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DUE DILIGENCE

Tenstorrent Blackhole: Performance Claims, Open Stack, and Due-Diligence Risks

Vendor benchmarks, PyTorch and Hugging Face compatibility, and the diligence checklist AGICY applies before Phase 1 fleet scale-up.

Published: July 12, 2026Read Time: 12 minBy AGICY Research
tenstorrent blackhole performance risks
Research disclaimer: Throughput and $/token figures below are vendor-claimed unless marked verified. AGICY will publish independent SC-36-class benchmarks pre-full commercial operation. This document is illustrative due diligence — not investment advice or a procurement guarantee.

Tenstorrent reports ~350 tok/s on DeepSeek-R1-class inference at roughly ~$6/M tokens — compared to ~$30/M on GB300-class systems in vendor presentations. The open stack (RISC-V, PyTorch, Hugging Face) is compelling for sovereign campuses, but SDK maturity, yield, firmware stability, and leadership continuity remain standard pre-production risks requiring independent validation.

Key Takeaways

  • DeepSeek-R1 benchmark:~350 tok/s on Galaxy-class hardware (vendor-claimed); ~$6/M tokens vs ~$30/M on GB300-class (vendor comparison).VENDOR-CLAIMED
  • Open ISA: RISC-V enables firmware and microcode audit for EU regulated workloads.VERIFIED
  • Framework compatibility: PyTorch and Hugging Face model import claimed for mainstream open-weight models.VENDOR-CLAIMED
  • SDK maturity risk: TT-Metalium / TT-Forge toolchain still maturing vs decade-old CUDA ecosystem.DESIGN TARGET
  • Yield & firmware: New process nodes and multi-chip Galaxy integration require burn-in and OTA stability programmes.DESIGN TARGET
  • Leadership continuity: Emerging silicon vendors face key-person and roadmap execution risk — standard vendor DD.DESIGN TARGET
  • AGICY contingency:Phase 1 delay triggers interim AMD MI300X air-cooled racks per vendor-neutral policy.VERIFIED

Performance Claims: DeepSeek-R1 and $/Token Economics

Tenstorrent's public Galaxy demonstrations highlight DeepSeek-R1 inference — a reasoning-heavy open model relevant to education, research, and public-sector analytics. Vendor materials cite approximately 350 tokens per second sustained decode on Galaxy configurations, with implied economics near $6 per million output tokens.

The comparison baseline in vendor decks — GB300-class GPU systems at roughly $30/M tokens — is illustrative. AGICY treats all vendor-side comparisons as hypotheses until reproduced on identical batch sizes, context lengths, and power meters in Vasilikos acceptance testing.

~350 tok/s
DeepSeek-R1 inference (vendor-claimed)

~$6/M output tokens vs ~$30/M on GB300-class systems in Tenstorrent marketing comparisons. AGICY Phase 1 fleet model uses 300 tok/s sustained fleet-average for capacity planning — conservative vs peak vendor demos.VENDOR-CLAIMED

Open Stack: RISC-V, PyTorch, Hugging Face

Sovereign buyers care as much about software portability as raw speed. Tenstorrent ships TT-Metalium and TT-Forge alongside PyTorch integration paths, with stated compatibility for Hugging Face model hubs — reducing the friction of deploying Llama, Mistral, and DeepSeek-class weights on EU soil.

  • RISC-V: Open ISA supports third-party security review — aligned with AGICY auditability gate.
  • PyTorch-first: Matches AGICY training/serving policy — no mandatory proprietary graph compiler.
  • Model agnosticism: Client BYOM supported; AGICY does not require exclusive model hosting.

Maturity gap remains: CUDA's library depth (cuDNN, NCCL, TensorRT) accumulated over fifteen years. TT-Forge must prove parity on your models — not benchmark charts alone.

Due-Diligence Risk Register

RiskDescriptionAGICY Mitigation
SDK maturityToolchain gaps vs CUDA for exotic ops and custom layersPre-COD model compatibility matrix; vLLM-class fallbacks
Yield / firmwareMulti-chip Galaxy integration and early-node defect rates50-unit spare pool; staged burn-in per deployment plan
Leadership continuityKey-person dependency in emerging silicon vendorsTechnology Committee quarterly review; multi-vendor slots
Benchmark inflationVendor peak vs fleet-sustained throughput divergence300 tok/s fleet-average in published basis; independent acceptance tests

What Independent Validation Must Prove

Before AGICY publishes customer-facing SLAs on Galaxy capacity, the Technology Committee requires:

  1. Reproducible throughput on target models at 65% fleet utilisation (Phase 1 management case).
  2. Power draw verification at 9 kW unit TDP × 1.15 PUE design point.
  3. Failover behaviour across Ethernet scale-out under single-rack loss.
  4. TT-Forge compile success rate for top-20 client model architectures.

Until those gates pass, public headline capacity remains 17T tokens/year as a target derived from deterministic fleet math — not a vendor marketing claim.DESIGN TARGET

AGICY Relevance

AGICY selects Galaxy for Phase 1 because it passes preliminary four-gate review — but selection is conditional on ongoing diligence, not faith in keynote slides.

Civil workloads (healthcare triage, university LLM sandboxes, municipal digital services) benefit from open-weight models on auditable RISC-V hardware — provided SDK and firmware risks are actively managed.

Per AGICY's vendor-neutral policy, shipment delay triggers interim AMD MI300X racks; superior TCO from any vendor triggers integration — AGICY never becomes captive to Tenstorrent roadmap timing.

Request Diligence Briefing

Institutional buyers can access AGICY's Technology Committee summary, fleet acceptance criteria, and vendor-neutral contingency plan under NDA.

Contact Investor Relations

References & Primary Sources

  1. Tenstorrent — Galaxy GA announcements and DeepSeek-R1 demo materials (2026).
  2. AGICY Galaxy fleet specification — fleet-average 300 tok/s basis.
  3. AGICY vendor-neutral policy — stress-test and exit ramps.
  4. AGICY token-fleet basis note — 17T vs 38.5T public narrative.
  5. AGICY Research synthesis — Jim Keller / Blackhole video keypoints (Jul 2026).

§ FIN — Close of Document

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