Ring-2.6-1T
inclusionAI · released May 8, 2026 · inclusionAI/Ring-2.6-1T
- Type
- Open weightsMIT License
- Params
- Not published
- Context
- 262K
about 197K words of context
Our take
Written Aug 3, 2026Ring-2.6-1T is a downloadable text model from inclusionAI with a permissive MIT licence and a 262,144-token request limit. Its input rate is budget-friendly, though output costs several times more per token, and no benchmark scores are on record.
Pick this for long-document processing where input volume dominates and you need a quarter-million-token request limit under a permissive licence. Use it if you want to self-host or modify weights without restriction. Skip it if you need verified quality data, balanced input-output pricing, or multimodal support.
The case for it
- Extremely long request limit at budget input rates: 262,144 tokens with cheap input per million tokens.
- Permissive MIT licence allows commercial use, modification and redistribution.
- One tracked tier has measured throughput at 50 tokens per second.
The case against it
- Output costs several times more per token than input on every tier — the gap is large and consistent.
- No benchmark scores on record, so capability is unverified against any measured task.
- Total and active parameters are both undisclosed, leaving no basis to judge efficiency or model class.
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 Ring-2.6-1T — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.
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
- $0.075 in / $0.63 out
- Context served
- 262K
- Throughput
- Not measured
| Provider | In / out per 1M tokens | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| OpenRouter | $0.075 / $0.63 | 262K | not measured | Unknown | Unknown | Unknown |
| Novita AI | $0.075 / $0.63 | 262K | 64 tok/s | No | No | Confirmed |
| Novita AI | $0.30 / $2.50 | 262K | not measured | Unknown | Unknown | Unknown |
Novita AIAcross the 3 listings we hold: 1 say they do not train on prompts, 0 say they do and 2 do not say. 1 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 | ✓ | ✓ | ✗ |
| Novita AI | ✓ | ✓ | ✗ |
| Novita AI |
Tool calling: 2 of 3 listings say yes, 1 publishes no parameter list. JSON output: 2 of 3 listings say yes, 1 publishes no parameter list. Strict schema: 0 of 3 listings say yes, 2 say no, 1 publishes no parameter list.
When we formed this view
Dates behind this page
Prices last checked 9d ago
What we do not know about this model yet
- No board we watch has turned up a score, so we hold no quality figures at all.
- 1 of 3 listings publish no parameter list, so what their API accepts is unknown to us.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 2 of 3 listings do not say whether they train on prompts.
Licence and identifiers
What the licence allowsMIT License, 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
MIT License
Fully permissive: do anything with attribution. No patent grant, unlike Apache-2.0.
Identifiers
- Hugging Face
- inclusionAI/Ring-2.6-1T
- Modality record
- text->text
- Catalogue slug
- inclusionai-ring-2-6-1t