address all three — but only if the nodes prove their isolation is real and the incentives are aligned to keep them honest.
A properly-incentivized network of contributors can operate distributed compute infrastructure where isolation is cryptographically verifiable and scores from an independent referee who watches for compliance. Contributors (miners) earn rewards for providing attested confidential capacity; consumers pay per compute unit used; a validator checks both sides against public competitor benchmarks and publishes evidence so anyone can audit the scoring.
KubeTEE operates such a network on Bittensor Subnet 90.
Miners register multi-node GPU clusters (one cluster per hotkey) running Kubernetes with Kata Containers and Confidential Containers in TEE mode (Intel TDX, NVIDIA CC, AMD SEV-SNP). A subnet-owned validator reads cluster readiness from Rancher inventory, normalizes miner compensation in USD against live Targon supply-side payouts, and sets weights each epoch. AI services (inference, agents, batch jobs) run as confidential pods with CoCo remote attestation; clients can request cryptographic proof a response came from an attested TEE guest. The LiteLLM gateway terminates TLS passthrough inside the TEE itself and routes via attestation-gated mTLS to GPU backends or external providers.
Auto-generated from the GitHub repository and may not reflect the latest changes.
KubeTEE AI Factory is a decentralized confidential computing infrastructure for SOTA AI services on Bittensor, running inference, agents, and batch jobs inside hardware-isolated Trusted Execution Environments (TEE) using Kata Containers and Confidential Containers on Intel TDX and NVIDIA CC GPUs across multi-cluster RKE2 Kubernetes.
KubeTEE is a decentralized multi-cluster Kubernetes (RKE2 + Rancher Fleet) infrastructure with a subnet-owner control plane (Validator, Armada Server) and per-miner clusters (Armada Executor, GPU Operator, Kata/CoCo TEE runtime). Miners register one cluster per hotkey; the validator reads Rancher inventory, scores miner infrastructure readiness and USD-equivalent compensation, and sets weights once per epoch. AI services (inference, agents, batch jobs) run as confidential pods under TEE runtime classes (kata-qemu-nvidia-gpu-tdx-runtime-rs for GPU, kata-qemu-tdx-runtime-rs for CPU-only Intel TDX) with CoCo remote attestation proving the guest is unmodified.
The LiteLLM gateway (running in TEE itself) terminates client TLS passthrough and routes to in-cluster NIM/SGLang backends via attestation-gated mTLS or to external providers (sayGM/SN28 idle-capacity channel, TEE fallbacks Chutes/Phala/Near AI). Armada multi-cluster batch scheduler dispatches confidential jobs across miner clusters with fair-use queuing and gang scheduling.
The validator implements a single Infrastructure mechanism in Early Access: (1) binary infrastructure-readiness verdict per miner hotkey; (2) USD-denominated compensation target computed from Taostats TAO/USD feed, on-chain alpha→TAO price (mg.price), GPU price card, and miner capacity; (3) Targon supply-side payout feed (stats.targon.com/api/miners) clamps the card downward, floored at 0.75×card per GPU class; (4) weights normalized per miner and set on-chain; unmined capacity is weighted to the owner UID which under recycle_or_burn=recycle returns to unissued supply. Future scoring dimensions (Phase 1+) include TEE attestation, Armada job metrics, and price-competitiveness against Lium/Chutes.
The sections above were auto-generated from the GitHub repository and may not reflect the latest changes. View repository (github.com, opens in a new tab, external site)
KubeTEE AI Factory: Confidential Computing TEE Multi-Cluster K8s
https://x.com/KubeTEEAI (x.com, opens in a new tab, external site) — Enterprise-Grade AIaaS with FIPS-140-3 Federal-Grade Security
This information was auto-extracted from the GitHub repository and may be incomplete or out of date. Always refer to the subnet's GitHub repository (github.com, opens in a new tab, external site) for the latest instructions.
