Granite 4.0 H-Tiny 7B-A1BvsMistral Nemo 12B Instruct
Complete comparison between Granite 4.0 H-Tiny 7B-A1B (7B parameters, IBM) and Mistral Nemo 12B Instruct (12B, Mistral AI). VRAM required by quantization, tokens/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 | Mistral Nemo 12B Instruct |
|---|---|---|
| Settings | 7B | 12B |
| Family | Granite | Mistral |
| Author | IBM | Mistral AI |
| Origin | US | FR |
| License | Apache 2.0 | Apache 2.0 |
| Context | 128,000 tokens | 128,000 tokens |
| Output | October 2025 | July 2024 |
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 | Mistral Nemo 12B Instruct |
|---|---|---|
| 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 | 16 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 | Mistral Nemo 12B Instruct |
|---|---|---|
| RTX 4090 (24 GB) | 350 tok/s · FP16 | 70 tok/s · FP16 |
| RTX 4080 (16 GB) | 180 tok/s · FP16 | 25 tok/s · Q8 |
| RTX 3060 12GB (12 GB) | 60 tok/s · Q8 | 8 tok/s · Q5_K_M |
| Apple M4 Pro (48 GB) (36 GB) | 180 tok/s · FP16 | 25 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.
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Strengths and weaknesses
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
Mistral Nemo 12B Instruct
Co-developed with NVIDIA. 128k ctx, Tekken tokenizer, strong in European multilingual.
- 128k context
- Strong in European multilingual performance
- Completely free Apache 2.0
- Excellent 12B compromise
- Worse than Small 3.1 at reasoning
- No vision
Installation
Frequently asked questions
Which model runs best on RTX 4090 (24 GB): Granite 4.0 H-Tiny 7B-A1B or Mistral Nemo 12B Instruct?
On an RTX 4090, Granite 4.0 H-Tiny 7B-A1B runs at FP16 (~350 tok/s), Mistral Nemo 12B Instruct at FP16 (~70 tok/s). In pure throughput, Granite 4.0 H-Tiny 7B-A1B wins. See the configurator to test your exact GPU.
Granite 4.0 H-Tiny 7B-A1B or Mistral Nemo 12B Instruct: which is better in French?
For formal French (writing, summarization, translation), Mistral Nemo 12B Instruct has the edge—trained on a dense French-language corpus. The other remains usable, but for less demanding use cases.
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. Mistral Nemo 12B Instruct is under Apache 2.0 — also free to use. 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: Mistral Nemo 12B Instruct (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.