Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Qwen2.5-VL-32B has the cleaner overall profile here, landing at 41 versus 39. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen2.5-VL-32B gives you the larger context window at 32K, compared with 16K for Phi-4.
Pick Qwen2.5-VL-32B if you want the stronger benchmark profile. Phi-4 only becomes the better choice if coding is the priority.
Qwen2.5-VL-32B
36.3
Phi-4
70.5
Qwen2.5-VL-32B
21
Phi-4
82.6
Qwen2.5-VL-32B
63
Phi-4
80.6
Qwen2.5-VL-32B is ahead overall, 41 to 39. The biggest single separator in this matchup is HumanEval, where the scores are 35 and 82.6.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 70.5 versus 36.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Phi-4 has the edge for coding in this comparison, averaging 82.6 versus 21. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Phi-4 has the edge for multilingual tasks in this comparison, averaging 80.6 versus 63. 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.