BGE-M3 567M FP16 VRAM Requirement and Ollama Model Size
BGE-M3 567M FP16 needs 4GB minimum VRAM, 12GB optimal VRAM, and 16GB+ system RAM for a safer Ollama run. Popular Ollama model family: BGE-M3. Caveat: Estimated values are placeholders unless marked measured..
Hardware Snapshot
| Family | BGE-M3 |
|---|---|
| Scenario | embedding |
| License scope | open-source |
| Quantization | FP16 |
| VRAM minimum | 4GB |
| VRAM optimal | 12GB |
| 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 | bge-m3:567m |
| 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 BGE-M3 567M FP16 need?
- BGE-M3 567M FP16 needs about 4GB minimum VRAM and 12GB optimal VRAM for a safer local run target.
- Can BGE-M3 567M FP16 run on an RTX 3090 24GB?
- Yes. BGE-M3 567M FP16 fits comfortably on an RTX 3090 24GB target with 12GB optimal VRAM.
- What is the Ollama command for BGE-M3 567M FP16?
- Use ollama run bge-m3:567m. Check the Ollama tag bge-m3:567m before running.
- What is the approximate Ollama model size for BGE-M3 567M FP16?
- BGE-M3 567M FP16 uses the bge-m3:567m Ollama tag. Treat the FP16 0.567 profile as smaller than the runtime VRAM budget; use 4GB minimum VRAM and 12GB optimal VRAM as the safer sizing numbers.
- How much system RAM does BGE-M3 567M FP16 need in Ollama?
- Plan for at least 16GB system RAM alongside 4GB minimum VRAM and 12GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.
- What is the RAM vs VRAM requirement for BGE-M3 567M FP16?
- BGE-M3 567M FP16 should be sized by GPU VRAM first: 4GB minimum and 12GB optimal. System RAM should be at least 16GB so Ollama has room for CPU-side layers, context, and the surrounding app process.
- What is BGE-M3 567M FP16 VRAM usage on an RTX 3090?
- BGE-M3 567M FP16 is comfortable for an RTX 3090 24GB target. The page estimates 4GB minimum and 12GB optimal VRAM, with spill risk marked as low.
- Which LocalVRAM profiles share the bge-m3:567m Ollama tag?
- LocalVRAM tracks these profiles for the same Ollama tag or model family: BGE-M3 567M FP16 (FP16, 4GB min/12GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
- Is BGE-M3 567M FP16 benchmark data measured or estimated?
- BGE-M3 567M 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 | bge-m3:567m |
|---|---|
| Run command | ollama run bge-m3:567m |
| Model size guidance | FP16 quantization, 0.567 profile; size runtime by VRAM, not download size alone |
| Runtime VRAM target | 4GB minimum, 12GB 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 | 4GB minimum / 12GB 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 BGE-M3 567M 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.