A structured set of research notes on Multimodal Reasoning, with concrete evaluation references and open questions. Plans and hypotheses are kept separate from completed results.
Runs On
What it takes to serve multimodal-reasoning-base (33,088 parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 18, 2026.
Model Card
By Jonas W. Schmidt, published under cc-by-4.0, revision 6b50e81f4d43.
A structured set of research notes on Multimodal Reasoning, with concrete evaluation references and open questions. Plans and hypotheses are kept separate from completed results. - the scope of the research question and likely confounders - a proposed comparison with matched baselines - concrete evaluation context such as VQAv2, GQA, and NLVR2 - reproducibility checks, failure modes, and open questions - topic-relevant references Start with review.md for the full note. Sections labeled as plans or hypotheses should not be interpreted as experimental results. If results are added later, they should include dataset versions, commands, seeds, hardware, and raw logs. The note is intentionally…
Read Jonas W. Schmidt's full model card
Notes on Multimodal Reasoning
Repository summary
A structured set of research notes on Multimodal Reasoning, with concrete evaluation references and open questions. Plans and hypotheses are kept separate from completed results.
What is covered
- the scope of the research question and likely confounders
- a proposed comparison with matched baselines
- concrete evaluation context such as VQAv2, GQA, and NLVR2
- reproducibility checks, failure modes, and open questions
- topic-relevant references
How to read this repository
Start with review.md for the full note. Sections labeled as plans or hypotheses should not be interpreted as experimental results. If results are added later, they should include dataset versions, commands, seeds, hardware, and raw logs.
Scope and limitations
The note is intentionally exploratory. It does not claim benchmark improvements, completed ablations, released code, or a trained checkpoint. References and proposed datasets provide a starting point for verification rather than evidence that the study has already been run.
Files
review.md— primary artifactREADME.md— this documentation
License
Released under cc-by-4.0. Review the source-data terms separately when this repository is used with external datasets.
Configuration
- Architecture
- CustomResearchModel
- Context length (tokens)
- 128
- Layers
- 8
- Hidden size
- 256
- Feed-forward size
- 512
- Attention heads
- 2
- Model type
- transformer
Identity and Version
- Repository
- jkschmidt/multimodal-reasoning-base
- Publisher
- Jonas W. Schmidt
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 33,088 parameters
- Languages
- Not stated by the source
- Revision
- 6b50e81f4d4304b5e88bef0f44e08b9328e9d228
- First published
- 2026-09-18
- Last updated
- 2026-09-18
Files and Weights
6 files, 139.5 KB in total. The weights are 1 file totalling 132.8 KB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 132.8 KB | e3990cda2590 |
| config.json | Configuration | 440 B | — |
| training_args.json | Configuration | 188 B | — |
| README.md | Documentation | 1.4 KB | — |
| review.md | Documentation | 3.1 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
License and Download
- License
- cc-by-4.0
- Access
- Open weights, no gate
- Download size
- 132.8 KB
Released by Jonas W. Schmidt through its official repository on Hugging Face. Read the license.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 132.8 KB |
| 16-bit | 0.0 GB |
| 8-bit | 0.0 GB |
| 4-bit | 0.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About multimodal-reasoning-base
How much GPU memory does multimodal-reasoning-base need?
About 0 GB at 16-bit and 0 GB at 4-bit: the weights (33,088 parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run multimodal-reasoning-base on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use multimodal-reasoning-base commercially?
Yes. multimodal-reasoning-base is released under Creative Commons Attribution 4.0. CC BY 4.0 permits sharing and adapting the work, including commercially, provided the creator is credited and changes are indicated.
What is multimodal-reasoning-base's context length?
128 tokens, from the maximum position embeddings in its published configuration.