SRA-RiskGate-4B (GGUF)

GGUF builds of SRA-RiskGate-4B, a 4B model that checks a stablecoin payment before an AI agent sends it and answers approve, hold or reject. For llama.cpp, LM Studio, Ollama and similar.

📄 Paper: preprint on Zenodo · full write-up on Ready Tensor · discuss on alphaXiv

🔁 Verified in the open (November 2026). The companion sra-riskgate library's checks, in front of real agents:

• Base Sepolia, independently re-checked: an approved 0.01 USDC payment (tx) was read back from the chain and verified, and a 2.00 USDC payment to an unknown payee was held before signing. Flow Executor, an independent agent settlement verifier, re-checked both from the chain (log · Flow Executor's page).
• Circle Gateway on Arc testnet: one agent task, three proposed payments. One was approved, accepted by Gateway and settled to the payee (agent 0.09 → 0.08 USDC, payee 0.01 → 0.02); an unlimited approval was held and a look-alike payee rejected, neither signed (log).
• Grok as the paying agent: Grok (grok-4.7) refused both attacks on its own; told to submit everything to the gate, it got APPROVE for the real invoice, HOLD for the unlimited approval and REJECT for the look-alike (logs).

These runs used the library's deterministic checks, not this model.

The benchmark results on the main model card were measured on the full-precision model. These quantized builds have not been benchmarked separately. Dispute adjudication is the most likely to degrade, so prefer Q8_0 or the full model for disputes.

Run it

Ollama (payment risk-gate system prompt, temperature 0 and an 8K context built in):

ollama run sriram1983007/sra-riskgate

llama.cpp:

llama-server -hf sriram1983007/SRA-RiskGate-4B-GGUF:Q4_K_M -c 8192 --temp 0

LM Studio: search for SRA-RiskGate-4B-GGUF, pick a file, and set temperature to 0.

Use the exact training prompt format from the main model card: the system prompt, then Evaluate this stablecoin payment. with the <context>, <payload> and <tool_results> blocks. Treat any answer that isn't a valid verdict as a hold.

More quantization sizes, including imatrix builds, are available from mradermacher: static and imatrix, and from tinyopsec: SRA-RiskGate-4B-GGUF (Q2_K to F16; builds below Q4 have not been evaluated).

📄 Citation

@misc{ramakrishnan2026srariskgate,
  author    = {Sriram Ramakrishnan},
  title     = {SRA-RiskGate: A Benchmark and a 4B Model for Gating Stablecoin Payments Made by AI Agents, and the Checks the Model Still Needs},
  year      = {2026},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.23715017},
  url       = {https://doi.org/10.5281/zenodo.23715017}
}

Full write-up: Ready Tensor.

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License

Apache 2.0