SOLAR 10.7B Instruct v1.0 — Hardware Requirements & GPU Compatibility
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SOLAR 10.7B Instruct v1.0 is a 10.7B-parameter open language model from Upstage in the Solar family. It supports a context window of up to 4,096 tokens. At Q4_K_M it needs about 7.12 GB of VRAM — see which GPUs and Macs can run it below.
26.6K downloads
649 likesSpecifications
- Publisher
- Upstage
- Family
- Solar
- Parameters
- 10.7B
- Architecture
- LlamaForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 32,000
- Release Date
- 2023-12-12
- License
- CC BY-NC 4.0
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HuggingFace
How Much VRAM Does SOLAR 10.7B Instruct v1.0 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 5.3 GB | 5.7 GB | 4.55 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 5.9 GB | 6.3 GB | 5.22 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 7.1 GB | 7.5 GB | 6.42 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 8.3 GB | 8.7 GB | 7.62 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 9.5 GB | 9.9 GB | 8.83 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 11.4 GB | 11.8 GB | 10.70 GB | 8-bit quantization, near-lossless |
| FP16est. | 16.00 | 22.1 GB | 22.5 GB | 21.40 GB | Full half-precision — baseline for inference |
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 SOLAR 10.7B Instruct v1.0?
Q4_K_M · 7.1 GBSOLAR 10.7B Instruct v1.0 (Q4_K_M) requires 7.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 10+ GB is recommended. Using the full 4K context window can add up to 0.4 GB, bringing total usage to 7.5 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run SOLAR 10.7B Instruct v1.0?
Q4_K_M · 7.1 GB55 devices with unified memory can run SOLAR 10.7B Instruct v1.0, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPad Pro M5 13" (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does SOLAR 10.7B Instruct v1.0 need?
SOLAR 10.7B Instruct v1.0 requires 7.1 GB of VRAM at Q4_K_M, or 22.1 GB at FP16.
VRAM = Weights + KV Cache + Overhead
Weights = 10.7B × 4.8 bits ÷ 8 = 6.4 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 1.1 GB (at full 4K context)
VRAM usage by quantization
Q4_K_M7.1 GBQ4_K_M + full context7.5 GB- What's the best quantization for SOLAR 10.7B Instruct v1.0?
For SOLAR 10.7B Instruct v1.0, Q4_K_M (7.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (8.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 5.3 GB.
VRAM requirement by quantization
Q2_K5.3 GBQ4_K_M ★7.1 GBQ5_K_M8.3 GBQ6_K9.5 GBQ8_011.4 GBFP1622.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run SOLAR 10.7B Instruct v1.0 on a Mac?
SOLAR 10.7B Instruct v1.0 requires at least 5.3 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 SOLAR 10.7B Instruct v1.0 locally?
Yes — SOLAR 10.7B Instruct v1.0 can run locally on consumer hardware. At Q4_K_M quantization it needs 7.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is SOLAR 10.7B Instruct v1.0?
At Q4_K_M, SOLAR 10.7B Instruct v1.0 can reach ~618 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~92 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 ÷ 7.1 × 0.65 = ~730 tok/s
Estimated speed at Q4_K_M (7.1 GB)
~730 tok/s~92 tok/s~730 tok/s~618 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of SOLAR 10.7B Instruct v1.0?
At Q4_K_M, the download is about 6.42 GB. The full-precision FP16 version is 21.40 GB. The smallest option (Q2_K) is 4.55 GB.
- Which GPUs can run SOLAR 10.7B Instruct v1.0?
50 consumer GPUs can run SOLAR 10.7B Instruct v1.0 at Q4_K_M (7.1 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 37 GPUs have plenty of headroom for comfortable inference.
- Which devices can run SOLAR 10.7B Instruct v1.0?
59 devices with unified memory can run SOLAR 10.7B Instruct v1.0 at Q4_K_M (7.1 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.