Ministral 3 14B Q5 VRAM Requirement and Ollama Model Size
Ministral 3 14B Q5 needs 14GB minimum VRAM, 16GB optimal VRAM, and 32GB+ system RAM for a safer Ollama run. Top-20 curated profile from ollama.com popular list.. Caveat: Auto-generated family metadata; review for taxonomy accuracy..
Hardware Snapshot
| Family | Ministral 3 |
|---|---|
| Scenario | chat |
| License scope | open-source |
| Quantization | Q5 |
| VRAM minimum | 14GB |
| VRAM optimal | 16GB |
| Best local GPU | RTX 3090 24GB |
| Cloud fallback | A6000 48GB |
| Updated | 2026-02-24 |
| Data status | Verified by Real Hardware |
| Ollama source | Library reference (verified: 2026-02-24) |
| Ollama tag | ministral-3:14b |
| Popularity | New Compact Model |
| Category | Reasoning / Chat |
Benchmark Anchors
| Hardware | Expected tok/s |
|---|---|
| RTX 3090 24GB | 18.9 |
| RTX 4090 24GB | 25.5 |
| A100 80GB | 45.4 |
Quick Answers
- How much VRAM does Ministral 3 14B Q5 need?
- Ministral 3 14B Q5 needs about 14GB minimum VRAM and 16GB optimal VRAM for a safer local run target.
- Can Ministral 3 14B Q5 run on an RTX 3090 24GB?
- Yes. Ministral 3 14B Q5 fits comfortably on an RTX 3090 24GB target with 16GB optimal VRAM.
- What is the Ollama command for Ministral 3 14B Q5?
- Use ollama run ministral-3:14b. Check the Ollama tag ministral-3:14b before running.
- What is the approximate Ollama model size for Ministral 3 14B Q5?
- Ministral 3 14B Q5 uses the ministral-3:14b Ollama tag. Treat the Q5 14 profile as smaller than the runtime VRAM budget; use 14GB minimum VRAM and 16GB optimal VRAM as the safer sizing numbers.
- How much system RAM does Ministral 3 14B Q5 need in Ollama?
- Plan for at least 32GB system RAM alongside 14GB minimum VRAM and 16GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.
- What is the RAM vs VRAM requirement for Ministral 3 14B Q5?
- Ministral 3 14B Q5 should be sized by GPU VRAM first: 14GB minimum and 16GB optimal. System RAM should be at least 32GB so Ollama has room for CPU-side layers, context, and the surrounding app process.
- What is Ministral 3 14B Q5 VRAM usage on an RTX 3090?
- Ministral 3 14B Q5 is comfortable for an RTX 3090 24GB target. The page estimates 14GB minimum and 16GB optimal VRAM, with spill risk marked as moderate at long context.
- Which LocalVRAM profiles share the ministral-3:14b Ollama tag?
- LocalVRAM tracks these profiles for the same Ollama tag or model family: Ministral 3 14B Q5 (Q5, 14GB min/16GB optimal); Ministral 3 14B Q4 (Q4, 12GB min/14GB optimal); Ministral 3 14B Q8 (Q8, 16GB min/26GB optimal); Ministral 3 14B FP16 (FP16, 22GB min/34GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
- Is Ministral 3 14B Q5 benchmark data measured or estimated?
- Ministral 3 14B Q5 has a verified RTX 3090 result of 85.619 tokens/s from LocalVRAM benchmark data.
Ollama Model Size and RAM Notes
| Ollama tag | ministral-3:14b |
|---|---|
| Run command | ollama run ministral-3:14b |
| Model size guidance | Q5 quantization, 14 profile; size runtime by VRAM, not download size alone |
| Runtime VRAM target | 14GB minimum, 16GB optimal |
| System RAM planning | 32GB 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 | 14GB minimum / 16GB optimal |
|---|---|
| System RAM requirement | 32GB or more for Ollama runtime headroom |
| RTX 3090 24GB fit | Comfortable |
| CPU spill risk | Moderate at long context |
| 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 |
|---|---|---|---|
| Ministral 3 14B Q5 | Q5 | 14GB min / 16GB optimal | ministral-3:14b |
| Ministral 3 14B Q4 | Q4 | 12GB min / 14GB optimal | ministral-3:14b |
| Ministral 3 14B Q8 | Q8 | 16GB min / 26GB optimal | ministral-3:14b |
| Ministral 3 14B FP16 | FP16 | 22GB min / 34GB optimal | ministral-3:14b |
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)
| Tokens/s | 85.619 |
|---|---|
| Latency | 1963 ms |
| Prompt tokens | 575 |
| Eval tokens | 128 |
| Test time | 2026-08-19T03:08:42Z |
| GPU model | NVIDIA GeForce RTX 3090 |
Verified by real hardware.
Performance Curve
Reference anchors are baseline estimates. Measured RTX 3090 data is overlaid when available.
Best Hardware for Ministral 3 14B Q5
- Local run: RTX 3090 (24GB) (Check latest deal) for around 85.619 tok/s on this profile.
- Cloud run: RunPod A6000 48GB , about 0.5x 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 |
Related Model Profiles
- Ministral 3 14B Q4 12GB min, 14GB optimal
- Ministral 3 14B Q8 16GB min, 26GB optimal
- Ministral 3 14B FP16 22GB min, 34GB optimal
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