Spark X2.5 1.7B — Hardware Requirements & GPU Compatibility
Chat
Spark X2.5 1.7B is a 1.7B-parameter open language model from XHToken. It supports a context window of up to 1,048,576 tokens. At BF16 it needs about 3.83 GB of VRAM — see which GPUs and Macs can run it below.
2.3K downloads
88 likesSpecifications
- Publisher
- XHToken
- Parameters
- 1.7B
- Architecture
- Spark2_5ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 131,072
- Release Date
- 2026-08-24
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Spark X2.5 1.7B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 3.8 GB | 63.8 GB | 3.42 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 Spark X2.5 1.7B?
BF16 · 3.8 GBSpark X2.5 1.7B (BF16) requires 3.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 5+ GB is recommended. Using the full 1049K context window can add up to 60.0 GB, bringing total usage to 63.8 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Spark X2.5 1.7B?
BF16 · 3.8 GB59 devices with unified memory can run Spark X2.5 1.7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPhone 17.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Spark X2.5 1.7B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Spark X2.5 1.7B need?
Spark X2.5 1.7B requires 3.8 GB of VRAM at BF16. Full 1049K context adds up to 60.0 GB (63.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1.7B × 16 bits ÷ 8 = 3.4 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 60.4 GB (at full 1049K context)
VRAM usage by quantization
BF163.8 GBBF16 + full context63.8 GB- Can I run Spark X2.5 1.7B on a Mac?
Spark X2.5 1.7B requires at least 3.8 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 Spark X2.5 1.7B locally?
Yes — Spark X2.5 1.7B can run locally on consumer hardware. At BF16 quantization it needs 3.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Spark X2.5 1.7B?
At BF16, Spark X2.5 1.7B can reach ~1253 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~171 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 ÷ 3.8 × 0.65 = ~1358 tok/s
Estimated speed at BF16 (3.8 GB)
~1358 tok/s~171 tok/s~1358 tok/s~1253 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Spark X2.5 1.7B?
At BF16, the download is about 3.42 GB.
- Which GPUs can run Spark X2.5 1.7B?
50 consumer GPUs can run Spark X2.5 1.7B at BF16 (3.8 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 Spark X2.5 1.7B?
59 devices with unified memory can run Spark X2.5 1.7B at BF16 (3.8 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.