Soren 1 Small — Hardware Requirements & GPU Compatibility
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Soren 1 Small is a 1.9B-parameter open language model from syntropy-ai. It supports a context window of up to 1,048,576 tokens. At BF16 it needs about 4.16 GB of VRAM — see which GPUs and Macs can run it below.
1.2K downloads
32 likesSpecifications
- Publisher
- syntropy-ai
- Parameters
- 1.9B
- Architecture
- Qwen3_5ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-05-20
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Soren 1 Small Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 4.2 GB | 55.6 GB | 3.76 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Soren 1 Small?
BF16 · 4.2 GBSoren 1 Small (BF16) requires 4.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 6+ GB is recommended. Using the full 1049K context window can add up to 51.4 GB, bringing total usage to 55.6 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Soren 1 Small?
BF16 · 4.2 GB59 devices with unified memory can run Soren 1 Small, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPhone 17.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Soren 1 Small need?
Soren 1 Small requires 4.2 GB of VRAM at BF16. Full 1049K context adds up to 51.4 GB (55.6 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1.9B × 16 bits ÷ 8 = 3.8 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 51.8 GB (at full 1049K context)
VRAM usage by quantization
BF164.2 GBBF16 + full context55.6 GB- Can I run Soren 1 Small on a Mac?
Soren 1 Small requires at least 4.2 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Soren 1 Small locally?
Yes — Soren 1 Small can run locally on consumer hardware. At BF16 quantization it needs 4.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Soren 1 Small?
At BF16, Soren 1 Small can reach ~1058 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~158 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 4.2 × 0.65 = ~1250 tok/s
Estimated speed at BF16 (4.2 GB)
~1250 tok/s~158 tok/s~1250 tok/s~1058 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Soren 1 Small?
At BF16, the download is about 3.76 GB.
- Which GPUs can run Soren 1 Small?
50 consumer GPUs can run Soren 1 Small at BF16 (4.2 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Soren 1 Small?
59 devices with unified memory can run Soren 1 Small at BF16 (4.2 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.