granite-4.1-8b
Q4 GGUF download: ibm-granite/granite-4.1-8b-GGUF - 5.35 GB on disk, read 2026-09-27. VRAM figures above are estimates; this is the actual file size.
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
6.6
AA Index
Coding
9.5
AA Index
Intelligence Index - granite-4.1-8b vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Benchmark data from Artificial Analysis · updated 2026-10-01.
Arena rating (LMArena)
Human preference wins from head-to-head chat battles
| Metric | Value |
|---|---|
| Overall arena rating | 1291.1 |
| Rank (overall) | #249 |
| Battle votes | 4,166 |
Overall rating published by LMArena on 2026-09-30 - a pairwise human-preference Elo across live chat battles; higher is better. Fetched 2026-10-01. Open-weights models compete head-to-head with proprietary ones here — no benchmark prompts, just what people pick.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA Diamond | 43.3 |
Source: Artificial Analysis component evals - updated 2026-10-01.
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
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Deep dive
Notes, sources, and the full write-up
granite-4.1-8b is a 8.8B-parameter apache-2.0 model from ibm-granite. It scores 6.6 on the Artificial Analysis Intelligence Index (coding 9.5). At Q4_K_M it needs roughly 5 GB of VRAM, placing it in the 8–12 GB GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - granite-4.1-8b vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| granite-4.1-8b | 6.7 | 9.5 | 43.3 |
| Claude Fable 5 (with fallback) | 59.9 | 76.5 | 92.6 |
| Claude Opus 4.8 (max) | 55.7 | 74.3 | 92 |
| GPT-5.5 (xhigh) | 54.8 | 74.9 | 93.5 |
| Claude Opus 4.7 (max) | 53.5 | 73.6 | 91.4 |
| Claude Sonnet 5 (max) | 53.4 | 71.5 | 91.1 |
Source: Artificial Analysis (2026-07-04).
Popularity
granite-4.1-8b has 474,685 downloads in the last month on HuggingFace and 203 likes.
Frequently asked
Quick answers to common questions
How much VRAM does granite-4.1-8b need?
granite-4.1-8b with 8.8B parameters needs approximately 5 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is granite-4.1-8b better than other ibm-granite models?
granite-4.1-8b has 8.8B parameters with 131,072 context - a strong choice for general use.
What license is granite-4.1-8b under?
granite-4.1-8b is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs granite-4.1-8b well?
With 8.8B parameters, granite-4.1-8b requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for granite-4.1-8b?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~6 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can granite-4.1-8b's context window handle?
granite-4.1-8b supports a 131,072-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with granite-4.1-8b?
granite-4.1-8b competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec