Scope

• Model tested: qwen/qwen3.6-flash
• Total tests: 459
• Categories covered: 9 — coding, cost, debugging, hallucination, reasoning, refactoring, security, speed, ui
• Run mode: Full benchmark (no --limit or --fail-fast triggered early termination)
• Results completeness: results_truncated: true — some detailed outputs may be omitted, but aggregate metrics are complete.

Performance Summary

• Overall pass rate: 210/459 (45.75%)
• Score achieved: 2173.62 out of 3137 (69.29%)
• Total cost: $0.432
• Latency:
  • Avg TTFT (Time to First Token): 0.665s
  • Avg latency per test: 3.595s
  • Median latency: 1.951s
• Output speed: 203.97 tok/s (average)

Category-Level Performance

High-Performing Categories

• Speed: 52/60 passed (86.67%), 92.22% score — fastest and most accurate.
• Cost: 29/30 passed (96.67%), 90% score — excellent on cost-aware tasks.
• Coding: 49/60 passed (81.67%), 90.04% score — strong on algorithmic tasks, especially at easy level (100% score).
• UI: 5/9 passed (55.56%), but 62.45% score — limited data, but moderate success.

Low-Performing Categories

• Refactoring: 6/60 passed (10%), 58.96% score — weakest category; struggles across all difficulty levels.
• Reasoning: 11/60 passed (18.33%), 70.43% score — poor pass rate despite moderate scoring; fails complex constraint reasoning.
• Security: 10/60 passed (16.67%), 52.34% score — low pass rate, especially on easy (2/20) and hard (2/20) tasks.
• Debugging: 19/60 passed (31.67%), 68.95% score — inconsistent; fails many subtle bugs, especially in concurrency and state management.

Hallucination

• Pass rate: 29/60 (48.33%), 72.78% score.
• Mixed results: passes some hard API behavior questions (e.g., fetch-timeout, weakref-gc) but fails basic ones (e.g., array-flat, json-parse-date).
• Struggles with edge cases and documentation accuracy (e.g., tc39-pipeline, validation-pipe).

Notable Observations

• Cost efficiency: Extremely low total cost ($0.43) for 459 tests, with 318,64 prompt and 285,906 completion tokens — indicates efficient token usage.
• Latency profile: Fast TTFT (0.66s avg), but long tail in latency (median 1.95s, mean 3.59s) — some complex tasks take significantly longer.
• Difficulty trends:
  • Easy: High pass rates in coding, cost, speed.
  • Hard: Sharp drop in refactoring (1/20), security (2/20), and debugging (5/20).
• Failures in reasoning: Despite high max score potential, reasoning had only 11 passes — often generates plausible but incorrect logic under constraints.
• Critical errors: Two debugging tests failed with "Spread syntax requires ...iterable[Symbol.iterator] to be a function" — suggests model-generated code with runtime errors.

Conclusion

The qwen/qwen3.6-flash model delivers strong performance in coding, cost optimization, and speed, with fast response times and low cost. However, it struggles significantly with refactoring, security, and complex reasoning, and shows inconsistent behavior in debugging and hallucination avoidance. It is suitable for lightweight, performance-sensitive tasks but may require validation for correctness in complex or safety-critical domains.