Llava Onevision Qwen2 7B Ov — Hardware Requirements & GPU Compatibility
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Llava Onevision Qwen2 7B Ov is a 8.0B-parameter open language model from lmms-lab in the Qwen 2 family. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 5.24 GB of VRAM — see which GPUs and Macs can run it below.
39.7K downloads
64 likesSpecifications
- Publisher
- lmms-lab
- Family
- Qwen 2
- Parameters
- 8.0B
- Architecture
- LlavaQwenForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2024-06-29
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Llava Onevision Qwen2 7B Ov Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 3.8 GB | 5.6 GB | 3.41 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 4.3 GB | 6.1 GB | 3.91 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 5.2 GB | 7 GB | 4.82 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 6.1 GB | 7.9 GB | 5.72 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 7.0 GB | 8.8 GB | 6.63 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 8.4 GB | 10.2 GB | 8.03 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 16.5 GB | 18.2 GB | 16.06 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 Llava Onevision Qwen2 7B Ov?
Q4_K_M · 5.2 GBLlava Onevision Qwen2 7B Ov (Q4_K_M) requires 5.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 33K context window can add up to 1.8 GB, bringing total usage to 7 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Llava Onevision Qwen2 7B Ov?
Q4_K_M · 5.2 GB58 devices with unified memory can run Llava Onevision Qwen2 7B Ov, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Apple iPhone 17 Pro.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Llava Onevision Qwen2 7B Ov need?
Llava Onevision Qwen2 7B Ov requires 5.2 GB of VRAM at Q4_K_M, or 16.5 GB at BF16. Full 33K context adds up to 1.8 GB (7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 8.0B × 4.8 bits ÷ 8 = 4.8 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 2.2 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M5.2 GBQ4_K_M + full context7.0 GB- What's the best quantization for Llava Onevision Qwen2 7B Ov?
For Llava Onevision Qwen2 7B Ov, Q4_K_M (5.2 GB) offers the best balance of quality and VRAM usage. Q5_K_M (6.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.8 GB.
VRAM requirement by quantization
Q2_K3.8 GBQ4_K_M ★5.2 GBQ5_K_M6.1 GBQ6_K7.0 GBQ8_08.4 GBBF1616.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Llava Onevision Qwen2 7B Ov on a Mac?
Llava Onevision Qwen2 7B Ov requires at least 3.8 GB at Q2_K, 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 Llava Onevision Qwen2 7B Ov locally?
Yes — Llava Onevision Qwen2 7B Ov can run locally on consumer hardware. At Q4_K_M quantization it needs 5.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llava Onevision Qwen2 7B Ov?
At Q4_K_M, Llava Onevision Qwen2 7B Ov can reach ~916 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~125 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 ÷ 5.2 × 0.65 = ~992 tok/s
Estimated speed at Q4_K_M (5.2 GB)
~992 tok/s~125 tok/s~992 tok/s~916 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Llava Onevision Qwen2 7B Ov?
At Q4_K_M, the download is about 4.82 GB. The full-precision BF16 version is 16.06 GB. The smallest option (Q2_K) is 3.41 GB.
- Which GPUs can run Llava Onevision Qwen2 7B Ov?
52 consumer GPUs can run Llava Onevision Qwen2 7B Ov at Q4_K_M (5.2 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Llava Onevision Qwen2 7B Ov?
59 devices with unified memory can run Llava Onevision Qwen2 7B Ov at Q4_K_M (5.2 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.