Intern S2 Preview — Hardware Requirements & GPU Compatibility
Vision
Intern S2 Preview is a 36.1B-parameter open language model from InternLM in the Intern-S2 family. It supports a context window of up to 262,144 tokens. At BF16 it needs about 72.58 GB of VRAM — see which GPUs and Macs can run it below.
7.0K downloads
113 likesSpecifications
- Publisher
- InternLM
- Family
- Intern-S2
- Parameters
- 36.1B
- Architecture
- InternS2PreviewForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 251,392
- Release Date
- 2026-05-15
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Intern S2 Preview Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 72.6 GB | 83.2 GB | 72.20 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 Intern S2 Preview?
BF16 · 72.6 GBIntern S2 Preview (BF16) requires 72.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 95+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 83.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Intern S2 Preview?
BF16 · 72.6 GB18 devices with unified memory can run Intern S2 Preview, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightFrequently Asked Questions
- How much VRAM does Intern S2 Preview need?
Intern S2 Preview requires 72.6 GB of VRAM at BF16. Full 262K context adds up to 10.7 GB (83.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 36.1B × 16 bits ÷ 8 = 72.2 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 11 GB (at full 262K context)
VRAM usage by quantization
BF1672.6 GBBF16 + full context83.2 GB- Can NVIDIA GeForce RTX 5090 run Intern S2 Preview?
No — Intern S2 Preview requires at least 72.6 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Intern S2 Preview on a Mac?
Intern S2 Preview requires at least 72.6 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 Intern S2 Preview locally?
Yes — Intern S2 Preview can run locally on consumer hardware. At BF16 quantization it needs 72.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Intern S2 Preview?
At BF16, Intern S2 Preview can reach ~61 tok/s on AMD Instinct MI350X. 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 ÷ 72.6 × 0.65 = ~72 tok/s
Estimated speed at BF16 (72.6 GB)
~72 tok/s~72 tok/s~61 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Intern S2 Preview?
At BF16, the download is about 72.20 GB.
- Which GPUs can run Intern S2 Preview?
No single consumer GPU has enough VRAM to run Intern S2 Preview at BF16 (72.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run Intern S2 Preview?
19 devices with unified memory can run Intern S2 Preview at BF16 (72.6 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (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.