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Omar (kouhxp): gutsy and solvi: solvi, compared on what they decide, where they run, what they cost and what their publishers report.
| Property | kouhxp/gutsy | solvi-ai/solvi |
|---|---|---|
| Summary | Omar (kouhxp)'s CPU decision model: a Qwen3.5-0.8B fine-tune shipped as GGUF for llama.cpp that answers yes/no, choice and score questions with a probability per option plus a 'none of these' reject probability, served by a local Jev-style HTTP runtime. | A 396M ModernBERT-large cross-encoder that answers typed questions about a text or a JSON state: one or several options, scores, yes/no with "not stated", spans with evidence quotes, rankings and numeric bins, each with a confidence and an act-or-escalate signal. |
| Decides | choice, score, noul, classify, route | choice, score, noul, rank, extract |
| Architecture | gutsy | solvi |
| Fine-tuned from | qwen/qwen3.5-0.8b | answerdotai/modernbert-large |
| License | apache-2.0 | apache-2.0 |
| Availability | Open weights | Open weights |
| Hosted by | — | — |
| Input price | — | — |
| Decision accuracy | 73.2% | 59.4% |
| Calibration error | — | 0.210 |
| Valid action rate | — | — |
| Median latency | — | — |
| p95 latency | — | — |
| Evaluation suite | JevBench public set (231 items; 169 correct), the maker's own run with Q8_0 | Fast Decisions public dev split (100 rows x 17 domains, macro), the maker's own harness, zero-shot |
| Latest version | 0.4.0 | 2026.09 |
| Variants | LICENSE, gutsy-inference | onnx |
| Size of latest version | 1.2 GB | 2.2 GB |
| Files | 24 | 11 |
| Downloads | 0 | 0 |
| Stars | 0 | 0 |
| Tags | system-one, qwen, gguf, llama-cpp, cpu, 0.8b | system-one, modernbert, cross-encoder, onnx, evidence, escalation, 396m |
| Updated | Oct 7, 2026 | Oct 7, 2026 |
Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
gutsy is from Omar (kouhxp) and solvi from solvi. Both have open weights you can download and run. Both answer choice, score and noul questions. Only gutsy answers classify and route. Only solvi answers rank and extract. gutsy reads up to 8K tokens of state, against 512 tokens for solvi. solvi is the smaller model, at 396M parameters to 800M.
They report on different suites — gutsy 73.2% on JevBench public set (231 items; 169 correct), the maker's own run with Q8_0, solvi 59.4% on Fast Decisions public dev split (100 rows x 17 domains, macro), the maker's own harness, zero-shot — so the numbers do not rank them. Test both on your own labelled examples.
gutsy: Free (open weights). solvi: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Yes, both: systemone pull kouhxp/gutsy and systemone pull solvi-ai/solvi download the weights.