Local Code Arena MBPP Qwen3.5 9B: LLM Performance Telemetry

ShahzebKhoso's repository hosts raw evaluation metrics and execution telemetry logs from running the Mostly Basic Python Problems (MBPP) benchmark against the Qwen 3.5 9B model. The data captures mid-tier performance and throughput dynamics of this generalist instruction model on local consumer hardware. The dataset was last updated on May 24, 2026.

Use Cases

• Benchmarking code generation model performance based on MBPP evaluation metrics.
• Analyzing execution throughput and dynamics of instruction-tuned LLMs.
• Comparing local hardware performance for foundation model inference tasks.

Strengths

• Includes raw evaluation metrics and execution telemetry logs.
• Captures performance data for a specific model architecture (Qwen 3.5 9B).
• Focuses on a standardized benchmark (Mostly Basic Python Problems).

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

Hugging Face dataset by ShahzebKhoso.

Collection Method

Telemetry logs from running the MBPP benchmark on the Qwen 3.5 9B model.

Freshness

Last updated 2026-05-24 09:07:59; freshness should be verified.