Databricks makes Chinese open-source model GLM 5.2 its default coding engine after it matched Opus at lower cost
$1.28 per task. That's what Databricks paid GLM 5.2 to match Anthropic's Opus—and they're making it their default coding engine.
Why it matters
Databricks' internal benchmark reveals open-source models can match frontier commercial models on real-world coding tasks at significantly lower cost, signaling a shift toward pragmatic model selection over brand loyalty. The decision to default to GLM 5.2 demonstrates that companies are moving beyond public benchmarks to build proprietary eval frameworks.
The key facts
6 to knowGLM 5.2 matched Anthropic's Opus 4.8 on Databricks' internal coding benchmark
Cost differential: $1.28 per task (GLM 5.2) vs $1.94 per task (Opus 4.8)
Benchmark conducted on Databricks' multi-million-line internal codebase
GLM 5.2 is a Chinese open-source model
Databricks rolling out GLM 5.2 as daily coding workhorse
Key strategic insight: no single provider dominates; internal benchmarks outweigh public ones
Go to the source
The Decoderthe-decoder.com
Publisher excerpt: Databricks benchmarked coding agents on its own multi-million-line codebase and found that the Chinese open-source model GLM 5.2 matched Anthropic's Opus 4.8 at $1.28 per task versus $1.94. The company plans to roll it out as a daily coding workhorse. Its broader takeaway: no single provider…