# Is Avalon-M1-Mini SOTA?

Pending benchmarks. Announced Oct 23, 2026; no independent results yet.

As of Oct 27, 2026, Avalon-M1-Mini is pending benchmarks on isitsota: announced Oct 23, 2026, with no independent results on the boards we track yet.

General Reasoning's research model trained to work as an agent organisation: copies of one policy act as a CEO and hired specialists sharing a message board and workspace, rewarded as a team (reinforcement learning from collective rewards, RLCR). Post-trained from NVIDIA's Nemotron 3 Super base. Training is still running; results so far are a preview, and weights are planned but not out.

Canonical: https://isitsota.com/m/avalon-m1-mini
Last updated: 2026-10-23
Tracking since: 2026-10-23

## Announced facts

| Fact | Value |
| --- | --- |
| Lab | General Reasoning |
| Announced | Oct 23, 2026 |
| API | Not yet |
| Open weights | Announced, not yet published |
| Parameters | 120B total / 12B active |
| Base model | NVIDIA Nemotron 3 Super pretrained base (120B-A12B) |
| Recipe | Reinforcement learning from collective rewards (RLCR): every agent in the organisation gets the same collective advantage |
| Training data | Small SFT set of 38,374 examples, then RL over 147 environments with more than 2 million tasks |
| Status | Still training; the technical report is marked "under revision" |
| Weights | Not released; the lab's roadmap plans to release the model weights, harness and open environments |
| API | None announced |
| Paper | Technical report on gr.inc; final version planned for arXiv |

Tags marked unsure are not stated on the lab's own pages.

## What would let us call it

Verdicts use only independent boards we already track. Two consecutive snapshots are required before any crown.

- [x] Publicly announced with a source
- [ ] Usable by the public (API or weights)
- [ ] Listed on an independent board we track
- [ ] Enough results for a rank in a category
- [ ] Holds across two snapshots (crowns only)

## What the lab claims

Self-reported. Shown for context; not used in any verdict.

- Lab claim: in the lab's organisational evaluations, Avalon-M1-Mini outperforms Nemotron 3 Super, post-trained from the same base without on-policy distillation, on every benchmark shown.
- Lab claim: against Inkling Small, comparing each model's better configuration, Avalon-M1-Mini wins 6 of 18 benchmarks and ties 3 (all run on the lab's own infrastructure).
- Lab claim: working as an organisation instead of alone raises IMO-ProofBench-Advanced from 29.8% to 37.5% and FrontierScience from 55.9% to 63.5%.

## Sources

- LAB: [General Reasoning announcement on X](https://x.com/GenReasoning/status/2113590771722952908) (2026-10-23)
- LAB: [Avalon-M1 release page](https://www.gr.inc/releases/avalon-m1) (2026-10-23)
- PAPER: [Avalon-M1: Reinforcement Learning from Collective Rewards (technical report)](https://www.gr.inc/avalonm1.pdf) (2026-10-23)
- LAB: [Ross Taylor (General Reasoning) post on the base model](https://x.com/rosstaylor90/status/2113616941646573716) (2026-10-23)

Tracking ends Jan 21, 2027 unless the API or weights become available.

## Related

- Lab: [General Reasoning](https://isitsota.com/labs/general-reasoning.md)
- All pending releases: https://isitsota.com/releases.md
- JSON: https://api.isitsota.com/v1/models/avalon-m1-mini