Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
62
Qwen3.5-122B-A10B
61
Verified leaderboard positions: Gemma 4 31B unranked · Qwen3.5-122B-A10B #26
Pick Gemma 4 31B if you want the stronger benchmark profile. Qwen3.5-122B-A10B only becomes the better choice if coding is the priority or you need the larger 262K context window.
Coding
+30.4 difference
Knowledge
+20.3 difference
Multimodal
+0.3 difference
Gemma 4 31B
Qwen3.5-122B-A10B
$0 / $0
$0 / $0
N/A
N/A
N/A
N/A
256K
262K
Pick Gemma 4 31B if you want the stronger benchmark profile. Qwen3.5-122B-A10B only becomes the better choice if coding is the priority or you need the larger 262K context window.
Gemma 4 31B finishes one point ahead on BenchLM's provisional leaderboard, 62 to 61. 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.
Qwen3.5-122B-A10B gives you the larger context window at 262K, compared with 256K for Gemma 4 31B.
Gemma 4 31B is ahead on BenchLM's provisional leaderboard, 62 to 61. The biggest single separator in this matchup is GPQA, where the scores are 84.3% and 86.6%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 61.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 72 versus 41.6. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 77.2 versus 76.9. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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