Llama 3.1 70B Q5 VRAM Requirement and Ollama Model Size
Llama 3.1 70B Q5 needs 40GB minimum VRAM, 50GB optimal VRAM, and 128GB+ system RAM for a safer Ollama run. Popular Ollama model family: Llama 3.1. Caveat: Estimated values are placeholders unless marked measured..
Hardware Snapshot
| Family | Llama 3.1 |
|---|---|
| Scenario | chat |
| License scope | closed-weight |
| Quantization | Q5 |
| VRAM minimum | 40GB |
| VRAM optimal | 50GB |
| Best local GPU | Dual RTX 4090 (model parallel) |
| Cloud fallback | A100 80GB |
| Updated | 2026-02-24 |
| Data status | Estimated baseline (pending measurement) |
| Ollama source | Library reference (verified: 2026-02-24) |
| Ollama tag | llama3.1:70b |
| Category | chat |
Benchmark Anchors
| Hardware | Expected tok/s |
|---|---|
| RTX 3090 24GB | 6.1 |
| RTX 4090 24GB | 8.2 |
| A100 80GB | 14.6 |
Quick Answers
- How much VRAM does Llama 3.1 70B Q5 need?
- Llama 3.1 70B Q5 needs about 40GB minimum VRAM and 50GB optimal VRAM for a safer local run target.
- Can Llama 3.1 70B Q5 run on an RTX 3090 24GB?
- Not as a comfortable local target. Llama 3.1 70B Q5 needs about 40GB minimum and 50GB optimal VRAM, so cloud or larger local GPUs are safer.
- What is the Ollama command for Llama 3.1 70B Q5?
- Use ollama run llama3.1:70b. Check the Ollama tag llama3.1:70b before running.
- What is the approximate Ollama model size for Llama 3.1 70B Q5?
- Llama 3.1 70B Q5 uses the llama3.1:70b Ollama tag. Treat the Q5 70 profile as smaller than the runtime VRAM budget; use 40GB minimum VRAM and 50GB optimal VRAM as the safer sizing numbers.
- How much system RAM does Llama 3.1 70B Q5 need in Ollama?
- Plan for at least 128GB system RAM alongside 40GB minimum VRAM and 50GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.
- What is the RAM vs VRAM requirement for Llama 3.1 70B Q5?
- Llama 3.1 70B Q5 should be sized by GPU VRAM first: 40GB minimum and 50GB optimal. System RAM should be at least 128GB so Ollama has room for CPU-side layers, context, and the surrounding app process.
- What is Llama 3.1 70B Q5 VRAM usage on an RTX 3090?
- Llama 3.1 70B Q5 is not recommended for an RTX 3090 24GB target. The page estimates 40GB minimum and 50GB optimal VRAM, with spill risk marked as high without a larger GPU or cloud.
- Which LocalVRAM profiles share the llama3.1:70b Ollama tag?
- LocalVRAM tracks these profiles for the same Ollama tag or model family: Llama 3.1 70B Q5 (Q5, 40GB min/50GB optimal); Llama 3.1 70B Q4 (Q4, 38GB min/48GB optimal); Llama 3.1 70B Q8 (Q8, 44GB min/54GB optimal); Llama 3.1 70B FP16 (FP16, 50GB min/62GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
- Is Llama 3.1 70B Q5 benchmark data measured or estimated?
- Llama 3.1 70B Q5 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 | llama3.1:70b |
|---|---|
| Run command | ollama run llama3.1:70b |
| Model size guidance | Q5 quantization, 70 profile; size runtime by VRAM, not download size alone |
| Runtime VRAM target | 40GB minimum, 50GB optimal |
| System RAM planning | 128GB 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 | 40GB minimum / 50GB optimal |
|---|---|
| System RAM requirement | 128GB or more for Ollama runtime headroom |
| RTX 3090 24GB fit | Not recommended |
| 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 |
|---|---|---|---|
| Llama 3.1 70B Q5 | Q5 | 40GB min / 50GB optimal | llama3.1:70b |
| Llama 3.1 70B Q4 | Q4 | 38GB min / 48GB optimal | llama3.1:70b |
| Llama 3.1 70B Q8 | Q8 | 44GB min / 54GB optimal | llama3.1:70b |
| Llama 3.1 70B FP16 | FP16 | 50GB min / 62GB optimal | llama3.1:70b |
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 Llama 3.1 70B Q5
- Local run: RTX 3090 (24GB) (Check latest deal) for around 6.1 tok/s on this profile.
- Cloud run: RunPod A100 80GB , 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 |
| A100 80GB | $102 | $306 |
Related Model Profiles
- Llama 3.1 70B Q4 38GB min, 48GB optimal
- Llama 3.1 70B Q8 44GB min, 54GB optimal
- Llama 3.1 70B FP16 50GB min, 62GB optimal
ollama run llama3.1:70b More chat models More 70b-class models Benchmark changelog Submit your test result Run on RunPod Try Vast.ai We may earn a commission if you click links on this page.
This page currently uses estimated benchmark baselines. Measured data will replace it after validation.