DeepSeekDeepSeek V4 ProVSOpenAIGPT-5.4
Our Take
We recommend GPT-5.4 if you need peak intelligence for reasoning and coding tasks, or the 2.6x cheaper DeepSeek V4 Pro to optimize your budget for high-volume pipelines. While GPT-5.4 holds a clear performance lead, it carries a heavy price premium. Choose GPT-5.4 for complex logic, or DeepSeek V4 Pro for budget efficiency.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. GPT-5.4 scored 57.7%, while DeepSeek V4 Pro scored 52.1%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. GPT-5.4 scored 92.8%, while DeepSeek V4 Pro scored 88%.
Cost Efficiency: DeepSeek V4 Pro pricing ($1.74/M input, $3.48/M output) is 2.6x cheaper than GPT-5.4 ($2.5/M input, $15/M output).
Was this recommendation helpful?
Benchmarks & Scores
Coding (swe-bench-pro)
52.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
88%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.6x cheaper
$2.17Input: $1.74 | Output: $3.48Context Window
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+5.6%)
57.7%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+4.8%)
92.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$5.63Input: $2.50 | Output: $15.00Context WindowLarger
1.05M tokensFrequently Asked Questions about DeepSeek V4 Pro vs GPT-5.4
DeepSeek V4 Pro is cheaper than GPT-5.4. DeepSeek V4 Pro has a blended cost of $2.17/1M tokens, which is about 2.6x cheaper than GPT-5.4 at $5.63/1M tokens.
GPT-5.4 is better for coding tasks on this benchmark. It scores 57.7% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to DeepSeek V4 Pro which scores 52.1%.
Related Matchups
Explore similar comparisons for DeepSeek V4 Pro and GPT-5.4.
Do you want to find a model for your constraints?
Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.