ReMM SLERP 13B
Undi95 · released Sep 4, 2023 · Undi95/ReMM-SLERP-L2-13B
- Type
- Open weightsCreative Commons Attribution-NonCommercial 4.0
- Params
- 13B
- Context
- 6K
about 5K words of context · download allowed, licence restricts use
Our take
Written Aug 2, 2026ReMM SLERP is a 13-billion-parameter text model released in 2023 with a non-commercial licence and a 6,144-token request limit. It is a budget option for light text tasks where the licence permits, though no quality benchmarks have been measured.
Pick this for low-cost non-commercial text work where identical pricing across all three hosts removes comparison effort, and choose Mancer if speed matters. Skip it if you need commercial use, redistribution, or any measured quality data — the licence blocks profit-making use and no benchmark scores exist in our data.
The case for it
- Identical pricing across all three tracked providers removes shopping friction.
- Mancer offers more than twice the throughput of the slowest measured host.
The case against it
- Non-commercial licence only: no profit-making use, redistribution for profit, or fine-tuning for commercial products.
- No benchmark scores in our data, so quality is unverified.
- The slowest measured throughput is sluggish compared with the fastest host.
How good is it?
We hold no score for this model.
We look for every model we track on every board we watch, and none of them has turned up ReMM SLERP 13B — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.
Can you run it yourself?
- Fits in memory
- weights load entirely on the card
- Spills to system RAM
- some weights offload; much slower
- Too large
- will not load even with offload
- est
- size is calculated; the verdict could change by 10%
Comfortable fit
GeForce RTX 4090 · 24 GB
Room to spare. 11.5 GB spare means a 10% error in the size would not change the answer.
GeForce RTX 5090 · 32 GB
Room to spare. 19.5 GB spare means a 10% error in the size would not change the answer.
Apple M1 (8-core GPU) · 16 GB
Borderline fit on an estimated size. It leaves 0.7 GB spare on a size we calculated rather than measured, and a 10% error either way would change the answer.
Memory use by level
Against a 24 GB card.
All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.
Check against your own machine → · All 71 devices, with every size →
Or rent it from someone else
Cheapest of 3 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.
- per 1M tokens
- $0.45 in / $0.65 out
- Context served
- 6K
- Throughput
- Not measured
| Provider | In / out per 1M tokens | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| OpenRouter | $0.45 / $0.65 | 6K | not measured | Unknown | Unknown | Unknown |
| NextBitbf16 | $0.45 / $0.65 | 6K | 22 tok/s | No | No | Confirmed |
| Mancer 2fp8 | $0.45 / $0.65 | 6K | 34 tok/s | No | No | Confirmed |
Across the 3 listings we hold: 2 say they do not train on prompts, 0 say they do and 1 do not say. 2 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.
What each host's API supports
From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.
- ✓
- Supported
- ✗
- Not supported
- Not published
- host gave no parameter list
| Provider | Tool calling | JSON output | Strict schema |
|---|---|---|---|
| OpenRouter | ✗ | ✓ | ✓ |
| NextBitbf16 | ✗ | ✓ | ✓ |
| Mancer 2fp8 | ✗ | ✓ | ✓ |
Tool calling: 0 of 3 listings say yes, 3 say no. JSON output: 3 of 3 listings say yes. Strict schema: 3 of 3 listings say yes.
When we formed this view
Dates behind this page
Prices last checked 5d ago
What we do not know about this model yet
- We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
- No board we watch has turned up a score, so we hold no quality figures at all.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 1 of 3 listings do not say whether they train on prompts.
- We hold no cached-input rate for any of its listings.
Licence and identifiers
What the licence allowsCreative Commons Attribution-NonCommercial 4.0, what it allows commercially, and the identifiers you need to pull this model — its Hugging Face repo, our slug and a machine-readable card.
Licence
Creative Commons Attribution-NonCommercial 4.0
Weights are downloadable but commercial use is prohibited. Research and personal use only.
Identifiers
- Hugging Face
- Undi95/ReMM-SLERP-L2-13B
- Architecture
- Dense
- Modality record
- text->text
- Catalogue slug
- undi95-remm-slerp-13b