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Granite 4.0 H-Tiny 7B-A1BvsGemma 3 12B

Complete comparison between Granite 4.0 H-Tiny 7B-A1B (7B parameters, IBM) and Gemma 3 12B (12B, Google). VRAM required by quantization, tokens per second measured on 4 reference GPUs, verdict by use case, license, installation commands. All figures are calculated from catalog data—no copy-pasting between pages.

In brief

Feature Granite 4.0 H-Tiny 7B-A1B Gemma 3 12B
Settings 7B 12B
Family Granite Gemma
Author IBM Google
Origin US US
License Apache 2.0 Gemma
Context 128,000 tokens 128,000 tokens
Output October 2025 March 2025

Memory footprint

Approximate VRAM required for inference with an average context window. The winner (in green) is the model that uses less — smaller models have the edge.

Quantization Granite 4.0 H-Tiny 7B-A1B Gemma 3 12B
Q4_K_M (lightweight) 4 GB 7 GB
Q5_K_M (balanced) 5 GB 9 GB
Q8 (near-lossless) 7 GB 13 GB
FP16 (max quality) 14 GB 24 GB
CPU-only RAM 8 GB 14 GB

Estimated speed (tokens/second)

Estimates based on the best quantization that can fit on each GPU. Actual figures depend on the prompt, context, and engine (llama.cpp, vLLM, MLX). Methodology.

Reference GPU Granite 4.0 H-Tiny 7B-A1B Gemma 3 12B
RTX 4090 (24 GB) 350 tok/s · FP16 60 tok/s · FP16
RTX 4080 (16 GB) 180 tok/s · FP16 22 tok/s · Q8
RTX 3060 12GB (12 GB) 60 tok/s · Q8 7 tok/s · Q5_K_M
Apple M4 Pro (48 GB) (36 GB) 180 tok/s · FP16 22 tok/s · FP16

Verdict by use case

For each common use case, we indicate which of the two is better suited based on its tags, size, and specialization.

General chat
Close match — it depends on the exact use case. The two are equivalent on this criterion; decide based on your VRAM or licensing constraints.
Vision / image
Gemma 3 12B wins. Natively supports image inputs.
RAG / long documents
Close match — it depends on the exact use case. The two are equivalent on this criterion; decide based on your VRAM or licensing constraints.
Agents & tool use
Close match — it depends on the exact use case. The two are equivalent on this criterion; decide based on your VRAM or licensing constraints.
Lightweight deployment
Granite 4.0 H-Tiny 7B-A1B wins. Lighter (7B parameters), runs on modest hardware.
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Strengths and weaknesses

IBM · 7B

Granite 4.0 H-Tiny 7B-A1B

Hybrid 7B/1B active. Extremely low compute cost. Edge/embedded.

  • Very low compute cost
  • Apache 2.0
  • Efficient long context
  • Below 3B dense quality for certain tasks

Installation

ollama run granite4:tiny-h
Google · 12B

Gemma 3 12B

Multimodal sweet spot. 128k ctx, vision, 140 languages.

  • Multimodal sweet spot
  • 128k ctx
  • 140 languages
  • License Gemma
  • 9 GB RAM minimum for Ollama

Installation

ollama run gemma3:12b

Frequently asked questions

Which model runs best on RTX 4090 (24 GB): Granite 4.0 H-Tiny 7B-A1B or Gemma 3 12B?

On an RTX 4090, Granite 4.0 H-Tiny 7B-A1B runs at FP16 (~350 tok/s), Gemma 3 12B in FP16 (~60 tok/s). In pure throughput, Granite 4.0 H-Tiny 7B-A1B wins. See the configurator to test your exact GPU.

Which uses the least VRAM?

In Q4_K_M, Granite 4.0 H-Tiny 7B-A1B fits in 4 GB versus 7 GB for its rival—a 3 GB gap, significant if you're targeting an RTX 3060 or an 8 GB 4060 Ti.

Can these models be used in commercial production?

Granite 4.0 H-Tiny 7B-A1B is under Apache 2.0 — free for commercial use. Gemma 3 12B is under Gemma — also check the terms. For SaaS, prefer Apache 2.0 or MIT.

Which one should you choose in 2026?

Depends on your primary constraint. Smaller / faster: Granite 4.0 H-Tiny 7B-A1B (7B). More capable: Gemma 3 12B (12B). If you're unsure, run it configurator with your GPU and use case — it will decide based on both.

Alternatives to consider

If neither works for you, here are some neighboring models you could explore.

Go further