Not yet verified: GPU, GPU count, Storage, OS, Notes
Not yet verified: Notes
Machine-extracted from the subnet's repository docs; may be wrong or out of date. Check the repository before buying or renting hardware. Open the repository (github.com, opens in a new tab, external site) · Extracted 9 Nov 2026
Verify Ubuntu 26.04 LTS and absence of NVIDIA drivers
lsb_release -ds && command -v nvidia-smi || echo 'PASS: no NVIDIA driver installed'
Apply BIOS Phase 1 base performance and platform attributes
# Configure BIOS Phase 1 (base performance): SysProfile=PerfOptimized, NodeInterleave=Disabled, ProcX2Apic=Enabled, CpuPaLimit=Disabled, IntelTxt=Off, TpmSecurity=On, EnergyPerformanceBias=MaxPower
Apply BIOS Phase 2 TDX base configuration
# Configure BIOS Phase 2 (TDX base): MemoryEncryption=MultipleKeys, EnableTdx=Enabled, KeySplit=1, EnableTdxSeamldr=Enabled, IntelSgx=On
Apply BIOS Phase 3 TME and SGX configuration; CRITICAL: ensure SgxAutoRegistrationAgent is Disabled
# Configure BIOS Phase 3 (TME + SGX): GlbMemIntegrity=Disabled, PrmrrSize=2G, SgxAutoRegistrationAgent=Disabled, SgxPackageInfoInBandAccess=On
Verify OS disk >784 GB usable and data drives >3.84 TB each, unformatted, totaling >7 TB
lsblk -o NAME,SIZE,TYPE,FSTYPE,MOUNTPOINTS,MODEL && findmnt
Grant KubeTEE SSH access with the provided public key and configure passwordless sudo
export KUBETEE_SSH_PUBLIC_KEY='<SSH-PUBLIC-KEY-PROVIDED-BY-KUBETEE>' && printf '%s\n' "$KUBETEE_SSH_PUBLIC_KEY" | ssh-keygen -l -f - && install -d -m 700 -o ubuntu -g ubuntu /home/ubuntu/.ssh && touch /home/ubuntu/.ssh/authorized_keys && chown ubuntu:ubuntu /home/ubuntu/.ssh/authorized_keys && chmod 600 /home/ubuntu/.ssh/authorized_keys && printf '%s\n' "$KUBETEE_SSH_PUBLIC_KEY" >> /home/ubuntu/.ssh/authorized_keys && printf 'ubuntu ALL=(ALL) NOPASSWD:ALL\n' | sudo visudo -cf /dev/stdin >/dev/null && printf 'ubuntu ALL=(root) NOPASSWD:ALL\n' | sudo tee /etc/sudoers.d/90-kubetee-ubuntu >/dev/null && sudo visudo -cf /etc/sudoers.d/90-kubetee-ubuntu >/dev/null && sudo chmod 0440 /etc/sudoers.d/90-kubetee-ubuntu && sudo -n true
Update and validate GPU firmware and VBIOS before handoff to KubeTEE
# Update GPU firmware and VBIOS using OEM/HGX or DGX procedure; verify all GPUs meet compatibility requirements per GPU-NODE-REQUIREMENTS.md
Configure remote power management for KubeTEE automated recovery
# Arrange remote cold-reboot access (Redfish preferred, or IPMI / power-management API) and provide credentials securely to KubeTEE onboarding operator
Hand off to KubeTEE for automated host preparation, storage formatting, GPU configuration, and RKE2 registration
# Contact KubeTEE with cluster details; KubeTEE performs automated host preparation and RKE2 registration
Install Bittensor SDK (validator requires >=11.0.1 for collateral support)
pip install bittensor>=11.0.1
Set validator collateral gate environment variables (Early Access configuration)
