DEPLOYDatabase

AI chip · Tenstorrent

Tenstorrent Blackhole

Next-generation Tenstorrent AI accelerator, positioned above Wormhole in the product stack. Announced 2024.

Market position

Tenstorrent's inference-focused Blackhole. 16 nodes per rack via native ethernet. RISC-V; open-source software stack. Direct pitch against NVIDIA L40S / H100 on inference cost.

DEPLOY editorial. What the vendor PDF cannot tell you.

Physical-AI cross-link

Derived from claims already on record (vendor first-party TDP, throughput, price, and the reference-design cluster registry). The arithmetic is shown per row so it can be audited. No estimated inputs.

Perf per watt
2.48 FP16 TFLOPS/W
745 TFLOPS ÷ 300 W = 2.48

What fits in 32 GB

Weights-only footprint for public open-weight LLMs. Pure arithmetic: params × bytes/param. Excludes KV cache and activation memory; add ~10-30% headroom for real serving. A model that does not fit at FP16 may still fit at INT8 or INT4 with quality trade-offs. Not a benchmark.

ModelParamsFP16INT8INT4
Llama 3.1 8B
dense
8 B16 GB ✓8 GB ✓4 GB ✓
Llama 3.1 70B
dense
70 B140 GB ✗70 GB ✗35 GB ✗
Llama 3.1 405B
dense
405 B810 GB ✗405 GB ✗203 GB ✗
Llama 3.3 70B
dense
70 B140 GB ✗70 GB ✗35 GB ✗
DeepSeek V3
MoE (671B total, 37B active per token)
671 B1342 GB ✗671 GB ✗336 GB ✗
DeepSeek R1
MoE (671B total, 37B active per token)
671 B1342 GB ✗671 GB ✗336 GB ✗
Qwen 2.5 7B
dense
7 B14 GB ✓7 GB ✓4 GB ✓
Qwen 2.5 72B
dense
72 B144 GB ✗72 GB ✗36 GB ✗
Mixtral 8x7B
MoE (46.7B total, 12.9B active per token)
46.7 B93 GB ✗47 GB ✗23 GB ✓
Mixtral 8x22B
MoE (141B total, 39B active per token)
141 B282 GB ✗141 GB ✗71 GB ✗
Gemma 2 27B
dense
27 B54 GB ✗27 GB ✓14 GB ✓
Command R+
dense
104 B208 GB ✗104 GB ✗52 GB ✗
Kimi K2
MoE (1T total, 32B active per token)
1000 B2000 GB ✗1000 GB ✗500 GB ✗

Math: FP16 = params × 2 bytes; INT8 = params × 1 byte; INT4 = params × 0.5 bytes. MoE models sum every expert (full weights on disk), not the per-token active subset.

Common questions

Answer-first, sourced. Every claim below traces to a specific field on this page or a cited datasheet. FAQPage schema is emitted so LLM crawlers can lift these verbatim.

How much does Tenstorrent Blackhole cost?

Tenstorrent Blackhole launch pricing is not on record in the DEPLOY registry. Vendor list prices are typically published in the vendor's own briefing rather than the datasheet.

How much memory does Tenstorrent Blackhole have?

32 GB of GDDR6 at 512 GB/s. Vendor datasheet, first-party.

How much power does one Tenstorrent Blackhole draw?

300 W TDP (thermal design power) per chip. System-level draw is higher: see the reference-design section for rack-level kW.

Which open-weight LLMs fit on one Tenstorrent Blackhole?

Of the 13 public open-weight LLMs DEPLOY tracks: 2 fit at FP16, 3 at INT8, 4 at INT4 (weights only, excludes KV cache). The full table is above with per-model math. Sparsity, offloading and multi-GPU serving change the picture; this row is single-chip weights-only.

Key facts

Class
Compute SoC (AI accelerator)
Designer
Tenstorrent
Safety-critical?
No (data-center inference / training)
Record as of
2026-08-25
Specifications (9 fields, click to expand)

Vendor datasheet figures (first-party). Dense throughput first; sparse (2:4) in parentheses where NVIDIA quotes it. The exhaustive spec sheet lives on the datasheet URL below the table: this row set covers what buyers actually compare on.

Process node
TSMC N6
TDP
300 W
Memory
32 GB GDDR6
Memory bandwidth
512 GB/s
FP16 (dense)
745 TFLOPS
INT8 (dense)
2,980 TOPS
Form factor
PCIe
Announced
2024-07-01
Released
2025-01-01

Source: vendor datasheet

Generation

Compare with

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Sources

Adoption rows appear as we verify chip-integration claims per model. Every row is a public claim the maker or a tier-1 source has stated; verification tier (verified / reported / inferred) is shown per row. See every chip on record for the full catalog or the Tenstorrent record.