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Local AI

Can the RTX 3080 10GB Run Llama 3.2 3B? (✅ 2.2GB VRAM Needed, 2026)

Can the RTX 3080 10GB run Llama 3.2 3B locally? Yes — runs at Q4 and full Q8 quality. VRAM requirements, expected tokens/sec, the right quantization, and the cheapest GPU that fits if it doesn’t.

← Can It Run? — GPU compatibility matrix · Local LLMs guide

✅ Yes — runs at Q4 and full Q8 quality
Llama 3.2 3B needs 2.2 GB VRAM at Q4. The RTX 3080 10GB has 10 GB.

🦙 Llama 3.2 3B (Meta) is a 3B-parameter model for lightweight chat, on-device assistants, quick tasks. Surprisingly capable for its size; great on low-VRAM cards. The question is whether the RTX 3080 10GB’s 10 GB of VRAM can hold it — here’s the exact math.

VRAM requirements

QuantizationVRAM neededRTX 3080 10GB
Q4_K_M (recommended)2.2 GB
Q8_0 (near-lossless)3.4 GB

Expected performance

Running Llama 3.2 3B at Q4 on the RTX 3080 10GB, expect roughly ~56 tokens/sec in Ollama or llama.cpp — comfortably faster than reading speed, so chat feels responsive.

Headroom: 2.2 GB used of 10 GB leaves about 7.8 GB free for KV cache (context). That’s fine for 4-8K context; for 32K+ you may need a smaller batch or a lower quant.

About the RTX 3080 10GB

Architecture: Ampere · VRAM: 10 GB · Price: ~$400 used.

Good: Fast memory bandwidth, strong tokens/sec for its tier
Watch out: Only 10GB — awkward middle ground, limits model size

Check current RTX 3080 10GB price on Amazon →

Related checks

Other models on the RTX 3080 10GB

Llama 3.2 3B on other GPUs

🎯 LLM Hardware Checker

Enter your exact GPU + RAM, see every model you can run.

💾 VRAM Requirements

Exact VRAM per model at Q4/Q5/Q8/FP16 with context scaling.

Frequently asked questions

Can the RTX 3080 10GB run Llama 3.2 3B?

Yes — runs at Q4 and full Q8 quality. Llama 3.2 3B needs 2.2 GB VRAM at Q4_K_M; the RTX 3080 10GB has 10 GB.

How much VRAM does Llama 3.2 3B need?

Llama 3.2 3B needs about 2.2 GB at Q4_K_M (recommended) and 3.4 GB at Q8_0.

How many tokens per second will the RTX 3080 10GB get on Llama 3.2 3B?

Roughly ~56 tokens/sec at Q4 in Ollama or llama.cpp.