Granite 4.2 30B — Hardware Requirements & GPU Compatibility
ChatReasoningFunctions
Granite 4.2 30B is a 29.3B-parameter open language model from IBM in the Granite family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 18.40 GB of VRAM — see which GPUs and Macs can run it below.
Decent on a 24 GB GPU
Runs on 24 GB (Q4_K_M · ~36 tok/s · 16K)Macs from 24 GB (Q4_K_M · ~12 tok/s)
Apache 2.0
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Granite 4.2 30B
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
ollama run granite4.2:30bQ4_K_M fits fully on the RTX 4090 · 1.8 GB free · 16K context
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Fits on RTX PRO 4500 (32 GB) (9 GB headroom) · Q4_K_M
- Generation speed
- ~32 tok/s
- generation speed
- Cost per 1M output tokens
- $2.98
- per 1M output tokens
How Much VRAM Does Granite 4.2 30B Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 13.3 GB | 21.3 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Fits: 32K context · ~49 tok/s | |
| 15.1 GB | 23.2 GB | 3-bit medium — 3-bit medium quantization | Fits: 32K context · ~43 tok/s | |
| 18.4 GB | 26.5 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Fits: 16K context · ~36 tok/s | |
| 21.7 GB | 29.8 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Fits: 8K context · ~30 tok/s | |
| 25.0 GB | 33 GB | 6-bit, very good — 6-bit quantization, very good quality | Does not fit: needs 28.8 GB | |
| 30.1 GB | 38.2 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Does not fit: needs 33.9 GB | |
| 59.4 GB | 67.4 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Does not fit: needs 63.2 GB |
Selected Q4_K_M
4-bit medium quantization22.2GBat 16K context
- Weights
- 17.6 GB
- KV cache
- 4.3 GB
- Overhead
- 0.3 GB
Fits RTX 4090 (reference) · 1.8 GB free · ~36 tok/s
≥50 tok/s needs ≥1.41 TB/s · RTX 5090 ~63
Which Hardware Can Run Granite 4.2 30B?
Q4_K_M · 18.4 GBGranite 4.2 30B (Q4_K_M) requires 18.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 24+ GB is recommended. Using the full 131K context window can add up to 33.8 GB, bringing total usage to 52.2 GB. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti. 122 devices with unified memory can run Granite 4.2 30B, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Mini M5 Pro (24 GB).
20 GB
tight · up to 4K ctx
1 GPU
RX 7900 XT~26Simulate output on RX 7900 XT32–40 GB
fits · 9.8 GB free · up to 32K ctx
1 GPU · 3 Mac classes · 4 device families
RTX 5090~63Simulate output on RTX 5090M5 Max36 GB~18Simulate output on Mac Studio M5 Max (36 GB)M532 GB~6Simulate output on MacBook Air 13" M5 (32 GB)Orin~7Simulate output on NVIDIA Jetson AGX Orin 32GBSnapdragon X Elite (X1E-80-100)~5Simulate output on Snapdragon X Elite Copilot+ PC
By VRAM tier · typical GPUs and Macs at Q4_K_M
How good is Granite 4.2 30B?
llmrun Score blends public benchmark boards into one number; 100 = the average open model.
Not enough data yet for an llmrun Score.
A Score needs results on enough independent boards. How the Composite Score is built
Benchmarks
This is the single board showing results for this model; badges show who ran the test.
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Alternatives to Granite 4.2 30B
Granite family · 26 models →Similar models
6| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Qwen3.8 27BAlibaba | 122.1 | 17.9 GB | ~38 | same size |
| Qwen3.6 27BAlibaba | 111.2 | 17.9 GB | ~38 | same size |
| Hy Memory 30B A3BTencent | — | 19.1 GB | ~184 | same size |
| Muse Glimmer 30BMeta | — | 19.6 GB | ~36 | same size |
| NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA | — | 19.3 GB | ~197 | same size |
| Hy MT2 30B A3BTencent | — | 19.1 GB | ~170 | same size |
Specifications
- Publisher
- IBM
- Family
- Granite
- Parameters
- 29.3B
- Architecture
- GraniteForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 100,352
- Release Date
- 2026-08-07
- License
- Apache 2.0
Frequently Asked Questions
How much VRAM does Granite 4.2 30B need?
Granite 4.2 30B requires 18.4 GB of VRAM at Q4_K_M, or 59.4 GB at BF16. Full 131K context adds up to 33.8 GB (52.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 29.3B × 4.8 bits ÷ 8 = 17.6 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 34.6 GB (at full 131K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 4090 run Granite 4.2 30B?
Yes, at Q5_K_M (21.7 GB) or lower. Higher quantizations like Q6_K (25.0 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
What's the best quantization for Granite 4.2 30B?
For Granite 4.2 30B, Q4_K_M (18.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (21.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 13.3 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run Granite 4.2 30B on a Mac?
Yes — Mac Mini M5 Pro (24 GB) and 106 other Macs can run Granite 4.2 30B. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 18.4 GB of usable unified memory (RAM minus macOS overhead).
Can I run Granite 4.2 30B locally?
Yes — Granite 4.2 30B can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is Granite 4.2 30B?
At Q4_K_M, Granite 4.2 30B can reach ~261 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~36 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 ÷ 18.4 × 0.65 = ~283 tok/s
Estimated speed at Q4_K_M (18.4 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of Granite 4.2 30B?
At Q4_K_M, the download is about 17.57 GB. The full-precision BF16 version is 58.55 GB. The smallest option (Q2_K) is 12.44 GB.
Which GPUs can run Granite 4.2 30B?
8 consumer GPUs can run Granite 4.2 30B at Q4_K_M. Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU has plenty of headroom for comfortable inference.
Which devices can run Granite 4.2 30B?
122 devices with unified memory can run Granite 4.2 30B at Q4_K_M (18.4 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (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.