Cyber Ornith 1.5 9B OBLITERATED — Hardware Requirements & GPU Compatibility
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Cyber Ornith 1.5 9B OBLITERATED is a 9.0B-parameter open language model from DuoNeural in the Ornith family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 5.94 GB of VRAM — see which GPUs and Macs can run it below.
1.7K downloads
9 likesSpecifications
- Publisher
- DuoNeural
- Family
- Ornith
- Parameters
- 9.0B
- Architecture
- Qwen3_5ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-09-25
- License
- Apache 2.0
Get Started
HuggingFace
Run in cloud
Fits on RTX 3060 12GB (6 GB headroom) · Q4_K_M
- Generation speed
- ~39 tok/s
- generation speed
- Cost per 1M output tokens
- $0.43
- per 1M output tokens
How Much VRAM Does Cyber Ornith 1.5 9B OBLITERATED Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.4 GB | 12.7 GB | 3.81 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.5 GB | 12.8 GB | 3.92 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.9 GB | 13.3 GB | 4.36 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 5.0 GB | 13.4 GB | 4.48 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 5.9 GB | 14.3 GB | 5.37 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 7.0 GB | 15.3 GB | 6.38 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 8.0 GB | 16.3 GB | 7.39 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 9.5 GB | 17.8 GB | 8.95 GB | 8-bit quantization, near-lossless |
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 Ornith 1.5 9B OBLITERATED?
Q4_K_M · 5.9 GBCyber Ornith 1.5 9B OBLITERATED (Q4_K_M) requires 5.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 262K context window can add up to 8.3 GB, bringing total usage to 14.3 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Cyber Ornith 1.5 9B OBLITERATED?
Q4_K_M · 5.9 GB53 devices with unified memory can run Cyber Ornith 1.5 9B OBLITERATED, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, NVIDIA Jetson Orin Nano 8GB (Super).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Cyber Ornith 1.5 9B OBLITERATED
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 Ornith 1.5 9B OBLITERATED need?
Cyber Ornith 1.5 9B OBLITERATED requires 5.9 GB of VRAM at Q4_K_M, or 18.5 GB at BF16. Full 262K context adds up to 8.3 GB (14.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 9.0B × 4.8 bits ÷ 8 = 5.4 GB
KV Cache + Overhead ≈ 0.5 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 ≈ 8.9 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M5.9 GBQ4_K_M + full context14.3 GB- What's the best quantization for Cyber Ornith 1.5 9B OBLITERATED?
For Cyber Ornith 1.5 9B OBLITERATED, Q4_K_M (5.9 GB) offers the best balance of quality and VRAM usage. Q5_K_S (6.7 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 3.0 GB.
VRAM requirement by quantization
IQ2_XXS3.0 GBIQ3_XS4.3 GBQ4_05.0 GBIQ4_NL5.6 GBQ4_K_M ★5.9 GBBF1618.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Cyber Ornith 1.5 9B OBLITERATED on a Mac?
Yes, but only at lower quantizations. The smallest Mac that can run Cyber Ornith 1.5 9B OBLITERATED is MacBook Air 13" M3 (8 GB) at IQ2_XXS; 39 of the 39 Macs we list can run it at some quantization. For Q4_K_M (5.9 GB) you need a Mac with more unified memory.
- Can I run Cyber Ornith 1.5 9B OBLITERATED locally?
Yes — Cyber Ornith 1.5 9B OBLITERATED can run locally on consumer hardware. At Q4_K_M quantization it needs 5.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Cyber Ornith 1.5 9B OBLITERATED?
At Q4_K_M, Cyber Ornith 1.5 9B OBLITERATED can reach ~808 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~110 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 ÷ 5.94 × 0.65 = ~875 tok/s
Estimated speed at Q4_K_M (5.9 GB)
~875 tok/s~110 tok/s~875 tok/s~808 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Cyber Ornith 1.5 9B OBLITERATED?
At Q4_K_M, the download is about 5.37 GB. The full-precision BF16 version is 17.91 GB. The smallest option (IQ2_XXS) is 2.46 GB.
- Which GPUs can run Cyber Ornith 1.5 9B OBLITERATED?
52 consumer GPUs can run Cyber Ornith 1.5 9B OBLITERATED at Q4_K_M (5.9 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 40 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Cyber Ornith 1.5 9B OBLITERATED?
53 devices with unified memory can run Cyber Ornith 1.5 9B OBLITERATED at Q4_K_M (5.9 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.