AI chip · Groq
Groq LPU (Language Processing Unit)
Deterministic-compilation inference accelerator optimized for low-latency LLM token generation; SRAM-based memory architecture.
Market position
The inference speed record-holder: Llama 70B at 500+ tokens/sec per user through 2024, an order of magnitude ahead of anyone else, by moving all weights into SRAM. Zero HBM, deterministic latency. Weakness: no training, and per-chip capacity is small so real deployments need dozens of racks.
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
- 0.50 FP16 TFLOPS/W188 TFLOPS ÷ 375 W = 0.50
What fits in 0.23 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 Groq LPU (Language Processing Unit) cost?
Groq LPU (Language Processing Unit) 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 Groq LPU (Language Processing Unit) have?
0.23 GB of SRAM (230 MB on-die) at 80,000 GB/s. Vendor datasheet, first-party.
How much power does one Groq LPU (Language Processing Unit) draw?
375 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 Groq LPU (Language Processing Unit)?
Of the 13 public open-weight LLMs DEPLOY tracks: 0 fit at FP16, 0 at INT8, 0 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
- Groq
- 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
- GlobalFoundries 14nm
- TDP
- 375 W
- Memory
- 0.23 GB SRAM (230 MB on-die)
- Memory bandwidth
- 80,000 GB/s
- FP16 (dense)
- 188 TFLOPS
- INT8 (dense)
- 750 TOPS
- Form factor
- PCIe (GroqCard) / rack-scale GroqRack
- Announced
- 2020-01-01
- Released
- 2021-06-01
Source: vendor datasheet
Compare with
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 Groq record.