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OPEN-1B makes every training step independently auditable

Gensyn releases OPEN-1B, a 1.61B-parameter model trained on 400B tokens with a state hash for every optimizer step. Its fixed-order kernels, data stream and topology-independent reductions reproduce the same bits across CPU, CUDA and Metal. The release includes the full corpus, 810 checkpoints, training code and an audit-replay harness. A volunteer can verify one step on commodity hardware instead of rerunning the full training job.

Imported from the existing research archive. Migration preserves the recorded judgment and is not a fresh verification.

What this means for you

For teams evaluating open models, this adds a verifiable tier above published weights and recipes. It can expose undeclared data or training changes without requiring an auditor to fund a full retraining run. The 1B scale and custom deterministic kernels make it a research prototype rather than a drop-in recipe for frontier training.

FRONTIER WATCH

Public artifacts and validated results are different.

The recorded fact is the public work and its artifacts. Author-reported outcomes do not establish independent reproduction. Next checks include usable code, task conditions and third-party validation.

Evidence & related material

Background · Historical record, not rechecked

Gensyn releases OPEN-1B, a 1.61B-parameter model trained on 400B tokens with a state hash for every optimizer step. Its fixed-order kernels, data stream and topology-independent reductions reproduce the same bits across CPU, CUDA and Metal. The release includes the full corpus, 810 checkpoints, training code and an audit-replay harness. A volunteer can verify one step on commodity hardware instead of rerunning the full training job.

Technical details & scores
Model 1.61B parameters; 1.08B non-embedding parameters
Training 400,004,481,024 tokens; 80,957 optimizer steps; 48 H100 GPUs
Audit bitwise replay on CPU, CUDA or Metal with chained BLAKE2b state hashes
Artifacts full corpus, 810 checkpoints, code, audit kits and browser audit app
License Apache-2.0 code repository
Limitation 1B-scale demonstration; replay trusts pinned compiled kernels and artifacts
Technical impact 4
Engineering value 4
Adoption signal 2
Maturity 2
Verification cost 3
Risk 2