FitMyLLM
Shanghai AI Lab/Dense

Shanghai AI LabInternVL3 38B

We introduce InternVL3, an advanced multimodal large language model (MLLM) series that demonstrates superior overall performance.

chatvisionreasoning
38B
Parameters
32K
Context length
2
Benchmarks
14
Quantizations
0
Architecture
Dense
Released
2025-04-15
Layers
64
KV Heads
8
Head Dim
128
Family
other

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
18.9 GB
15.9 + 3.0 KV
low
IQ3_XS3.5
20.1 GB
17.1 + 3.0 KV
low
Q3_K_S3.64
20.8 GB
17.8 + 3.0 KV
low
IQ3_M3.76
21.3 GB
18.3 + 3.0 KV
low
Q3_K_M4
22.5 GB
19.5 + 3.0 KV
low
Q3_K_L4.3
23.9 GB
20.9 + 3.0 KV
moderate
IQ4_XS4.46
24.7 GB
21.7 + 3.0 KV
moderate
Q4_K_S4.67
25.7 GB
22.7 + 3.0 KV
moderate
Q4_K_M4.89
26.7 GB
23.7 + 3.0 KV
good
Q5_K_S5.57
29.9 GB
26.9 + 3.0 KV
good
Q5_K_M5.7
30.6 GB
27.6 + 3.0 KV
good
Q6_K6.56
34.6 GB
31.6 + 3.0 KV
excellent
Q8_08.5
43.9 GB
40.9 + 3.0 KV
lossless
FP1616
79.5 GB
76.5 + 3.0 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

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Community Ratings

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Benchmarks (2)

MMBench87.6
MMMU70.1

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run other:38b-q4_K_M

Tag may need adjustment — check ollama.com/library/other for available tags.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Apple M4 Pro (24GB)
24 GB VRAM • 273 GB/s
APPLE
$1399
NVIDIA L4 24GB
24 GB VRAM • 300 GB/s
NVIDIA
$2500
Apple M2 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M3 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M4 (24GB)
24 GB VRAM • 120 GB/s
APPLE
$699
NVIDIA Tesla M40 24 GB
24 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla P10
24 GB VRAM • 694 GB/s
NVIDIA
NVIDIA Tesla P40
24 GB VRAM • 347 GB/s
NVIDIA
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000
NVIDIA L40G
24 GB VRAM • 864 GB/s
NVIDIA
$5000

Find the best GPU for InternVL3 38B

Build Hardware for InternVL3 38B
▸ SPEC SHEET

InternVL3 38B38B Dense.

▸ SPECIFICATIONS
PARAMETERS
38B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat, vision, reasoning
RELEASE DATE
2025-04-15
PROVIDER
Shanghai AI Lab
FAMILY
other
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2515.9 GB82%
IQ3_XS3.517.1 GB84%
Q3_K_S3.6417.8 GB85%
IQ3_M3.7618.3 GB86%
Q3_K_M419.5 GB88%
Q3_K_L4.320.9 GB90%
IQ4_XS4.4621.7 GB92%
Q4_K_S4.6722.7 GB93%
Q4_K_M4.8923.7 GB94%
Q5_K_S5.5726.9 GB96%
Q5_K_M5.727.6 GB96%
Q6_K6.5631.6 GB97%
Q8_08.540.9 GB100%
FP161676.5 GB100%
§ 01BENCHMARK SCORES
MMMU70.1
MMBench87.6
§ 03COMPATIBLE GPUs
30 @ Q4_K_M