InternVL3.5 38B on NVIDIA GeForce RTX 4070 SUPER
Can the NVIDIA GeForce RTX 4070 SUPER run InternVL3.5 38B?
Barely: most of the model spills into system RAM
Heavy offload. At Q5_K_M it needs about 30.6 GB of 12.0 GB usable, with an estimated speed of 2.4 tok/s.
- Best quant
Q5_K_M- Generation speed
- 2.4 tok/s
- Prompt processing
- 348 tok/s
- First token (1K prompt)
- 2.9 s
- Largest safe context
- —
Download InternVL3.5 38B
Recommended for the NVIDIA GeForce RTX 4070 SUPER: Q5_K_M. 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 Q5_K_M file (opens in a new tab)
huggingface.co/bartowski/OpenGVLab_InternVL3_5-38B-GGUF (opens in a new tab)
ollama run hf.co/bartowski/OpenGVLab_InternVL3_5-38B-GGUF:Q5_K_MOriginal weights · Hugging Face
Full-precision files from Shanghai AI Lab, for fine-tuning, vLLM, Transformers.
huggingface.co/OpenGVLab/InternVL3_5-38B (opens in a new tab)
How the C grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 33.2 / 45 | |
|---|---|---|
| Memory fit | 4.0 / 25 | |
| Speed | 3.7 / 15 | |
| Memory use | 15.0 / 15 | |
| Total | 55.9 / 100 | 55 ptsUsable (C) · 55 of 100 points: Model quality 33.2/45, Memory fit 4.0/25, Speed 3.7/15, Memory use 15.0/15 |
Every quantization on the NVIDIA GeForce RTX 4070 SUPER
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 18.7 GB | 12.0 GB | 6.9 tok/s | Heavy offload | 49 ptsUsable (C) · 49 of 100 points: Model quality 23.9/45, Memory fit 4.0/25, Speed 6.2/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q3_K_M | 22.2 GB | 12.0 GB | 4.6 tok/s | Heavy offload | 52 ptsUsable (C) · 52 of 100 points: Model quality 28.7/45, Memory fit 4.0/25, Speed 5.1/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q4_K_M | 26.8 GB | 12.0 GB | 3.1 tok/s | Heavy offload | 55 ptsUsable (C) · 55 of 100 points: Model quality 32.5/45, Memory fit 4.0/25, Speed 4.2/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q5_K_M | 30.6 GB | 12.0 GB | 2.4 tok/s | Heavy offload | 55 ptsUsable (C) · 55 of 100 points: Model quality 33.2/45, Memory fit 4.0/25, Speed 3.7/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q6_K | 34.8 GB | 12.0 GB | — | Won't run | 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF (opens in a new tab) |
Q8_0 | 44.0 GB | 12.0 GB | — | Won't run | 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF (opens in a new tab) |
F16 | 80.1 GB | 12.0 GB | — | Won't run | 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF · folder (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
- 87 ptsExcellent (S) · 87 of 100 points: Model quality 33.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090
- 83 ptsGreat (A) · 83 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.4/15 NVIDIA RTX PRO 6000 Blackwell
- 82 ptsGreat (A) · 82 of 100 points: Model quality 28.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090
- 82 ptsGreat (A) · 82 of 100 points: Model quality 28.7/45, Memory fit 24.0/25, Speed 14.8/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090
- 81 ptsGreat (A) · 81 of 100 points: Model quality 28.7/45, Memory fit 24.0/25, Speed 13.9/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX
- 81 ptsGreat (A) · 81 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 9.2/15, Memory use 14.4/15 Apple M4 Max (64 GB)
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.