Model Details
- Base model: gpt-oss-20b
- Parameters: 20B (Mixture of Experts)
- Training: SFT + RL (CISPO) with a staged curriculum
- Precision: BF16 (MXFP4 quantized checkpoint coming soon)
Key Capabilities
- Query decomposition: Breaks complex multi-constraint
questions into targeted subqueries.
- Parallel tool calling: Averages 2.56 tool calls per
turn, reducing total turns and end-to-end latency.
- Self-editing context: Selectively prunes irrelevant
documents mid-search to sustain retrieval quality over
long horizons within a bounded context window (0.94
prune accuracy).
- Cross-domain generalization: Trained on web, legal,
and finance tasks; generalizes to held-out domains and
public benchmarks (BrowseComp-Plus, SealQA, FRAMES,
HLE).
Important: Agent Harness Required
Context-1 is trained to operate within a specific agent
harness that manages tool execution, token budgets, context
pruning, and deduplication. The harness is not yet
public. Running the model without it will not reproduce
the results reported in the technical report.
We plan to release the full agent harness and evaluation
code soon. In the meantime, the technical report describes
the harness design in detail.
Citation
@techreport{bashir2026context1,
title = {Chroma Context-1: Training a Self-Editing Search Agent},
author = {Bashir, Hammad and Hong, Kelly and Jiang, Patrick and Shi, Zhiyi},
year = {2026},
month = {March},
institution = {Chroma},
url = {https://trychroma.com/research/context-1},
}
License
Apache 2.0