AI chip · Google
Google TPU v5p
Performance-tier TPU v5 generation, aimed at large-model training; ~2x compute vs TPU v4.
On the DEPLOY graph: 1 campus carry a cited inventory line for it · 1 reference-design cluster include it.
Market position
v5p is the flagship of Google's fifth TPU generation, engineered for peak training throughput at 8,960-chip pod scale. Gemini 1.0 and 1.5 trained on it. v6p (Ironwood) is the announced successor; v6e (Trillium) is the inference-optimised sibling.
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
- 1.53 BF16 TFLOPS/W459 TFLOPS ÷ 300 W = 1.53
- Cooling class (across reference designs)
- waterObserved across 1 reference-design cluster containing this chip
What fits in 95 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.
| Model | Params | FP16 | INT8 | INT4 |
|---|---|---|---|---|
| Llama 3.1 8B dense | 8 B | 16 GB ✓ | 8 GB ✓ | 4 GB ✓ |
| Llama 3.1 70B dense | 70 B | 140 GB ✗ | 70 GB ✓ | 35 GB ✓ |
| Llama 3.1 405B dense | 405 B | 810 GB ✗ | 405 GB ✗ | 203 GB ✗ |
| Llama 3.3 70B dense | 70 B | 140 GB ✗ | 70 GB ✓ | 35 GB ✓ |
| DeepSeek V3 MoE (671B total, 37B active per token) | 671 B | 1342 GB ✗ | 671 GB ✗ | 336 GB ✗ |
| DeepSeek R1 MoE (671B total, 37B active per token) | 671 B | 1342 GB ✗ | 671 GB ✗ | 336 GB ✗ |
| Qwen 2.5 7B dense | 7 B | 14 GB ✓ | 7 GB ✓ | 4 GB ✓ |
| Qwen 2.5 72B dense | 72 B | 144 GB ✗ | 72 GB ✓ | 36 GB ✓ |
| Mixtral 8x7B MoE (46.7B total, 12.9B active per token) | 46.7 B | 93 GB ✓ | 47 GB ✓ | 23 GB ✓ |
| Mixtral 8x22B MoE (141B total, 39B active per token) | 141 B | 282 GB ✗ | 141 GB ✗ | 71 GB ✓ |
| Gemma 2 27B dense | 27 B | 54 GB ✓ | 27 GB ✓ | 14 GB ✓ |
| Command R+ dense | 104 B | 208 GB ✗ | 104 GB ✗ | 52 GB ✓ |
| Kimi K2 MoE (1T total, 32B active per token) | 1000 B | 2000 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 Google TPU v5p cost?
Google TPU v5p 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 Google TPU v5p have?
95 GB of HBM2e at 2,765 GB/s. Vendor datasheet, first-party.
How much power does one Google TPU v5p draw?
300 W TDP (thermal design power) per chip. System-level draw is higher: see the reference-design section for rack-level kW.
Which data centers have Google TPU v5p?
1 campus on the DEPLOY registry carry a cited inventory line for this chip. Full list below with per-campus quantity hints where published.
Which open-weight LLMs fit on one Google TPU v5p?
Of the 13 public open-weight LLMs DEPLOY tracks: 4 fit at FP16, 7 at INT8, 9 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
- Safety-critical?
- No (data-center inference / training)
- Record as of
- 2026-08-25
- Latest cited claim
- 2024-01-01 (across 2 inventory + benchmark rows)
Specifications (8 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.
- TDP
- 300 W
- Memory
- 95 GB HBM2e
- Memory bandwidth
- 2,765 GB/s
- BF16 (dense)
- 459 TFLOPS
- INT8 (dense)
- 918 TOPS
- Form factor
- OAM (per-chip in v5p pod)
- Announced
- 2023-12-06
- Released
- 2024-01-01
Source: vendor datasheet
Generation
Used in reference designs
The named rack-scale and pod-scale designs buyers actually order that contain this chip.
- ×8,960Google TPU v5p Pod (8,960 chips)supercluster
Compare with
Benchmarks
Published measurements per workload. Vendor datasheet numbers are first-party (verified posture); MLPerf / InferenceX / press results come in when their license terms + workload naming permit.
| Workload | Value | Unit | Source | As of |
|---|---|---|---|---|
| peak tflops bf16 | 459 | TFLOPS | vendor | 2023-12-01 |
Data centers stocking Google TPU v5p
Who has the most? →Every campus on the DEPLOY registry with a public claim of Google TPU v5p on site. Quantity hints are unstructured because underlying disclosures vary by order of magnitude.
- Google The Dalles Data Center Campusas of 2024-01-01partially energizedreported
TPU v5p available in us-east5 (Columbus) + us-central1 (Iowa) + us-central2 (Oklahoma) — The Dalles hosts related pods
Sources
- Cloud TPU v5pGoogle Cloud
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 Google record.