CYBER FROST 3.8 BF16 — Hardware Requirements & GPU Compatibility
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CYBER FROST 3.8 BF16 is a 180.0B-parameter open language model from Blackfrost-AI. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 108.38 GB of VRAM — see which GPUs and Macs can run it below.
1.6K downloads
59 likesSpecifications
- Publisher
- Blackfrost-AI
- Parameters
- 180.0B
- Architecture
- Qwen4ExpForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-09-15
- License
- Other
Get Started
HuggingFace
Run in cloud
Fits on H200 (141 GB) (32 GB headroom) · Q4_K_M
- Generation speed
- ~69 tok/s
- generation speed
- Cost per 1M output tokens
- $14.47
- per 1M output tokens
How Much VRAM Does CYBER FROST 3.8 BF16 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K_S | 3.20 | 72.4 GB | 83.0 GB | 72.00 GB | 2-bit small K-quant |
| Q2_K | 3.40 | 76.9 GB | 87.5 GB | 76.50 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 79.1 GB | 89.8 GB | 78.75 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 88.1 GB | 98.8 GB | 87.75 GB | 3-bit medium quantization |
| IQ4_XS | 4.30 | 97.1 GB | 107.8 GB | 96.75 GB | Importance-weighted 4-bit, compact |
| Q4_K_M | 4.80 | 108.4 GB | 119.0 GB | 108.00 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 128.6 GB | 139.3 GB | 128.25 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 148.9 GB | 159.5 GB | 148.50 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 180.4 GB | 191.0 GB | 180.00 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 360.4 GB | 371.0 GB | 360.00 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 CYBER FROST 3.8 BF16?
Q4_K_M · 108.4 GBCYBER FROST 3.8 BF16 (Q4_K_M) requires 108.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 141+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 119.0 GB. No consumer GPU has enough memory.
Which Devices Can Run CYBER FROST 3.8 BF16?
Q4_K_M · 108.4 GB11 devices with unified memory can run CYBER FROST 3.8 BF16, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M5 Max (128 GB).
Runs great
— Plenty of headroom
Where to Download CYBER FROST 3.8 BF16
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 CYBER FROST 3.8 BF16 need?
CYBER FROST 3.8 BF16 requires 108.4 GB of VRAM at Q4_K_M, or 360.4 GB at BF16. Full 262K context adds up to 10.7 GB (119.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 180.0B × 4.8 bits ÷ 8 = 108 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 11 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M108.4 GBQ4_K_M + full context119.0 GB- Can NVIDIA GeForce RTX 5090 run CYBER FROST 3.8 BF16?
No — CYBER FROST 3.8 BF16 requires at least 72.4 GB at Q2_K_S, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for CYBER FROST 3.8 BF16?
For CYBER FROST 3.8 BF16, Q4_K_M (108.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (128.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K_S at 72.4 GB.
VRAM requirement by quantization
Q2_K_S72.4 GBQ3_K_S79.1 GBQ4_K_M ★108.4 GBQ5_K_M128.6 GBQ6_K148.9 GBBF16360.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run CYBER FROST 3.8 BF16 on a Mac?
Yes — Mac Studio M4 Max (128 GB) and 5 other Macs can run CYBER FROST 3.8 BF16. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 108.4 GB of usable unified memory (RAM minus macOS overhead).
- Can I run CYBER FROST 3.8 BF16 locally?
Yes — CYBER FROST 3.8 BF16 can run locally on consumer hardware. At Q4_K_M quantization it needs 108.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is CYBER FROST 3.8 BF16?
At Q4_K_M, CYBER FROST 3.8 BF16 can reach ~58 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = 1000 ÷ (active GB ÷ (bandwidth GB/s × efficiency) × 1000 + layers × routing ms)
Mixture-of-Experts: only the active experts are read per token, plus a fixed per-layer routing cost.
Example: NVIDIA B200 → 37.1 GB active ÷ (8000 × 0.65) = 7.13 ms, plus 48 layers × 0.055 ms = 2.64 ms, so 1000 ÷ 9.77 ms = ~102 tok/s
Estimated speed at Q4_K_M (108.4 GB)
~102 tok/s~102 tok/s~70 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of CYBER FROST 3.8 BF16?
At Q4_K_M, the download is about 108.00 GB. The full-precision BF16 version is 360.00 GB. The smallest option (Q2_K_S) is 72.00 GB.
- Which GPUs can run CYBER FROST 3.8 BF16?
No single consumer GPU has enough VRAM to run CYBER FROST 3.8 BF16 at Q4_K_M (108.4 GB). Multi-GPU or professional hardware is required.
- Which devices can run CYBER FROST 3.8 BF16?
11 devices with unified memory can run CYBER FROST 3.8 BF16 at Q4_K_M (108.4 GB), including ASUS Ascent GX10, Mac Pro M2 Ultra (192 GB), Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.