Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash (High)
71
GPT-5.4 nano
61
Verified leaderboard positions: DeepSeek V4 Flash (High) #19 · GPT-5.4 nano unranked
Pick DeepSeek V4 Flash (High) if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+12.5 difference
Knowledge
+4.0 difference
DeepSeek V4 Flash (High)
GPT-5.4 nano
$0.14 / $0.28
$0.2 / $1.25
N/A
191 t/s
N/A
3.64s
1M
400K
Pick DeepSeek V4 Flash (High) if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
DeepSeek V4 Flash (High) is clearly ahead on the provisional aggregate, 71 to 61. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Flash (High)'s sharpest advantage is in agentic, where it averages 55.4 against 42.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 56.6% to 46.3%.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 4.5x on output cost alone. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 400K for GPT-5.4 nano.
DeepSeek V4 Flash (High) is ahead on BenchLM's provisional leaderboard, 71 to 61. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 56.6% and 46.3%.
DeepSeek V4 Flash (High) has the edge for knowledge tasks in this comparison, averaging 57.2 versus 53.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
DeepSeek V4 Flash (High) has the edge for agentic tasks in this comparison, averaging 55.4 versus 42.9. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
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