Granite 3.1 2B Instruct — Hardware Requirements & GPU Compatibility
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Granite 3.1 2B Instruct is IBM's 2.5-billion-parameter dense instruction-tuned model, fine-tuned from Granite-3.1-2B-Base on permissively licensed open instruction datasets plus internally generated synthetic data aimed at long-context problems. It targets business-assistant work such as summarization, classification, extraction, question answering, retrieval-augmented generation, code tasks and function calling, and supports twelve languages including English, German, Spanish, French, Japanese, Arabic and Chinese. At this size it runs on almost any consumer GPU, and on a laptop CPU once quantized. Context length is 131,072 tokens. It is released under the Apache 2.0 license, permitting unrestricted commercial and research use, and was published in December 2024. IBM has since superseded it with Granite 3.3 2B Instruct, which keeps the same size class.
9.3K downloads
57 likesSpecifications
- Publisher
- IBM
- Family
- Granite
- Parameters
- 2.5B
- Architecture
- GraniteForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 49,155
- Release Date
- 2024-12-06
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Granite 3.1 2B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 1.5 GB | 12.1 GB | 1.08 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 1.7 GB | 12.3 GB | 1.24 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 2.0 GB | 12.6 GB | 1.52 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 2.3 GB | 12.8 GB | 1.81 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 2.6 GB | 13.1 GB | 2.09 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 3 GB | 13.6 GB | 2.53 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 5.5 GB | 16.1 GB | 5.07 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 Granite 3.1 2B Instruct?
Q4_K_M · 2.0 GBGranite 3.1 2B Instruct (Q4_K_M) requires 2.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. Using the full 131K context window can add up to 10.6 GB, bringing total usage to 12.6 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 3.1 2B Instruct?
Q4_K_M · 2.0 GB59 devices with unified memory can run Granite 3.1 2B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomBenchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does Granite 3.1 2B Instruct need?
Granite 3.1 2B Instruct requires 2.0 GB of VRAM at Q4_K_M, or 5.5 GB at BF16. Full 131K context adds up to 10.6 GB (12.6 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 2.5B × 4.8 bits ÷ 8 = 1.5 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 11.1 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M2.0 GBQ4_K_M + full context12.6 GB- What's the best quantization for Granite 3.1 2B Instruct?
For Granite 3.1 2B Instruct, Q4_K_M (2.0 GB) offers the best balance of quality and VRAM usage. Q5_K_M (2.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.5 GB.
VRAM requirement by quantization
Q2_K1.5 GBQ4_K_M ★2.0 GBQ5_K_M2.3 GBQ6_K2.6 GBQ8_03.0 GBBF165.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Granite 3.1 2B Instruct on a Mac?
Granite 3.1 2B Instruct requires at least 1.5 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 3.1 2B Instruct locally?
Yes — Granite 3.1 2B Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 2.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Granite 3.1 2B Instruct?
At Q4_K_M, Granite 3.1 2B Instruct can reach ~2412 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~329 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 ÷ 2.0 × 0.65 = ~2613 tok/s
Estimated speed at Q4_K_M (2.0 GB)
~2613 tok/s~329 tok/s~2613 tok/s~2412 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Granite 3.1 2B Instruct?
At Q4_K_M, the download is about 1.52 GB. The full-precision BF16 version is 5.07 GB. The smallest option (Q2_K) is 1.08 GB.
- Which GPUs can run Granite 3.1 2B Instruct?
52 consumer GPUs can run Granite 3.1 2B Instruct at Q4_K_M (2.0 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 3.1 2B Instruct?
59 devices with unified memory can run Granite 3.1 2B Instruct at Q4_K_M (2.0 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.