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Can the NVIDIA GeForce RTX 4070 SUPER run StarCoder 15B?

64 ptsGood (B) · 64 of 100 points: Model quality 11.1/45, Memory fit 24.0/25, Speed 14.8/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q4_K_M it needs about 11.0 GB of 12.0 GB usable, with an estimated speed of 39.1 tok/s.

Best quant
Q4_K_M
Generation speed
39.1 tok/s
Prompt processing
1,616 tok/s
First token (1K prompt)
0.6 s
Largest safe context
8K

Download StarCoder 15B

Recommended for the NVIDIA GeForce RTX 4070 SUPER: Q4_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run starcoder:15b-q4_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q4_K_M file (opens in a new tab)

huggingface.co/mradermacher/starcoder-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/starcoder-i1-GGUF:Q4_K_M

Original weights · Hugging Face

Full-precision files from BigCode, for fine-tuning, vLLM, Transformers.

huggingface.co/bigcode/starcoder (opens in a new tab)

Free Hugging Face account needed: accept the license on the model page and the download starts right away.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the B grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.11.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.14.8 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total64.9 / 10064 ptsGood (B) · 64 of 100 points: Model quality 11.1/45, Memory fit 24.0/25, Speed 14.8/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA GeForce RTX 4070 SUPER

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 7.7 GB 12.0 GB 64.2 tok/s Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 8.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.8/15 GGUF (opens in a new tab)
Q3_K_M 9.1 GB 12.0 GB 50.6 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 9.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 11.0 GB 12.0 GB 39.1 tok/s Tight fit 64 ptsGood (B) · 64 of 100 points: Model quality 11.1/45, Memory fit 24.0/25, Speed 14.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 12.6 GB 12.0 GB 23.9 tok/s Runs with offload 47 ptsUsable (C) · 47 of 100 points: Model quality 11.3/45, Memory fit 10.0/25, Speed 11.6/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 14.3 GB 12.0 GB 12.4 tok/s Runs with offload 44 ptsUsable (C) · 44 of 100 points: Model quality 11.6/45, Memory fit 10.0/25, Speed 8.4/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 18.1 GB 12.0 GB 5.9 tok/s Heavy offload 36 ptsPoor (D) · 36 of 100 points: Model quality 11.7/45, Memory fit 4.0/25, Speed 5.7/15, Memory use 15.0/15
F16 33.0 GB 12.0 GB — Won't run 3 ptsWon't run (F) · 3 of 100 points: Model quality 3.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.