# Configure KUBETEE_COLLATERAL_REQUIRED_TAO=0 (disabled in Early Access), KUBETEE_COLLATERAL_ENFORCE=false, KUBETEE_COLLATERAL_GRACE_CYCLES=3, KUBETEE_COLLATERAL_RECOVERY_MARGIN=0.05
Deploy validator v1 from the repository
# Read validator code from validator/ directory; validator v1 is built and live on Finney
Configure external price feed sources for compensation and competitive pricing
# Configure Taostats TAO/USD price feed and Targon stats.targon.com API endpoints for competitive pricing
Configure Rancher authentication using Bittensor hotkey challenge signing
# Set up Rancher v3 API client with Bittensor hotkey signing for miner cluster read access
Run the validator; it reads metagraph, enumerates clusters via Rancher, reconciles infrastructure readiness, computes USD-denominated compensation target, and sets weights once per epoch
python validator/main.py
| Day (UTC) | Share |
|---|---|
| 2026-11-08 | 1.85% |
| 2026-11-07 | 1.89% |
| 2026-11-06 | 1.90% |
| 2026-11-05 | 1.83% |
| 2026-11-04 | 1.86% |
| 2026-11-03 | 1.94% |
| 2026-11-02 | 1.99% |
| 2026-11-01 | 2.02% |
| 2026-10-31 | 2.03% |
| 2026-10-30 | 1.95% |
| 2026-10-29 | 1.92% |
| 2026-10-28 | 1.96% |
| 2026-10-27 | 1.86% |
| 2026-10-26 | 1.95% |
| 2026-10-25 | 2.15% |
| 2026-10-24 | 2.13% |
| 2026-10-23 | 2.22% |
| 2026-10-22 | 2.36% |
| 2026-10-21 | 2.51% |
| 2026-10-20 | 2.56% |
| 2026-10-19 | 2.41% |
| 2026-10-18 | 2.44% |
| 2026-10-17 | 2.53% |
| 2026-10-16 | 2.60% |
| 2026-10-15 | 2.70% |
| 2026-10-14 | 2.64% |
| 2026-10-13 | 2.45% |
| 2026-10-12 | 2.37% |
| 2026-10-11 | 2.49% |
| 2026-10-10 | 2.64% |
| 2026-10-09 | 2.68% |
| 2026-10-08 | 2.65% |
| 2026-10-07 | 2.55% |
| 2026-10-06 | 2.57% |
| 2026-10-05 | 2.60% |
| 2026-10-04 | 2.55% |
| 2026-10-03 | 2.65% |
| 2026-10-02 | 2.57% |
| 2026-10-01 | 2.53% |
| 2026-09-30 | 2.59% |
| 2026-09-29 | 2.66% |
| 2026-09-28 | 2.53% |
| 2026-09-27 | 2.46% |
| 2026-09-26 | 2.68% |
| 2026-09-25 | 2.86% |
| 2026-09-24 | 2.88% |
| 2026-09-23 | 2.73% |
| 2026-09-22 | 2.71% |
| 2026-09-21 | 2.77% |
| 2026-09-20 | 3.12% |
| 2026-09-19 | 2.88% |
| 2026-09-18 | 3.01% |
| 2026-09-17 | 3.22% |
| 2026-09-16 | 3.27% |
| 2026-09-15 | 1.72% |
| 2026-09-14 | 1.17% |
| 2026-09-13 | 0.56% |
| 2026-09-12 | 0.47% |
| 2026-09-11 | 0.42% |
| 2026-09-10 | 0.35% |
| 2026-09-09 | 0.17% |
| 2026-09-08 | 0.00% |
| 2026-09-07 | 0.00% |
| 2026-09-06 | 0.00% |
| 2026-09-05 | 0.00% |
| 2026-09-04 | 0.00% |
| 2026-09-03 | 0.00% |
| 2026-09-02 | 0.00% |
| 2026-09-01 | 0.00% |
| 2026-08-31 | 0.00% |
| 2026-08-30 | 0.00% |
| 2026-08-29 | 0.00% |
| 2026-08-28 | 0.00% |
| 2026-08-27 | 0.00% |
| 2026-08-26 | 0.00% |
| 2026-08-25 | 0.00% |
| 2026-08-24 | 0.00% |
| 2026-08-23 | 0.00% |
| 2026-08-22 | 0.00% |
| 2026-08-21 | 0.00% |
| 2026-08-20 | 0.00% |
| 2026-08-19 | 0.00% |
| 2026-08-18 | 0.00% |
| 2026-08-17 | 0.00% |
| 2026-08-16 | 0.00% |
| 2026-08-15 | 0.00% |
| 2026-08-14 | 0.00% |
| 2026-08-13 | 0.00% |
| 2026-08-12 | 0.00% |
| 2026-08-11 | 0.00% |
