North Mini Code 1.0 — Hardware Requirements & GPU Compatibility
ChatCodeFunctions
North Mini Code 1.0 is a 30.5B-parameter open language model from Cohere. It supports a context window of up to 500,000 tokens. At Q4_K_M it needs about 18.69 GB of VRAM — see which GPUs and Macs can run it below.
4.1K downloads
330 likesSpecifications
- Publisher
- Cohere
- Parameters
- 30.5B
- Architecture
- Cohere2MoeForCausalLM
- Context Length
- 500,000 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-06-05
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does North Mini Code 1.0 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 13.4 GB | 38.3 GB | 12.96 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 15.3 GB | 40.3 GB | 14.86 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 18.7 GB | 43.7 GB | 18.29 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 22.1 GB | 47.1 GB | 21.72 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 25.6 GB | 50.5 GB | 25.15 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 30.9 GB | 55.9 GB | 30.48 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 North Mini Code 1.0?
Q4_K_M · 18.7 GBNorth Mini Code 1.0 (Q4_K_M) requires 18.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 25+ GB is recommended. Using the full 500K context window can add up to 25.0 GB, bringing total usage to 43.7 GB. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run North Mini Code 1.0?
Q4_K_M · 18.7 GB21 devices with unified memory can run North Mini Code 1.0, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomWhere to Download North Mini Code 1.0
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 North Mini Code 1.0 need?
North Mini Code 1.0 requires 18.7 GB of VRAM at Q4_K_M, or 61.4 GB at BF16. Full 500K context adds up to 25.0 GB (43.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 30.5B × 4.8 bits ÷ 8 = 18.3 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 25.4 GB (at full 500K context)
VRAM usage by quantization
Q4_K_M18.7 GBQ4_K_M + full context43.7 GB- Can NVIDIA GeForce RTX 4090 run North Mini Code 1.0?
Yes, at Q5_K_M (22.1 GB) or lower. Higher quantizations like Q6_K (25.6 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for North Mini Code 1.0?
For North Mini Code 1.0, Q4_K_M (18.7 GB) offers the best balance of quality and VRAM usage. Q5_K_M (22.1 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 8.8 GB.
VRAM requirement by quantization
IQ2_XXS8.8 GBQ2_K13.4 GBIQ4_XS16.8 GBQ4_K_M ★18.7 GBQ5_K_M22.1 GBBF1661.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run North Mini Code 1.0 on a Mac?
North Mini Code 1.0 requires at least 8.8 GB at IQ2_XXS, 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 North Mini Code 1.0 locally?
Yes — North Mini Code 1.0 can run locally on consumer hardware. At Q4_K_M quantization it needs 18.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is North Mini Code 1.0?
At Q4_K_M, North Mini Code 1.0 can reach ~156 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~35 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 18.7 × 0.55 = ~156 tok/s
Estimated speed at Q4_K_M (18.7 GB)
~156 tok/s~35 tok/s~117 tok/s~96 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of North Mini Code 1.0?
At Q4_K_M, the download is about 18.29 GB. The full-precision BF16 version is 60.97 GB. The smallest option (IQ2_XXS) is 8.38 GB.
- Which GPUs can run North Mini Code 1.0?
6 consumer GPUs can run North Mini Code 1.0 at Q4_K_M (18.7 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run North Mini Code 1.0?
21 devices with unified memory can run North Mini Code 1.0 at Q4_K_M (18.7 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.