Granite 4.0 H Tiny (7B-A1B) on AMD Radeon RX 9060 XT 8GB
Can the AMD Radeon RX 9060 XT 8GB run Granite 4.0 H Tiny (7B-A1B)?
Yes, it runs great
Runs great. At Q6_K it needs about 6.8 GB of 8.0 GB usable, with an estimated speed of 127 tok/s.
- Best quant
Q6_K- Generation speed
- 127 tok/s
- Prompt processing
- 31,744 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 128K
Best app to run it on the AMD Radeon RX 9060 XT 8GB
On Windows
- AMD’s own app: llama.cpp tuned for Radeon on Vulkan and ROCm.
lemonade pull ibm-granite/granite-4.0-h-tiny-GGUF:Q6_KOn Linux
- AMD’s own app: llama.cpp tuned for Radeon on Vulkan and ROCm.
lemonade pull ibm-granite/granite-4.0-h-tiny-GGUF:Q6_KDownload Granite 4.0 H Tiny (7B-A1B)
Recommended for the AMD Radeon RX 9060 XT 8GB: Q6_K. Every other quantization has its own download link in the table below.
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run granite4:tiny-hQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q6_K file (opens in a new tab)
huggingface.co/ibm-granite/granite-4.0-h-tiny-GGUF (opens in a new tab)
ollama run hf.co/ibm-granite/granite-4.0-h-tiny-GGUF:Q6_KOriginal weights · Hugging Face
Full-precision files from IBM, for fine-tuning, vLLM, Transformers.
huggingface.co/ibm-granite/granite-4.0-h-tiny (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from IBM. The weights themselves download from Hugging Face.
github.com/ibm-granite/granite-4.0-language-models (opens in a new tab)
git clone https://github.com/ibm-granite/granite-4.0-language-modelsHow it’s rated
Match score
To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.
| Model quality | 19.6 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 74.6 / 100 |
Every quantization on the AMD Radeon RX 9060 XT 8GB
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 3.8 GB | 8.0 GB | 203 tok/s | Runs great | 30Basic quality (D) · 30 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 4.5 GB | 8.0 GB | 181 tok/s | Runs great | 36Basic quality (D) · 36 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 5.3 GB | 8.0 GB | 158 tok/s | Runs great | 41Fair quality (C) · 41 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 6.0 GB | 8.0 GB | 141 tok/s | Runs great | 42Fair quality (C) · 42 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 6.8 GB | 8.0 GB | 127 tok/s | Runs great | 43Fair quality (C) · 43 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 8.4 GB | 8.0 GB | 93.8 tok/s | Runs welloffloads to RAM | 44Fair quality (C) · 44 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 14.9 GB | 8.0 GB | 27.2 tok/s | Slowheavy RAM offload | 44Fair quality (C) · 44 of 100: how capable the model is at F16, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
-
44Fair quality (C) · 44 of 100: how capable the model is at F16, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
44Fair quality (C) · 44 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 (16 GB)
-
44Fair quality (C) · 44 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
-
44Fair quality (C) · 44 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
44Fair quality (C) · 44 of 100: how capable the model is at F16, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
44Fair quality (C) · 44 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
Quick answers
How much memory does Granite 4.0 H Tiny (7B-A1B) need on the RX 9060 XT 8GB?
At Q6_K it needs about 6.8 GB. The RX 9060 XT 8GB has 8.0 GB usable.
How fast is Granite 4.0 H Tiny (7B-A1B) on the RX 9060 XT 8GB?
About 127 tok/s at Q6_K, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Granite 4.0 H Tiny (7B-A1B) should I use on the RX 9060 XT 8GB?
Q6_K. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.