Can RTX 5080 run StarCoder2 7B?
Yes — runs locally
~78 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 5080 (16 GB VRAM) handles StarCoder2 7B comfortably using the Q8_0 quantization, which fits in 7.6 GB. Expected throughput is around 78 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Larger code model with better completions.
How to run it
- 1. Install Ollama or LM Studio.
- 2. Pull the
Q8_0GGUF — best balance of quality and speed on 16 GB. - 3. Start chatting. Expect ~78 tok/sec on first-token, faster after warmup.
Other models that run great on RTX 5080
FAQ (20)
What GPU do I need to run StarCoder2 7B?
To run StarCoder2 7B, you need a GPU with at least 4.7 GB of VRAM for the lowest quantization level, and up to 7.6 GB for higher precision levels.
Is StarCoder2 7B good for coding?
Yes, StarCoder2 7B is specifically designed for coding tasks and offers better completions compared to smaller models, making it a strong choice for developers.
StarCoder2 7B vs Llama 3.1 8B?
StarCoder2 7B is optimized for coding tasks, while Llama 3.1 8B is more general-purpose. StarCoder2 7B has a larger context length of 16384 tokens, which is beneficial for complex coding tasks.
Can I run StarCoder2 7B on a Mac?
Yes, you can run StarCoder2 7B on a Mac, but you will need a compatible GPU with sufficient VRAM and the necessary drivers installed.
How much VRAM does StarCoder2 7B need?
StarCoder2 7B requires between 4.7 GB and 7.6 GB of VRAM, depending on the quantization level used.
Is StarCoder2 7B censored?
No, StarCoder2 7B is not censored, but it adheres to the bigcode-openrail-m license, which includes guidelines for responsible use.
Is StarCoder2 7B commercial-use allowed?
Yes, StarCoder2 7B can be used commercially, but you must comply with the terms of the bigcode-openrail-m license, which includes restrictions on certain uses.
StarCoder2 7B context length?
StarCoder2 7B has a context length of 16384 tokens, which is significantly longer than many other models and allows for more complex code generation and understanding.
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