Models / d1-omni-600M

d1-omni-600M

edge
HuggingFace → Liquid AI → Find for my hardware

Audio-in at 600M parameters. d1-omni-600M closes the year’s smallest-omni race: voice in, image in, text out, 10,030 downloads in days with the official GGUF out the same day. 587M parameters, 16 layers, 8 KV heads x 64 head-dim, a 128,000-token context and 32MB of cache per 1,000 tokens; 0.3GB in 4-bit, which is wearable-and-microcontroller class, not just phone class.

Where it lands. Same bespoke Liquid license as the 3B sibling; the omni’s value is the single-digit-hundred-megabyte footprint with ears: always-on voice interfaces with the audio never leaving the device.

audio vision edge multimodal
Parameters
590M
Context
128k
License
liquid ai license
Developer
Liquid AI
Origin
🇺🇸 USA
Released
Oct 2026

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3.1B edge 4GB min RAM Oct 7, 2026

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Run it locally

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

Q4_K_M
0.3GB 2.0GB min 3.0GB rec
Balanced - the usual local sweet spot

The reference hardware

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 Single GTX 1080 Ti (11GB) reference rig - 11GB VRAM, 484 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
Schematic of the NVIDIA Jetson Orin NX 16GB reference rig - 16GB unified memory, 102 GB/s aggregate bandwidth

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

Can you run it? - reference rigs

Rig Q4_K_M
4x H100 80GB (320GB) fast 17219.6t/s
NVIDIA DGX Station 748GB fast 10280.4t/s
8x RTX 3090 rack (192GB) fast 9624.5t/s
4x RTX 5090 (128GB) fast 9211.2t/s
AMD Instinct MI300X (192GB) fast 6842.6t/s
4x RTX 4090 (96GB) fast 5181.3t/s
2x RTX 5090 (64GB) fast 4605.6t/s
2x RTX 3090 (48GB) fast 2406.1t/s
Single RTX 5090 (32GB) fast 2302.8t/s
RTX PRO 6000 Blackwell (96GB) fast 2302.8t/s
Mac Studio M4 Ultra 192GB fast 1530.8t/s
Mac Studio M4 Ultra 512GB fast 1530.8t/s
Single RTX 4090 (24GB) fast 1295.3t/s
MacBook Pro M5 Max 128GB fast 860.8t/s
Single GTX 1080 Ti (11GB) fast 622.0t/s
Dual EPYC 9004 + 768GB DDR5-4800 fast 592.2t/s
DGX Spark 128GB unified fast 350.8t/s
Ryzen AI Max+ 395 128GB fast 329.0t/s
Jetson AGX Orin 64GB fast 263.2t/s
Epyc + 512GB DDR4-3200 + 2x RTX 3090 fast 263.2t/s
Epyc + 512GB DDR4-2400 + 2x RTX 3090 fast 197.4t/s
NVIDIA Jetson Orin NX 16GB fast 131.6t/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

Q4_K_M community
0.3GB dl 2.0GB min 3.0GB rec
REC RAM vs largest quant
0.3GB q4 + KV 32MB/1k (16L x 8 kv x 64); wearable class
GGUF on HF →

Or run it in the cloud

No per-token API provider pricing tracked for d1-omni-600M 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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