Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed-2.0-Mini finishes one point ahead overall, 53 to 52. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Seed-2.0-Mini's sharpest advantage is in reasoning, where it averages 64.8 against 49.4. The single biggest benchmark swing on the page is SWE-bench Pro, 29 to 65. GPT-4o mini does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Seed-2.0-Mini. Seed-2.0-Mini gives you the larger context window at 256K, compared with 128K for GPT-4o mini.
Pick Seed-2.0-Mini if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority.
Seed-2.0-Mini
46.2
GPT-4o mini
50.9
Seed-2.0-Mini
24.7
GPT-4o mini
65
Seed-2.0-Mini
73.1
GPT-4o mini
60.2
Seed-2.0-Mini
64.8
GPT-4o mini
49.4
Seed-2.0-Mini
44.6
GPT-4o mini
62
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Seed-2.0-Mini
71.8
GPT-4o mini
74.7
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Seed-2.0-Mini is ahead overall, 53 to 52. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 29 and 65.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 62 versus 44.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 65 versus 24.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Seed-2.0-Mini has the edge for reasoning in this comparison, averaging 64.8 versus 49.4. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for agentic tasks in this comparison, averaging 50.9 versus 46.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed-2.0-Mini has the edge for multimodal and grounded tasks in this comparison, averaging 73.1 versus 60.2. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 74.7 versus 71.8. Inside this category, MGSM 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.