Llama 4 128X17B Q4 VRAM Requirement and Ollama Model Size
Llama 4 128X17B Q4 needs 418GB minimum VRAM, 428GB optimal VRAM, and 128GB+ system RAM for a safer Ollama run. Popular Ollama model family: Llama 4. Caveat: Estimated values are placeholders unless marked measured..
Hardware Snapshot
| Family | Llama 4 |
|---|---|
| Scenario | multimodal |
| License scope | closed-weight |
| Quantization | Q4 |
| VRAM minimum | 418GB |
| VRAM optimal | 428GB |
| Best local GPU | Cloud-first (no practical single-GPU local) |
| Cloud fallback | H100/H200 class |
| Updated | 2026-02-24 |
| Data status | Estimated baseline (pending measurement) |
| Ollama source | Library reference (verified: 2026-02-24) |
| Ollama tag | llama4:128x17b |
| Category | multimodal |
Benchmark Anchors
| Hardware | Expected tok/s |
|---|---|
| RTX 3090 24GB | 1.1 |
| RTX 4090 24GB | 1.5 |
| A100 80GB | 2.6 |
Quick Answers
- How much VRAM does Llama 4 128X17B Q4 need?
- Llama 4 128X17B Q4 needs about 418GB minimum VRAM and 428GB optimal VRAM for a safer local run target.
- Can Llama 4 128X17B Q4 run on an RTX 3090 24GB?
- Not as a comfortable local target. Llama 4 128X17B Q4 needs about 418GB minimum and 428GB optimal VRAM, so cloud or larger local GPUs are safer.
- What is the Ollama command for Llama 4 128X17B Q4?
- Use ollama run llama4:128x17b. Check the Ollama tag llama4:128x17b before running.
- What is the approximate Ollama model size for Llama 4 128X17B Q4?
- Llama 4 128X17B Q4 uses the llama4:128x17b Ollama tag. Treat the Q4 2176 profile as smaller than the runtime VRAM budget; use 418GB minimum VRAM and 428GB optimal VRAM as the safer sizing numbers.
- How much system RAM does Llama 4 128X17B Q4 need in Ollama?
- Plan for at least 128GB system RAM alongside 418GB minimum VRAM and 428GB 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 4 128X17B Q4?
- Llama 4 128X17B Q4 should be sized by GPU VRAM first: 418GB minimum and 428GB 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 4 128X17B Q4 VRAM usage on an RTX 3090?
- Llama 4 128X17B Q4 is not recommended for an RTX 3090 24GB target. The page estimates 418GB minimum and 428GB optimal VRAM, with spill risk marked as high without a larger GPU or cloud.
- Which LocalVRAM profiles share the llama4:128x17b Ollama tag?
- LocalVRAM tracks these profiles for the same Ollama tag or model family: Llama 4 128X17B Q4 (Q4, 418GB min/428GB optimal); Llama 4 128X17B Q5 (Q5, 420GB min/430GB optimal); Llama 4 128X17B Q8 (Q8, 424GB min/434GB optimal); Llama 4 128X17B FP16 (FP16, 430GB min/442GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
- Is Llama 4 128X17B Q4 benchmark data measured or estimated?
- Llama 4 128X17B Q4 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 | llama4:128x17b |
|---|---|
| Run command | ollama run llama4:128x17b |
| Model size guidance | Q4 quantization, 2176 profile; size runtime by VRAM, not download size alone |
| Runtime VRAM target | 418GB minimum, 428GB 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 | 418GB minimum / 428GB 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 4 128X17B Q4 | Q4 | 418GB min / 428GB optimal | llama4:128x17b |
| Llama 4 128X17B Q5 | Q5 | 420GB min / 430GB optimal | llama4:128x17b |
| Llama 4 128X17B Q8 | Q8 | 424GB min / 434GB optimal | llama4:128x17b |
| Llama 4 128X17B FP16 | FP16 | 430GB min / 442GB optimal | llama4:128x17b |
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 4 128X17B Q4
- Local run: RTX 3090 (24GB) (Check latest deal) for around 1.1 tok/s on this profile.
- Cloud run: RunPod H100/H200 class , 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 |
| H100/H200 class | $196 | $588 |
Related Model Profiles
- Llama 4 128X17B Q5 420GB min, 430GB optimal
- Llama 4 128X17B Q8 424GB min, 434GB optimal
- Llama 4 128X17B FP16 430GB min, 442GB optimal
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This page currently uses estimated benchmark baselines. Measured data will replace it after validation.