granite 4.2 3b

3.7B parameters · 128k context · Apache 2.0 · released 2026-08-25

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In short

granite 4.2 3b is an open model from IBM with 3.7B parameters. At Q4_K_M, granite 4.2 3b needs about 4 GB of memory at 8k context and 14 GB at 128k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in the UK that runs granite 4.2 3b fully in memory at 128k context is the NVIDIA GeForce RTX 5060 Ti 16GB, £550 at eBay, at about 19 tok/s (estimated).

Updated . Speeds are estimates; how they are worked out.

What to run it on in the UK

Fully in memory at 128k context, priced at retailers today.

All hardware that runs it

Everything we price, best value first. Two cards split the model by layers.

HardwareQuantFitsDecodePricetok/s per 1,000
NVIDIA Tesla P40Q8_0fits15 tok/s£26156.4
AMD Radeon RX 7600 XTQ8_0fits11 tok/s£34831.0
AMD Radeon RX 9060 XT 16GBQ8_0fits12 tok/s£49924.1
NVIDIA GeForce RTX 5060 Ti 16GBQ8_0fits19 tok/s£55034.5
AMD Radeon RX 7800 XTQ8_0fits24 tok/s£56841.4
Intel Arc A770 16GBQ8_0fits19 tok/s£58832.5
AMD Radeon RX 9070 XTQ8_0fits24 tok/s£67036.0
Intel Arc Pro B60Q8_0fits16 tok/s£74221.0
AMD Radeon RX 7900 XTQ8_0fits30 tok/s£78938.1
NVIDIA GeForce RTX 4070 Ti SuperQ8_0fits29 tok/s£95030.0
NVIDIA GeForce RTX 5070 TiQ8_0fits38 tok/s£97539.0
NVIDIA GeForce RTX 4060 Ti 16GBQ8_0fits12 tok/s£97712.5
AMD Radeon RX 7900 XTXQ8_0fits36 tok/s£99936.1
NVIDIA GeForce RTX 5080Q8_0fits41 tok/s£1,19933.9
Mac mini M4 32GBQ8_0fits5 tok/s£1,2004.4
NVIDIA GeForce RTX 4080 SuperQ8_0fits31 tok/s£1,42921.8
AMD Radeon AI PRO R9700Q8_0fits24 tok/s£1,67414.4
NVIDIA GeForce RTX 3090Q8_0fits40 tok/s£1,70723.3
NVIDIA GeForce RTX 3090 TiQ8_0fits43 tok/s£2,19919.4
Mac mini M4 Pro 48GBQ8_0fits12 tok/s£3,0004.0
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ8_0fits10 tok/s£3,3202.9
Mac Studio M4 Max 64GBQ8_0fits24 tok/s£3,3997.1
NVIDIA GeForce RTX 5090Q8_0fits76 tok/s£5,00015.2
Mac Studio M3 Ultra 96GBQ8_0fits36 tok/s£5,4996.6
NVIDIA GeForce RTX 4090Q8_0fits43 tok/s£6,0157.1
Mac Studio M3 Ultra 256GBQ8_0fits36 tok/s£8,4994.3
Mac Studio M3 Ultra 512GBQ8_0fits36 tok/s£17,4952.1
NVIDIA RTX PRO 6000 BlackwellQ8_0fits76 tok/s£29,5042.6
Mac Studio M4 Max 128GBQ8_0fits24 tok/s––
Mac mini M4 Pro 64GBQ8_0fits12 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ8_0fits10 tok/s––
NVIDIA DGX Spark 128GBQ8_0fits12 tok/s––
ASUS Ascent GX10 128GBQ8_0fits12 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBQ8_0fits10 tok/s––
Intel Arc B580Q4_K_Moffload11 tok/s£34930.1
NVIDIA GeForce RTX 3060 12GBQ4_K_Moffload11 tok/s£39027.9
NVIDIA GeForce RTX 3080 10GBQ4_K_Moffload10 tok/s£46621.0
NVIDIA GeForce RTX 5070Q4_K_Moffload14 tok/s£69520.6
NVIDIA GeForce RTX 4070 SuperQ4_K_Moffload13 tok/s£87414.7

1 other card or machine we price cannot hold it at this context.

Memory needed

Weights, KV cache and runtime buffers at each context length (KV cache at fp16).

QuantFile@8k@32k@64k@128k
Q4_K_Mgguf2.2 GB3.5 GB5.5 GB8.2 GB13.6 GB
Q5_K_Mgguf2.5 GB3.9 GB5.9 GB8.6 GB13.9 GB
Q6_Kgguf2.9 GB4.3 GB6.3 GB9.0 GB14.4 GB
Q8_0gguf3.6 GB5.0 GB7.0 GB9.7 GB15.1 GB

Run it

Copy a command for the runtime you use.

  • Q4_K_M
    • Ollamaollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q4_K_M
    • LM Studiolms get bartowski/granite-4.2-3b-GGUF@q4_k_m
    • llama.cppllama-server -hf bartowski/granite-4.2-3b-GGUF:Q4_K_M
  • Q5_K_M
    • Ollamaollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q5_K_M
    • LM Studiolms get bartowski/granite-4.2-3b-GGUF@q5_k_m
    • llama.cppllama-server -hf bartowski/granite-4.2-3b-GGUF:Q5_K_M
  • Q6_K
    • Ollamaollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q6_K
    • LM Studiolms get bartowski/granite-4.2-3b-GGUF@q6_k
    • llama.cppllama-server -hf bartowski/granite-4.2-3b-GGUF:Q6_K
  • Q8_0
    • Ollamaollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q8_0
    • LM Studiolms get bartowski/granite-4.2-3b-GGUF@q8_0
    • llama.cppllama-server -hf bartowski/granite-4.2-3b-GGUF:Q8_0

Notes

Native context is 128K, and the card also claims a long-context extension to 512K; its serving examples use 131072. The vLLM reasoning parser needs vLLM v0.20+ (or SGLang v0.5.18+), and the recommended sampling is temperature=1.0 and top_p=0.95.

Questions

How much VRAM does granite 4.2 3b need?
At Q4_K_M, granite 4.2 3b needs about 4 GB of memory at 8k context and 14 GB at 128k, counting the weights, the KV cache and runtime buffers.
What is the best GPU for running granite 4.2 3b locally?
The cheapest hardware in the UK that runs granite 4.2 3b fully in memory at 128k context is the NVIDIA GeForce RTX 5060 Ti 16GB, £550 at eBay, at about 19 tok/s (estimated). The best value is the AMD Radeon RX 7800 XT (about 24 tok/s for £568). The fastest we price is the NVIDIA GeForce RTX 5090, at about 76 tok/s.
Can I run granite 4.2 3b on a 16 GB GPU?
Yes: at Q8_0 it fits fully in 16 GB at 128k context. On the NVIDIA GeForce RTX 5080 it runs at about 41 tok/s (estimated).
Can I run granite 4.2 3b on a 24 GB GPU?
Yes: at Q8_0 it fits fully in 24 GB at 128k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 43 tok/s (estimated).
How do I run granite 4.2 3b locally?
With Ollama: ollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q4_K_M (the Q4_K_M build). LM Studio and llama.cpp commands are on this page.
What licence is granite 4.2 3b released under?
Apache 2.0, which allows commercial use.