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Can the NVIDIA GeForce RTX 4070 SUPER run Seed-Coder 8B Instruct?

79 ptsGreat (A) · 79 of 100 points: Model quality 24.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 9.0 GB of 12.0 GB usable, with an estimated speed of 52.0 tok/s.

Best quant
Q6_K
Generation speed
52.0 tok/s
Prompt processing
3,098 tok/s
First token (1K prompt)
0.3 s
Largest safe context
30K

Download Seed-Coder 8B Instruct

Recommended for the NVIDIA GeForce RTX 4070 SUPER: Q6_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q6_K file (opens in a new tab)

huggingface.co/unsloth/Seed-Coder-8B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/unsloth/Seed-Coder-8B-Instruct-GGUF:Q6_K

Original weights · Hugging Face

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

huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from ByteDance. The weights themselves download from Hugging Face.

github.com/ByteDance-Seed/Seed-Coder (opens in a new tab)

git clone https://github.com/ByteDance-Seed/Seed-Coder

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the A 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.24.9 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 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
Total79.9 / 10079 ptsGreat (A) · 79 of 100 points: Model quality 24.9/45, Memory fit 25.0/25, Speed 15.0/15, 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 5.6 GB 12.0 GB 123 tok/s Runs well 68 ptsGood (B) · 68 of 100 points: Model quality 17.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.7/15 GGUF (opens in a new tab)
Q3_K_M 6.3 GB 12.0 GB 96.9 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 21.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q4_K_M 7.3 GB 12.0 GB 75.0 tok/s Runs well 77 ptsGreat (A) · 77 of 100 points: Model quality 23.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.1/15 GGUF (opens in a new tab)
Q5_K_M 8.1 GB 12.0 GB 62.0 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 24.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 9.0 GB 12.0 GB 52.0 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 24.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 11.0 GB 12.0 GB 38.2 tok/s Tight fit 78 ptsGreat (A) · 78 of 100 points: Model quality 25.2/45, Memory fit 24.0/25, Speed 14.7/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 18.8 GB 12.0 GB 4.8 tok/s Heavy offload 49 ptsUsable (C) · 49 of 100 points: Model quality 25.2/45, Memory fit 4.0/25, Speed 5.2/15, Memory use 15.0/15 GGUF (opens in a new tab) 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.