Can RTX 3090 run Llama 70B Q4 locally?

Yes, in many setups. Keep context length conservative and plan cloud fallback for heavy or long-context sessions.

Should I use Llama 3 70B or Llama 3.3 70B?

Use the newer 3.3 profile first, then validate quality and latency against your workload before production rollout.

Llama 70B Q4 on RTX 3090: Practical 2026 Decision Page

This page exists for users searching llama 70b q4 directly. If you are choosing between local RTX 3090 and cloud fallback, start with the measured and baseline anchors below.

Quick Answer

24GB VRAM is the minimum tier for 70B Q4-class local experiments.
Llama 3.3 70B Q4 is the recommended first profile for new runs, with cloud fallback for long-context workloads.
If your target is throughput-first production, compare 3090 vs 4090 and keep a RunPod path ready.

Measured Local Anchor (RTX 3090)

Profile	Ollama tag	3090 tokens/s	Status
Llama 3.3 70B Q4	`llama3.3:70b`	3.795	Measured
Llama 3 70B Q4	`llama3:70b`	6.8	Baseline estimate

Measured entries come from latest benchmark snapshots; non-measured entries are kept as clearly labeled baseline estimates.

3090 vs 4090 vs A100 Baseline Comparison

Profile	RTX 3090	RTX 4090	A100 80GB
Llama 3.3 70B Q4	6.8	9.2	16.3
Llama 3 70B Q4	6.8	9.2	16.3

Recommended Execution Path

Run ollama run llama3.3:70b first and capture tokens/s on your own prompt set.
If latency or context ceiling blocks your target, move burst traffic to RunPod or Vast.ai.
For stable daily local usage, compare with 3090 vs 4090 guide before hardware spend.

Open Llama 3.3 70B profile Open Llama 3 70B profile Run Q4 vs Q8 blind test workflow Check local GPU upgrade path

We may earn a commission if you purchase via links on this page.