Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
35
Gemini 3.5 Flash
88
Verified leaderboard positions: DeepSeek V3 unranked · Gemini 3.5 Flash #7
Pick Gemini 3.5 Flash if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+15.3 difference
Knowledge
+12.0 difference
Inst. Following
+9.8 difference
DeepSeek V3
Gemini 3.5 Flash
$0.27 / $1.1
$1.5 / $9
N/A
284.2 t/s
N/A
18.55s
128K
1M
Pick Gemini 3.5 Flash if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Gemini 3.5 Flash is clearly ahead on the provisional aggregate, 88 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.5 Flash's sharpest advantage is in coding, where it averages 54.5 against 39.2. The single biggest benchmark swing on the page is GPQA, 59.1% to 92.2%. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemini 3.5 Flash is also the more expensive model on tokens at $1.50 input / $9.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 8.2x on output cost alone. Gemini 3.5 Flash is the reasoning model in the pair, while DeepSeek V3 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. Gemini 3.5 Flash gives you the larger context window at 1M, compared with 128K for DeepSeek V3.
Gemini 3.5 Flash is ahead on BenchLM's provisional leaderboard, 88 to 35. The biggest single separator in this matchup is GPQA, where the scores are 59.1% and 92.2%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 70 versus 58. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 3.5 Flash has the edge for coding in this comparison, averaging 54.5 versus 39.2. DeepSeek V3 stays close enough that the answer can still flip depending on your workload.
DeepSeek V3 has the edge for instruction following in this comparison, averaging 86.1 versus 76.3. Gemini 3.5 Flash stays close enough that the answer can still flip depending on your workload.
Estimates at 50,000 req/day · 1000 tokens/req average.
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