Benchmarking Sub-Billion-Parameter Models on Commodity Hardware
A poster summarising latency, memory and quality for twenty sub-billion-parameter models on a laptop CPU, a single-board computer and a mobile phone.
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A poster summarising latency, memory and quality for twenty sub-billion-parameter models on a laptop CPU, a single-board computer and a mobile phone.
Agents that retry failed tool calls recover from transient errors but can also compound mistakes and waste resources. We analyse 18,000 recorded agent runs and show that retries help for network and rate-limit errors but hurt for malformed arguments. We propose a retry budget that depends on the error class and show that it improves success by 6 points at equal cost.
Some tool failures return plausible but wrong output and raise no error. We detect such silent failures by comparing the distribution of tool outputs against a rolling reference and flagging shifts. On three deployed tools the detector finds 71% of injected faults with a 2% false-alarm rate.
We report experience building perturbation suites — rephrased instructions, reordered tool lists, noisy outputs — for three deployed agents, and summarise which perturbations revealed real failures and which only added cost.