Architecture
data/models.yaml. Every label is auditable
against the model's sources.
Specs
- Architecture
- unknown
- Total params
- not disclosed
- Active params
- not disclosed
- Context window
- 128K tokens
- Attention
- unknown
- Position encoding
- unknown
- Post-training
- sft, rlhf
- OSI-approved
- no
- Data released
- no
- Training code
- not released
Benchmarks
Each score carries the date it was published; we never infer or interpolate missing scores.
General reasoning
| MMLU-Pro | 76.0 | as of 2026-05-21 | source ↗ |
| GPQA-Diamond | 57.8 | as of 2026-05-21 | source ↗ |
Code
| LiveCodeBench | 40.0 | as of 2026-05-21 | source ↗ |
Available quantizations
None. The weights are not distributed, so there are no public quantizations.
Notable innovations
- · Hybrid, on-premises, and in-VPC deployment options
- · Coding and STEM focus
Lineage
New mid-tier slot between Mistral Small and Large; proprietary, not weights-released.