How much VRAM does All-MiniLM 33M FP16 need?

All-MiniLM 33M FP16 needs about 2GB minimum VRAM and 10GB optimal VRAM for a safer local run target.

Can All-MiniLM 33M FP16 run on an RTX 3090 24GB?

Yes. All-MiniLM 33M FP16 fits comfortably on an RTX 3090 24GB target with 10GB optimal VRAM.

What is the Ollama command for All-MiniLM 33M FP16?

Use ollama run all-minilm:33m. Check the Ollama tag all-minilm:33m before running.

What is the approximate Ollama model size for All-MiniLM 33M FP16?

All-MiniLM 33M FP16 uses the all-minilm:33m Ollama tag. Treat the FP16 0.033 profile as smaller than the runtime VRAM budget; use 2GB minimum VRAM and 10GB optimal VRAM as the safer sizing numbers.

How much system RAM does All-MiniLM 33M FP16 need in Ollama?

Plan for at least 16GB system RAM alongside 2GB minimum VRAM and 10GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.

What is the RAM vs VRAM requirement for All-MiniLM 33M FP16?

All-MiniLM 33M FP16 should be sized by GPU VRAM first: 2GB minimum and 10GB optimal. System RAM should be at least 16GB so Ollama has room for CPU-side layers, context, and the surrounding app process.

What is All-MiniLM 33M FP16 VRAM usage on an RTX 3090?

All-MiniLM 33M FP16 is comfortable for an RTX 3090 24GB target. The page estimates 2GB minimum and 10GB optimal VRAM, with spill risk marked as low.

Which LocalVRAM profiles share the all-minilm:33m Ollama tag?

LocalVRAM tracks these profiles for the same Ollama tag or model family: All-MiniLM 33M FP16 (FP16, 2GB min/10GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.

Is All-MiniLM 33M FP16 benchmark data measured or estimated?

All-MiniLM 33M FP16 currently uses estimated baseline anchors on this page. Verified benchmark data will replace the estimate after a local hardware run is available.

All-MiniLM 33M FP16 VRAM Requirement and Ollama Model Size

All-MiniLM 33M FP16 needs 2GB minimum VRAM, 10GB optimal VRAM, and 16GB+ system RAM for a safer Ollama run. Popular Ollama model family: All-MiniLM. Caveat: Estimated values are placeholders unless marked measured..

Hardware Snapshot

Family	All-MiniLM
Scenario	embedding
License scope	open-source
Quantization	FP16
VRAM minimum	2GB
VRAM optimal	10GB
Best local GPU	RTX 3090 24GB
Cloud fallback	A6000 48GB
Updated	2026-02-24
Data status	Estimated baseline (pending measurement)
Ollama source	Library reference (verified: 2026-02-24)
Ollama tag	`all-minilm:33m`
Category	embedding

Benchmark Anchors

Hardware	Expected tok/s
RTX 3090 24GB	48
RTX 4090 24GB	64.8
A100 80GB	115.2

Quick Answers

How much VRAM does All-MiniLM 33M FP16 need?: All-MiniLM 33M FP16 needs about 2GB minimum VRAM and 10GB optimal VRAM for a safer local run target.
Can All-MiniLM 33M FP16 run on an RTX 3090 24GB?: Yes. All-MiniLM 33M FP16 fits comfortably on an RTX 3090 24GB target with 10GB optimal VRAM.
What is the Ollama command for All-MiniLM 33M FP16?: Use ollama run all-minilm:33m. Check the Ollama tag all-minilm:33m before running.
What is the approximate Ollama model size for All-MiniLM 33M FP16?: All-MiniLM 33M FP16 uses the all-minilm:33m Ollama tag. Treat the FP16 0.033 profile as smaller than the runtime VRAM budget; use 2GB minimum VRAM and 10GB optimal VRAM as the safer sizing numbers.
How much system RAM does All-MiniLM 33M FP16 need in Ollama?: Plan for at least 16GB system RAM alongside 2GB minimum VRAM and 10GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.
What is the RAM vs VRAM requirement for All-MiniLM 33M FP16?: All-MiniLM 33M FP16 should be sized by GPU VRAM first: 2GB minimum and 10GB optimal. System RAM should be at least 16GB so Ollama has room for CPU-side layers, context, and the surrounding app process.
What is All-MiniLM 33M FP16 VRAM usage on an RTX 3090?: All-MiniLM 33M FP16 is comfortable for an RTX 3090 24GB target. The page estimates 2GB minimum and 10GB optimal VRAM, with spill risk marked as low.
Which LocalVRAM profiles share the all-minilm:33m Ollama tag?: LocalVRAM tracks these profiles for the same Ollama tag or model family: All-MiniLM 33M FP16 (FP16, 2GB min/10GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
Is All-MiniLM 33M FP16 benchmark data measured or estimated?: All-MiniLM 33M FP16 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	`all-minilm:33m`
Run command	`ollama run all-minilm:33m`
Model size guidance	FP16 quantization, 0.033 profile; size runtime by VRAM, not download size alone
Runtime VRAM target	2GB minimum, 10GB optimal
System RAM planning	16GB 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	2GB minimum / 10GB optimal
System RAM requirement	16GB or more for Ollama runtime headroom
RTX 3090 24GB fit	Comfortable
CPU spill risk	Low
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.

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 All-MiniLM 33M FP16

Local run: RTX 3090 (24GB) (Check latest deal) for around 48 tok/s on this profile.
Cloud run: RunPod A6000 48GB , about 2.4x the local 3090 speed anchor.
Alternative cloud: Vast.ai options for flexible spot pricing.

Local vs Cloud Cost Hint

Mode	40h / month	120h / month
Local power only (3090 baseline)	$2.24	$6.72
A6000 48GB	$30.4	$91.2

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