TildeOpen 30B — Hardware Requirements & GPU Compatibility
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TildeOpen 30B is a 30.7B-parameter open language model from TildeAI. It supports a context window of up to 65,536 tokens. At BF16 it needs about 62.16 GB of VRAM — see which GPUs and Macs can run it below.
3.3K downloads
155 likesSpecifications
- Publisher
- TildeAI
- Parameters
- 30.7B
- Architecture
- LlamaForCausalLM
- Context Length
- 65,536 tokens
- Vocabulary Size
- 131,072
- Release Date
- 2025-10-08
- License
- CC BY 4.0
Get Started
HuggingFace
How Much VRAM Does TildeOpen 30B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 62.2 GB | 77.8 GB | 61.36 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run TildeOpen 30B?
BF16 · 62.2 GBTildeOpen 30B (BF16) requires 62.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 81+ GB is recommended. Using the full 66K context window can add up to 15.6 GB, bringing total usage to 77.8 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run TildeOpen 30B?
BF16 · 62.2 GB8 devices with unified memory can run TildeOpen 30B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does TildeOpen 30B need?
TildeOpen 30B requires 62.2 GB of VRAM at BF16. Full 66K context adds up to 15.6 GB (77.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 30.7B × 16 bits ÷ 8 = 61.4 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 16.4 GB (at full 66K context)
VRAM usage by quantization
BF1662.2 GBBF16 + full context77.8 GB- Can NVIDIA GeForce RTX 5090 run TildeOpen 30B?
No — TildeOpen 30B requires at least 62.2 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run TildeOpen 30B on a Mac?
TildeOpen 30B requires at least 62.2 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 TildeOpen 30B locally?
Yes — TildeOpen 30B can run locally on consumer hardware. At BF16 quantization it needs 62.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is TildeOpen 30B?
At BF16, TildeOpen 30B can reach ~47 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 62.2 × 0.55 = ~47 tok/s
Estimated speed at BF16 (62.2 GB)
~47 tok/s~35 tok/s~29 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of TildeOpen 30B?
At BF16, the download is about 61.36 GB.
- Which GPUs can run TildeOpen 30B?
No single consumer GPU has enough VRAM to run TildeOpen 30B at BF16 (62.2 GB). Multi-GPU or professional hardware is required.
- Which devices can run TildeOpen 30B?
8 devices with unified memory can run TildeOpen 30B at BF16 (62.2 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), Mac Studio M4 Max (64 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.