Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-4.7 is clearly ahead on the aggregate, 69 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Composer 2 is also the more expensive model on tokens at $0.50 input / $2.50 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone.
Pick GLM-4.7 if you want the stronger benchmark profile. Composer 2 only becomes the better choice if agentic is the priority.
Composer 2
61.7
GLM-4.7
50.8
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GLM-4.7 is ahead overall, 69 to 62. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 61.7% and 41%.
Composer 2 has the edge for agentic tasks in this comparison, averaging 61.7 versus 50.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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