Granite4.1 30B Q8 VRAM Requirement and Ollama Model Size

Granite4.1 30B Q8 needs 24GB minimum VRAM, 34GB optimal VRAM, and 64GB+ system RAM for a safer Ollama run. Auto-discovered from local Ollama inventory.. Caveat: Auto-generated family metadata; review for taxonomy accuracy..

Hardware Snapshot

Family Granite4.1
Scenario chat
License scope open-source
Quantization Q8
VRAM minimum 24GB
VRAM optimal 34GB
Best local GPU RTX 6000 Ada 48GB
Cloud fallback A100 80GB
Updated 2026-02-24
Data status Estimated baseline (pending measurement)
Ollama source Library reference (verified: 2026-02-24)
Ollama tag granite4.1:30b
Category chat

Benchmark Anchors

Hardware Expected tok/s
RTX 3090 24GB 7.9
RTX 4090 24GB 10.7
A100 80GB 19

Quick Answers

How much VRAM does Granite4.1 30B Q8 need?
Granite4.1 30B Q8 needs about 24GB minimum VRAM and 34GB optimal VRAM for a safer local run target.
Can Granite4.1 30B Q8 run on an RTX 3090 24GB?
It may load on an RTX 3090 24GB because the minimum estimate is 24GB, but the safer target is 34GB. Expect tighter context or lower throughput.
What is the Ollama command for Granite4.1 30B Q8?
Use ollama run granite4.1:30b. Check the Ollama tag granite4.1:30b before running.
What is the approximate Ollama model size for Granite4.1 30B Q8?
Granite4.1 30B Q8 uses the granite4.1:30b Ollama tag. Treat the Q8 30 profile as smaller than the runtime VRAM budget; use 24GB minimum VRAM and 34GB optimal VRAM as the safer sizing numbers.
How much system RAM does Granite4.1 30B Q8 need in Ollama?
Plan for at least 64GB system RAM alongside 24GB minimum VRAM and 34GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.
What is the RAM vs VRAM requirement for Granite4.1 30B Q8?
Granite4.1 30B Q8 should be sized by GPU VRAM first: 24GB minimum and 34GB optimal. System RAM should be at least 64GB so Ollama has room for CPU-side layers, context, and the surrounding app process.
What is Granite4.1 30B Q8 VRAM usage on an RTX 3090?
Granite4.1 30B Q8 is borderline for an RTX 3090 24GB target. The page estimates 24GB minimum and 34GB optimal VRAM, with spill risk marked as high without a larger GPU or cloud.
Which LocalVRAM profiles share the granite4.1:30b Ollama tag?
LocalVRAM tracks these profiles for the same Ollama tag or model family: Granite4.1 30B Q8 (Q8, 24GB min/34GB optimal); Granite4.1 30B Q4 (Q4, 18GB min/28GB optimal); Granite4.1 30B Q5 (Q5, 20GB min/30GB optimal); Granite4.1 30B FP16 (FP16, 30GB min/42GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
Is Granite4.1 30B Q8 benchmark data measured or estimated?
Granite4.1 30B Q8 currently uses estimated baseline anchors on this page. Verified benchmark data will replace the estimate after a local hardware run is available.

Ollama Model Size and RAM Notes

Ollama tag granite4.1:30b
Run command ollama run granite4.1:30b
Model size guidance Q8 quantization, 30 profile; size runtime by VRAM, not download size alone
Runtime VRAM target 24GB minimum, 34GB optimal
System RAM planning 64GB or more when running this tag locally with Ollama

Download size alone is not a safe runtime budget. Runtime memory also includes KV cache, context length, and GPU layer placement.

Ollama RAM vs VRAM Requirements

GPU VRAM usage estimate 24GB minimum / 34GB optimal
System RAM requirement 64GB or more for Ollama runtime headroom
RTX 3090 24GB fit Borderline
CPU spill risk High without larger GPU or cloud
Context warning Longer context increases KV cache memory, so real VRAM usage can exceed short-prompt estimates.

For Ollama, VRAM is the first fit check. System RAM matters when layers spill to CPU, when context grows, or when the local app stack runs beside the model.

Available Tag Variants and VRAM Targets

Profile Quantization VRAM target Ollama tag
Granite4.1 30B Q8 Q8 24GB min / 34GB optimal granite4.1:30b
Granite4.1 30B Q4 Q4 18GB min / 28GB optimal granite4.1:30b
Granite4.1 30B Q5 Q5 20GB min / 30GB optimal granite4.1:30b
Granite4.1 30B FP16 FP16 30GB min / 42GB optimal granite4.1:30b

Ollama library tags often group multiple quantization choices under one model family. LocalVRAM separates them into VRAM profiles so you can pick the right local target.

Real Hardware Benchmark (RTX 3090)

Real benchmark data not available yet for this tag. Estimated anchors are shown above.

Performance Curve

Reference anchors are baseline estimates. Measured RTX 3090 data is overlaid when available.

Best Hardware for Granite4.1 30B Q8

Local vs Cloud Cost Hint

Mode 40h / month 120h / month
Local power only (3090 baseline) $2.24 $6.72
A100 80GB $78 $234

Related Model Profiles

ollama run granite4.1:30b More chat models More 30b-34b models Benchmark changelog Submit your test result Run on RunPod Try Vast.ai

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This page currently uses estimated benchmark baselines. Measured data will replace it after validation.