Granite 3.0 1B A400m Instruct — Hardware Requirements & GPU Compatibility
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Granite 3.0 1B A400m Instruct is a 1.3B-parameter open language model from IBM in the Granite family. It supports a context window of up to 4,096 tokens. At Q4_K_M it needs about 1.20 GB of VRAM — see which GPUs and Macs can run it below.
63.3K downloads
21 likesSpecifications
- Publisher
- IBM
- Family
- Granite
- Parameters
- 1.3B
- Architecture
- GraniteMoeForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 49,155
- Release Date
- 2024-10-03
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Granite 3.0 1B A400m Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 1.0 GB | 1.1 GB | 0.57 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 1.0 GB | 1.1 GB | 0.58 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 1.1 GB | 1.1 GB | 0.65 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 1.1 GB | 1.2 GB | 0.67 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 1.2 GB | 1.3 GB | 0.80 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 1.4 GB | 1.4 GB | 0.95 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 1.5 GB | 1.6 GB | 1.10 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 1.7 GB | 1.8 GB | 1.33 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 Granite 3.0 1B A400m Instruct?
Q4_K_M · 1.2 GBGranite 3.0 1B A400m Instruct (Q4_K_M) requires 1.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ GB is recommended. Using the full 4K context window can add up to 0.1 GB, bringing total usage to 1.3 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Granite 3.0 1B A400m Instruct?
Q4_K_M · 1.2 GB59 devices with unified memory can run Granite 3.0 1B A400m Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomWhere to Download Granite 3.0 1B A400m Instruct
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 Granite 3.0 1B A400m Instruct need?
Granite 3.0 1B A400m Instruct requires 1.2 GB of VRAM at Q4_K_M, or 3.1 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 1.3B × 4.8 bits ÷ 8 = 0.8 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 0.5 GB (at full 4K context)
VRAM usage by quantization
Q4_K_M1.2 GBQ4_K_M + full context1.3 GB- What's the best quantization for Granite 3.0 1B A400m Instruct?
For Granite 3.0 1B A400m Instruct, Q4_K_M (1.2 GB) offers the best balance of quality and VRAM usage. Q4_K_L (1.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.0 GB.
VRAM requirement by quantization
Q2_K1.0 GBQ4_01.1 GBQ4_K_M ★1.2 GBQ4_K_L1.2 GBQ5_K_M1.4 GBBF163.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Granite 3.0 1B A400m Instruct on a Mac?
Granite 3.0 1B A400m Instruct requires at least 1.0 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 Granite 3.0 1B A400m Instruct locally?
Yes — Granite 3.0 1B A400m Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 1.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Granite 3.0 1B A400m Instruct?
At Q4_K_M, Granite 3.0 1B A400m Instruct can reach ~205 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~524 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 ÷ 1.2 × 0.65 = ~717 tok/s
Estimated speed at Q4_K_M (1.2 GB)
~717 tok/s~524 tok/s~717 tok/s~694 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Granite 3.0 1B A400m Instruct?
At Q4_K_M, the download is about 0.80 GB. The full-precision BF16 version is 2.67 GB. The smallest option (Q2_K) is 0.57 GB.
- Which GPUs can run Granite 3.0 1B A400m Instruct?
52 consumer GPUs can run Granite 3.0 1B A400m Instruct at Q4_K_M (1.2 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 Granite 3.0 1B A400m Instruct?
59 devices with unified memory can run Granite 3.0 1B A400m Instruct at Q4_K_M (1.2 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.