GLM-4.5 vs Qwen3-Next 80B-A3B (Thinking)

Both GLM-4.5 and Qwen3-Next 80B-A3B (Thinking) are open-weights foundation models available at $0.00 direct API cost when self-hosted, or offered at identical baseline rates across major inference providers. Model selection depends on GPU deployment sizing and specialized benchmark performance rather than raw token price.

Both GLM-4.5 and Qwen3-Next 80B-A3B (Thinking) offer an identical context window of 131K tokens (~98k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

GLM-4.5 scores 42% on SWE-bench Verified while Qwen3-Next 80B-A3B (Thinking) scores 46%. For autonomous software engineering and multi-file debugging, Qwen3-Next 80B-A3B (Thinking) holds the verified benchmark lead.

GLM-4.5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Qwen3-Next 80B-A3B (Thinking) provides chain-of-thought reasoning depth for complex math and science.

GLM-4.5 generates approximately 75 tokens per second, while Qwen3-Next 80B-A3B (Thinking) delivers 95 tokens per second. In latency-sensitive production environments, Qwen3-Next 80B-A3B (Thinking) provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Yes! Tiered multi-model routing can optimize for latency and accuracy: you can route high-frequency conversational turns and latency-sensitive queries to Qwen3-Next 80B-A3B (Thinking), and route deep architectural or complex reasoning queries to GLM-4.5. This balanced routing strategy maximizes system throughput and answer quality.