Provider: Synthetic.new (via Fireworks) Context window: 159k tokens Task: Multi-step tool calling chain (weather → Bulgarian description → markdown file → email with attachment)
| Criteria | Score | Max |
|---|---|---|
| Correct tool call sequence | 0 | 3 |
| Tool call accuracy | 0 | 3 |
| Final output quality | 0 | 2 |
| Efficiency & communication | 0 | 2 |
- Time: N/A (never completed)
- Cost: Fixed subscription ($20–60/mo on Synthetic.new)
- User interventions: 3 (all ignored/unanswered)
The model hung after partially completing step 1:
- User sent the prompt → (no output)
- User: "ау?" → Model: "Получаю данные о погоде... (Шаг 1)"
- User: "и?" → Model: "Шаг 1: Получил данные о погоде. Шаг 2: Составляю описание на болгарском. Сначала получю текущую дату."
- User: "и?" → (no output)
- User: "где результат?" → (no output)
Task was abandoned.
- Silent hang — The model stopped producing output without any error message or explanation.
- No error reporting — Worse than crashing: the user has no idea what happened or how to fix it.
- Partial progress messages — Teased that it was working ("Получаю данные...") but never delivered.
- Three user pings ignored — No response to repeated attempts to get status.
- Timeout on the Fireworks inference endpoint
- Tool call error that wasn't surfaced to the user
- Context or token limit issue during generation
Regardless of the root cause, the user-facing result is the same: nothing.
Complete failure. A silently hanging agent is arguably worse than one that crashes with an error — at least an error gives the user something to act on. For agentic use cases where reliability is paramount, this is disqualifying. The model may perform well in benchmarks, but in this real-world tool-calling scenario via Synthetic.new/Fireworks, it was non-functional.