Qwen3.5-35B-A3B outpaces Claude Opus in local bug hunting

This comparison highlights a significant shift where high-efficiency, open-weights models are challenging proprietary frontier models by leveraging brute-force context stuffing on local hardware.

• –The hybrid Gated DeltaNet + Sparse MoE architecture (3B active parameters) allows for flagship-level performance on consumer GPUs.
• –Massive 256k native context windows enable developers to load entire codebase modules, bypassing the need for fragmented RAG or multi-turn searching.
• –Proprietary models like Claude 4.7 Opus, while theoretically more intelligent, are often limited by conservative context management and API latency.
• –High-speed local inference (180 tps) drastically reduces the friction of iterative debugging and plan generation compared to slower frontier APIs.
• –The success of Qwen 3.5-35B underscores the growing viability of "medium-tier" models for complex, agentic developer workflows.