Models / pplx-embed-v2-late-9b

Late interaction goes local. Perplexity’s pplx-embed-v2-late-9b (October 7, 2026, MIT) is an 8.39B late-interaction embedding model on the Qwen3.5 backbone: 32 layers, 4 KV heads x 256 head-dim, a 262,144-token context. Late-interaction retrieval keeps one vector per token instead of pooling into one vector, which buys recall on long documents at the cost of storing more vectors; the 9B size makes the trade affordable on a workstation rather than a cluster.

The MIT license does the differentiating. The v2 line’s smaller sibling (0.6B) covers the low end; against this site’s current local-RAG default, EmbeddingGemma 2 at 744M, the 9B late-interaction build is the upgrade path for retrieval stacks with money for an A100-class card or a 24GB unit at 16.8GB fp16. 467 downloads in the first days: early, but the license means no friction when the retrieval-benchmark posts arrive.

embeddings retrieval rag
Parameters
8.4B
Context
262k
License
mit
Developer
Perplexity
Origin
🇺🇸 USA
Released
Oct 2026

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Run it locally

Per-quant memory needs and a static "can you run it?" reference - no rig entry required

FP16
16.8GB 17.0GB min 24.0GB rec
Full quality, largest

The reference hardware

Schematic of the NVIDIA Jetson Orin NX 16GB reference rig - 16GB unified memory, 102 GB/s aggregate bandwidth
Schematic of the Single GTX 1080 Ti (11GB) reference rig - 11GB VRAM, 484 GB/s aggregate bandwidth
Schematic of the 4x H100 80GB (320GB) reference rig - 320GB VRAM, 13400 GB/s aggregate bandwidth
Schematic of the NVIDIA DGX Station 748GB reference rig - 748GB unified memory, 8000 GB/s aggregate bandwidth
Schematic of the 8x RTX 3090 rack (192GB) reference rig - 192GB VRAM, 7489 GB/s aggregate bandwidth
Schematic of the 4x RTX 5090 (128GB) reference rig - 128GB VRAM, 7168 GB/s aggregate bandwidth
Schematic of the AMD Instinct MI300X (192GB) reference rig - 192GB VRAM, 5324 GB/s aggregate bandwidth
Schematic of the 4x RTX 4090 (96GB) reference rig - 96GB VRAM, 4032 GB/s aggregate bandwidth
Schematic of the 2x RTX 5090 (64GB) reference rig - 64GB VRAM, 3584 GB/s aggregate bandwidth
Schematic of the 2x RTX 3090 (48GB) reference rig - 48GB VRAM, 1872 GB/s aggregate bandwidth
Schematic of the Single RTX 5090 (32GB) reference rig - 32GB VRAM, 1792 GB/s aggregate bandwidth
Schematic of the RTX PRO 6000 Blackwell (96GB) reference rig - 96GB VRAM, 1792 GB/s aggregate bandwidth
Schematic of the Mac Studio M4 Ultra 192GB reference rig - 192GB unified memory, 1092 GB/s aggregate bandwidth
Schematic of the Mac Studio M4 Ultra 512GB reference rig - 512GB unified memory, 1092 GB/s aggregate bandwidth
Schematic of the Single RTX 4090 (24GB) reference rig - 24GB VRAM, 1008 GB/s aggregate bandwidth
Schematic of the MacBook Pro M5 Max 128GB reference rig - 128GB unified memory, 614 GB/s aggregate bandwidth
Schematic of the Dual EPYC 9004 + 768GB DDR5-4800 reference rig - 768GB unified memory, 460 GB/s aggregate bandwidth
Schematic of the DGX Spark 128GB unified reference rig - 128GB unified memory, 273 GB/s aggregate bandwidth
Schematic of the Ryzen AI Max+ 395 128GB reference rig - 128GB unified memory, 256 GB/s aggregate bandwidth
Schematic of the Jetson AGX Orin 64GB reference rig - 64GB unified memory, 204 GB/s aggregate bandwidth
Schematic of the Epyc + 512GB DDR4-3200 + 2x RTX 3090 reference rig - 560GB unified memory, 204 GB/s aggregate bandwidth
Schematic of the Epyc + 512GB DDR4-2400 + 2x RTX 3090 reference rig - 560GB unified memory, 153 GB/s aggregate bandwidth

22 reference configs, drawn in-house. Scroll for more.

Can you run it? - reference rigs

Rig FP16
NVIDIA Jetson Orin NX 16GB no -> cloud
Single GTX 1080 Ti (11GB) offload
4x H100 80GB (320GB) fast 425.7t/s
NVIDIA DGX Station 748GB fast 254.2t/s
8x RTX 3090 rack (192GB) fast 237.9t/s
4x RTX 5090 (128GB) fast 227.7t/s
AMD Instinct MI300X (192GB) fast 169.2t/s
4x RTX 4090 (96GB) fast 128.1t/s
2x RTX 5090 (64GB) fast 113.9t/s
2x RTX 3090 (48GB) fast 59.5t/s
Single RTX 5090 (32GB) fast 56.9t/s
RTX PRO 6000 Blackwell (96GB) fast 56.9t/s
Mac Studio M4 Ultra 192GB fast 37.9t/s
Mac Studio M4 Ultra 512GB fast 37.9t/s
Single RTX 4090 (24GB) fast 32.0t/s
MacBook Pro M5 Max 128GB fast 21.3t/s
Dual EPYC 9004 + 768GB DDR5-4800 ok 14.6t/s
DGX Spark 128GB unified ok 8.7t/s
Ryzen AI Max+ 395 128GB ok 8.1t/s
Jetson AGX Orin 64GB slow 6.5t/s
Epyc + 512GB DDR4-3200 + 2x RTX 3090 slow 6.5t/s
Epyc + 512GB DDR4-2400 + 2x RTX 3090 slow 4.9t/s

Fit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.

Download options

FP16 official
16.8GB dl 17.0GB min 24.0GB rec
REC RAM vs largest quant
16.8GB fp16 + KV 128MB/1k (32L x 4 kv x 256); late-interaction keeps per-token vectors on disk, not just cache

Or run it in the cloud

No per-token API provider pricing tracked for pplx-embed-v2-late-9b yet. For flagship list prices, see the calculator.

PRICE HISTORY

Inference cost over time

Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.

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