MiniMaxAI·Qwen2ForCausalLM

SynLogic 7B — Hardware Requirements & GPU Compatibility

Chat

SynLogic 7B is a 7.6B-parameter open language model from MiniMaxAI. It supports a context window of up to 131,072 tokens. At BF16 it needs about 15.65 GB of VRAM — see which GPUs and Macs can run it below.

177 downloads 28 likes131K context

Specifications

Publisher
MiniMaxAI
Parameters
7.6B
Architecture
Qwen2ForCausalLM
Context Length
131,072 tokens
Vocabulary Size
152,064
Release Date
2025-06-10
License
MIT

Get Started

How Much VRAM Does SynLogic 7B Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
BF1616.0015.7 GB

Which GPUs Can Run SynLogic 7B?

BF16 · 15.7 GB

SynLogic 7B (BF16) requires 15.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 21+ GB is recommended. Using the full 131K context window can add up to 7.4 GB, bringing total usage to 23.1 GB. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.

Which Devices Can Run SynLogic 7B?

BF16 · 15.7 GB

27 devices with unified memory can run SynLogic 7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).

Related Models

Frequently Asked Questions

How much VRAM does SynLogic 7B need?

SynLogic 7B requires 15.7 GB of VRAM at BF16. Full 131K context adds up to 7.4 GB (23.1 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 7.6B × 16 bits ÷ 8 = 15.2 GB

KV Cache + Overhead 0.5 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 7.9 GB (at full 131K context)

VRAM usage by quantization

15.7 GB
23.1 GB

Learn more about VRAM estimation →

Can I run SynLogic 7B on a Mac?

SynLogic 7B requires at least 15.7 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 SynLogic 7B locally?

Yes — SynLogic 7B can run locally on consumer hardware. At BF16 quantization it needs 15.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is SynLogic 7B?

At BF16, SynLogic 7B can reach ~186 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~42 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: AMD Instinct MI300X5300 ÷ 15.7 × 0.55 = ~186 tok/s

Estimated speed at BF16 (15.7 GB)

~186 tok/s
~42 tok/s
~139 tok/s
~115 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of SynLogic 7B?

At BF16, the download is about 15.23 GB.

Which GPUs can run SynLogic 7B?

17 consumer GPUs can run SynLogic 7B at BF16 (15.7 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3090 Ti, AMD Radeon RX 6800. 5 GPUs have plenty of headroom for comfortable inference.

Which devices can run SynLogic 7B?

27 devices with unified memory can run SynLogic 7B at BF16 (15.7 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.