K2 Horizon 7B — Hardware Requirements & GPU Compatibility
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K2 Horizon 7B is a 9.0B-parameter open language model from IFM. It supports a context window of up to 524,288 tokens. At Q4_K_M it needs about 6.00 GB of VRAM — see which GPUs and Macs can run it below.
1.3K downloads
69 likesSpecifications
- Publisher
- IFM
- Parameters
- 9.0B
- Architecture
- K2HorizonForCausalLM
- Context Length
- 524,288 tokens
- Vocabulary Size
- 250,624
- Release Date
- 2026-09-01
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does K2 Horizon 7B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.4 GB | 81.4 GB | 3.82 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.5 GB | 81.5 GB | 3.94 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 5.0 GB | 82 GB | 4.39 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 5.1 GB | 82.1 GB | 4.50 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 6 GB | 83.0 GB | 5.40 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 7.0 GB | 84.0 GB | 6.41 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 8.0 GB | 85.0 GB | 7.42 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 9.6 GB | 86.6 GB | 9.00 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run K2 Horizon 7B?
Q4_K_M · 6 GBK2 Horizon 7B (Q4_K_M) requires 6 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 524K context window can add up to 77.0 GB, bringing total usage to 83.0 GB. 50 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 K2 Horizon 7B?
Q4_K_M · 6 GB58 devices with unified memory can run K2 Horizon 7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomWhere to Download K2 Horizon 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 K2 Horizon 7B need?
K2 Horizon 7B requires 6 GB of VRAM at Q4_K_M, or 18.6 GB at BF16. Full 524K context adds up to 77.0 GB (83.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 9.0B × 4.8 bits ÷ 8 = 5.4 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 77.6 GB (at full 524K context)
VRAM usage by quantization
Q4_K_M6.0 GBQ4_K_M + full context83.0 GB- What's the best quantization for K2 Horizon 7B?
For K2 Horizon 7B, Q4_K_M (6 GB) offers the best balance of quality and VRAM usage. Q5_0 (6.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 3.1 GB.
VRAM requirement by quantization
IQ2_XXS3.1 GBIQ3_XS4.3 GBQ3_K_L5.2 GBQ4_K_M ★6.0 GBQ5_06.2 GBBF1618.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run K2 Horizon 7B on a Mac?
K2 Horizon 7B requires at least 3.1 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 K2 Horizon 7B locally?
Yes — K2 Horizon 7B can run locally on consumer hardware. At Q4_K_M quantization it needs 6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is K2 Horizon 7B?
At Q4_K_M, K2 Horizon 7B can reach ~800 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~109 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 ÷ 6.0 × 0.65 = ~867 tok/s
Estimated speed at Q4_K_M (6 GB)
~867 tok/s~109 tok/s~867 tok/s~800 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of K2 Horizon 7B?
At Q4_K_M, the download is about 5.40 GB. The full-precision BF16 version is 18.00 GB. The smallest option (IQ2_XXS) is 2.47 GB.
- Which GPUs can run K2 Horizon 7B?
50 consumer GPUs can run K2 Horizon 7B at Q4_K_M (6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 39 GPUs have plenty of headroom for comfortable inference.
- Which devices can run K2 Horizon 7B?
59 devices with unified memory can run K2 Horizon 7B at Q4_K_M (6 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.