Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mercury 2 is clearly ahead on the aggregate, 65 to 37. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mercury 2's sharpest advantage is in reasoning, where it averages 80.1 against 36.4. The single biggest benchmark swing on the page is LongBench v2, 77 to 36. DBRX Instruct does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Mercury 2 is also the more expensive model on tokens at $0.25 input / $0.75 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DBRX Instruct. That is roughly Infinityx on output cost alone. Mercury 2 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. Mercury 2 gives you the larger context window at 128K, compared with 32K for DBRX Instruct.
Pick Mercury 2 if you want the stronger benchmark profile. DBRX Instruct only becomes the better choice if coding is the priority or you want the cheaper token bill.
Mercury 2
63.7
DBRX Instruct
34.3
Mercury 2
41.1
DBRX Instruct
48
Mercury 2
68.3
DBRX Instruct
35.6
Mercury 2
80.1
DBRX Instruct
36.4
Mercury 2
57.2
DBRX Instruct
52
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Mercury 2
79.7
DBRX Instruct
46
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Mercury 2 is ahead overall, 65 to 37. The biggest single separator in this matchup is LongBench v2, where the scores are 77 and 36.
Mercury 2 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 52. Inside this category, FrontierScience is the benchmark that creates the most daylight between them.
DBRX Instruct has the edge for coding in this comparison, averaging 48 versus 41.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for reasoning in this comparison, averaging 80.1 versus 36.4. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for agentic tasks in this comparison, averaging 63.7 versus 34.3. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for multimodal and grounded tasks in this comparison, averaging 68.3 versus 35.6. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for multilingual tasks in this comparison, averaging 79.7 versus 46. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.