Intern-Decision 4B — VRAM & /v1/systemone setup
Written by Jakub Rusinowski · Last updated
InternLM's multimodal 4B decision model on Qwen3.5-4B: answers every question in a schema from one forward pass and accepts optional images.
Intern-Decision 4B needs about 4 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
Call Intern-Decision 4B
Served by reference Python code. This model does not run in Ollama.
Setup for servers other than Ollama →
Build a request for this model Decision models guide
Other decision models: Nimble 9B · Tev1 4B · Tev1 0.8B · Winnow 12B · Winnow E4B · Decider 2B · Decider 4B · Decider 35B-A3B (NVFP4) · JevK5 4B · AutoJev 27B · Laya
Hardware fit
Weights plus overhead plus the KV cache at a 8,192-token prompt, on NVIDIA RTX 4090 (24 GB). A publisher build is sized from its file; the other rows are modelled at a standard quant. Decision requests are short, so no long-context figure is shown.
| Quant | Memory | VRAM | Fit |
|---|---|---|---|
| Q4_K_M 4.83 bpw · modelled quant | 4.6 GB | Fits | |
| Q6_K 6.56 bpw · modelled quant | 5.6 GB | Fits | |
| Q8_0 8.50 bpw · modelled quant | 6.7 GB | Fits |
Reads every question's answer slot from one causal forward pass (Transformers). Accepts optional images.
How it was scored
Two different suites on two different scales. Never compare the numbers across the two cards.
Decision Index 0.2.1 (snapshot 2026-09-28)
Decision Index 0.2.1- ECE (lower is better)
- 0.0278
- Median compute
- 44.2 ms on 1x NVIDIA RTX PRO 6000 (96 GB)
Community-maintained; not affiliated with the model authors.
Source ↗Decision models are not ranked on chat, creative or coding scores.
Specifications
Verified — Checked against the primary source — the model card or the vendor spec page — and corroborated by a second independent source. Still unconfirmed: weightsGbByQuant.
- Parameters
- 4.66B
- Context window
- Not published
- Architecture
- Fine-tune of Qwen/Qwen3.5-4B
- Provider
- InternLM
- Licence
- Apache-2.0
- Specified at
- Q4_K_M
- System RAM
- 8 GB
- Record updated
- 2026-09-30
Commercial use permitted. No usage restrictions beyond attribution.
Intern-Decision 4B — frequently asked questions
What is Intern-Decision 4B?
Intern-Decision 4B is a decision model: you send it a state and typed questions (choice, yes/no/unknown, or a score) and it returns one answer per question with a probability for every option. It is not a chat model.
How do I run Intern-Decision 4B locally?
Intern-Decision 4B does not run in Ollama. Served by reference Python code. This model does not run in Ollama. See the setup guide for servers other than Ollama.
How much memory does Intern-Decision 4B need?
About 4 GB for the weights plus overhead at Q4_K_M, before the prompt's KV cache. Decision prompts are short, so the cache stays small.
How accurate is Intern-Decision 4B?
It has two separate published scores on two different suites — the author's own benchmark and the community Decision Index 0.2.1. They are not comparable with each other, and neither is a calibration guarantee.