Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GLM-4.7-Flash is clearly ahead on the aggregate, 64 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.7-Flash is the reasoning model in the pair, while DBRX Instruct is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GLM-4.7-Flash gives you the larger context window at 200K, compared with 32K for DBRX Instruct.
Pick GLM-4.7-Flash if you want the stronger benchmark profile. DBRX Instruct only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
GLM-4.7-Flash
57.3
DBRX Instruct
73.7
GLM-4.7-Flash
47.7
DBRX Instruct
70.1
GLM-4.7-Flash is ahead overall, 64 to 32. The biggest single separator in this matchup is HumanEval, where the scores are 58 and 70.1.
DBRX Instruct has the edge for knowledge tasks in this comparison, averaging 73.7 versus 57.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DBRX Instruct has the edge for coding in this comparison, averaging 70.1 versus 47.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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