Granite 3.3 8B Instruct — Hardware Requirements & GPU Compatibility
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Granite 3.3 8B Instruct is a 8.2B-parameter open language model from IBM. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 5.54 GB of VRAM — see which GPUs and Macs can run it below.
70.4K downloads
157 likesSpecifications
- Publisher
- IBM
- Parameters
- 8.2B
- Architecture
- GraniteForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 49,159
- Release Date
- 2025-05-12
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Granite 3.3 8B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.1 GB | 25.3 GB | 3.47 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.2 GB | 25.4 GB | 3.57 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.6 GB | 25.8 GB | 3.98 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 4.7 GB | 25.9 GB | 4.09 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 5.5 GB | 26.7 GB | 4.90 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 6.5 GB | 27.6 GB | 5.82 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 7.4 GB | 28.5 GB | 6.74 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 8.8 GB | 29.9 GB | 8.17 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Granite 3.3 8B Instruct?
Q4_K_M · 5.5 GBGranite 3.3 8B Instruct (Q4_K_M) requires 5.5 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 131K context window can add up to 21.1 GB, bringing total usage to 26.7 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Granite 3.3 8B Instruct?
Q4_K_M · 5.5 GB33 devices with unified memory can run Granite 3.3 8B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Derivatives (6)
Frequently Asked Questions
- How much VRAM does Granite 3.3 8B Instruct need?
Granite 3.3 8B Instruct requires 5.5 GB of VRAM at Q4_K_M, or 8.8 GB at Q8_0. Full 131K context adds up to 21.1 GB (26.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 8.2B × 4.8 bits ÷ 8 = 4.9 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 21.8 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M5.5 GBQ4_K_M + full context26.7 GB- What's the best quantization for Granite 3.3 8B Instruct?
For Granite 3.3 8B Instruct, Q4_K_M (5.5 GB) offers the best balance of quality and VRAM usage. Q5_0 (5.7 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 2.9 GB.
VRAM requirement by quantization
IQ2_XXS2.9 GBIQ3_XS4.0 GBQ4_04.7 GBQ4_K_M ★5.5 GBQ5_05.7 GBQ8_08.8 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Granite 3.3 8B Instruct on a Mac?
Granite 3.3 8B Instruct requires at least 2.9 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 Granite 3.3 8B Instruct locally?
Yes — Granite 3.3 8B Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 5.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Granite 3.3 8B Instruct?
At Q4_K_M, Granite 3.3 8B Instruct can reach ~526 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~118 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 ÷ 5.5 × 0.55 = ~526 tok/s
Estimated speed at Q4_K_M (5.5 GB)
~526 tok/s~118 tok/s~393 tok/s~325 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Granite 3.3 8B Instruct?
At Q4_K_M, the download is about 4.90 GB. The full-precision Q8_0 version is 8.17 GB. The smallest option (IQ2_XXS) is 2.25 GB.
- Which GPUs can run Granite 3.3 8B Instruct?
35 consumer GPUs can run Granite 3.3 8B Instruct at Q4_K_M (5.5 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 28 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Granite 3.3 8B Instruct?
33 devices with unified memory can run Granite 3.3 8B Instruct at Q4_K_M (5.5 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.