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DeepSeek V4 Flash Base vs GPT-5.4 mini

Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.

DeepSeek V4 Flash Base

31

VS

GPT-5.4 mini

72

0 categoriesvs1 categories

Pick GPT-5.4 mini if you want the stronger benchmark profile. DeepSeek V4 Flash Base only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.

Category Radar

Head-to-Head by Category

Category Breakdown

Knowledge

GPT-5.4 mini
52.2vs57.4

+5.2 difference

Operational Comparison

DeepSeek V4 Flash Base

GPT-5.4 mini

Price (per 1M tokens)

$null / $null

$0.75 / $4.5

Speed

N/A

201 t/s

Latency (TTFT)

N/A

3.85s

Context Window

1M

400K

Quick Verdict

Pick GPT-5.4 mini if you want the stronger benchmark profile. DeepSeek V4 Flash Base only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.

GPT-5.4 mini is clearly ahead on the provisional aggregate, 72 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.4 mini's sharpest advantage is in knowledge, where it averages 57.4 against 52.2.

GPT-5.4 mini is the reasoning model in the pair, while DeepSeek V4 Flash Base 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. DeepSeek V4 Flash Base gives you the larger context window at 1M, compared with 400K for GPT-5.4 mini.

Benchmark Deep Dive

Frequently Asked Questions (2)

Which is better, DeepSeek V4 Flash Base or GPT-5.4 mini?

GPT-5.4 mini is ahead on BenchLM's provisional leaderboard, 72 to 31.

Which is better for knowledge tasks, DeepSeek V4 Flash Base or GPT-5.4 mini?

GPT-5.4 mini has the edge for knowledge tasks in this comparison, averaging 57.4 versus 52.2. DeepSeek V4 Flash Base stays close enough that the answer can still flip depending on your workload.

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Last updated: April 24, 2026

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