Rocinante X 12B V1 — Hardware Requirements & GPU Compatibility
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Rocinante X 12B V1 is a 12.2B-parameter open language model from TheDrummer. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 8.07 GB of VRAM — see which GPUs and Macs can run it below.
1.3K downloads
92 likesSpecifications
- Publisher
- TheDrummer
- Parameters
- 12.2B
- Architecture
- MistralForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 131,072
- Release Date
- 2026-01-19
Get Started
HuggingFace
How Much VRAM Does Rocinante X 12B V1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 5.9 GB | 32.4 GB | 5.21 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 6.1 GB | 32.5 GB | 5.36 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 6.7 GB | 33.1 GB | 5.97 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 6.8 GB | 33.3 GB | 6.12 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 8.1 GB | 34.5 GB | 7.35 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 9.4 GB | 35.9 GB | 8.73 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 10.8 GB | 37.3 GB | 10.10 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 13.0 GB | 39.4 GB | 12.25 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Rocinante X 12B V1?
Q4_K_M · 8.1 GBRocinante X 12B V1 (Q4_K_M) requires 8.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 11+ GB is recommended. Using the full 131K context window can add up to 26.4 GB, bringing total usage to 34.5 GB. 39 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Rocinante X 12B V1?
Q4_K_M · 8.1 GB49 devices with unified memory can run Rocinante X 12B V1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPad Pro M5 13" (16 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Rocinante X 12B V1
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 Rocinante X 12B V1 need?
Rocinante X 12B V1 requires 8.1 GB of VRAM at Q4_K_M, or 25.2 GB at BF16. Full 131K context adds up to 26.4 GB (34.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 12.2B × 4.8 bits ÷ 8 = 7.3 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 27.2 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M8.1 GBQ4_K_M + full context34.5 GB- Can NVIDIA GeForce RTX 4090 run Rocinante X 12B V1?
Yes, at Q8_0 (13.0 GB) or lower. Higher quantizations like BF16 (25.2 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Rocinante X 12B V1?
For Rocinante X 12B V1, Q4_K_M (8.1 GB) offers the best balance of quality and VRAM usage. Q4_K_L (8.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_S at 4.5 GB.
VRAM requirement by quantization
IQ2_S4.5 GBQ3_K_S6.1 GBIQ4_NL7.6 GBQ4_K_M ★8.1 GBQ5_K_S9.1 GBBF1625.2 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Rocinante X 12B V1 on a Mac?
Rocinante X 12B V1 requires at least 4.5 GB at IQ2_S, 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 Rocinante X 12B V1 locally?
Yes — Rocinante X 12B V1 can run locally on consumer hardware. At Q4_K_M quantization it needs 8.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Rocinante X 12B V1?
At Q4_K_M, Rocinante X 12B V1 can reach ~545 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~81 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 ÷ 8.1 × 0.65 = ~644 tok/s
Estimated speed at Q4_K_M (8.1 GB)
~644 tok/s~81 tok/s~644 tok/s~545 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Rocinante X 12B V1?
At Q4_K_M, the download is about 7.35 GB. The full-precision BF16 version is 24.50 GB. The smallest option (IQ2_S) is 3.83 GB.
- Which GPUs can run Rocinante X 12B V1?
39 consumer GPUs can run Rocinante X 12B V1 at Q4_K_M (8.1 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 26 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Rocinante X 12B V1?
52 devices with unified memory can run Rocinante X 12B V1 at Q4_K_M (8.1 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.