Llama 3.3 70B
Meta · Llama
Meta's flagship open-weight model and the go-to choice for users who want GPT-4-class performance without sending data to the cloud. Consistently tops open-source leaderboards. Needs ~48 GB VRAM at Q4_K_M — a dual-GPU rig or Apple Silicon with 48 GB unified memory.
Params
70B
License
Llama 3.3 Community
Context
128K
Min VRAM
48 GB
Min RAM
64 GB
Tier
Giant
Run locally with Ollama
ollama run llama3.3:70bOnce running, Ollama exposes an OpenAI-compatible endpoint at localhost:11434/v1.
Will it run on my hardware?
Llama 3.3 70B needs about 48 GB of fast memory at Q4. Here is what in our hardware database clears that bar.
Runs at full speed · 2
Runs, but slower on shared memory · 2
11 other tracked configurations do not have enough memory.
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Specifications
| Parameters | 70B |
|---|---|
| Context window | 128K |
| License | Llama 3.3 Community |
| Min VRAM (Q4) | 48 GB |
| Min RAM | 64 GB |
| Recommended tier | Giant |
| Best for | codingchatanalysiscreative writing |
Variants on Ollama
Ollama serves the Q4_K_M quantization by default. Higher-precision tags exist for users with more memory.
Llama 3.3 70B
ollama run llama3.3:70bollama pull llama3.3:q8_0ollama pull llama3.3:fp16Exact quantization tags vary per model — run ollama show llama3.3 or check the tags page for the full list.
Popularity trend (illustrative)
Illustrative adoption trend, not actual download counts. We do not publish a download number for any model because we have no honest source for it.
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