DeepSeek V4 Pro vs GPT-5.4

Choose DeepSeek V4 Pro if you want…

• ✓Lower price ($2.17 / 1M blended)

Choose GPT-5.4 if you want…

• ✓Higher intelligence (Artificial Analysis index 57)
• ✓Faster output (~163.4 tokens/sec)
• ✓Larger context window (1.1M)

DeepSeek V4 Pro

DeepSeek V4 Pro makes a compelling case that frontier-class coding performance and a one-million-token context window do not have to cost frontier-class money. At roughly $0.18 per million tokens blended, it runs 10x cheaper on input and 30x cheaper on output than comparable models, while posting an 80.6% score on SWE-Bench Verified — the highest reported among open-weight models at launch. Users consistently praise its agentic coding ability, noting it competes with or beats larger closed models on multi-step coding tasks, and its hybrid attention architecture handles full-codebase analysis without collapsing under the token budget. The MIT license is a genuine differentiator: weights are freely available for self-hosting, fine-tuning, and commercial integration. The honest caveat: V4 Pro is verbose. It can generate four to five times more output tokens than comparable models on the same prompt, which erodes the per-token savings and makes cost estimation harder than it first appears. Still in preview as of mid-2026, with all benchmark scores currently vendor-reported, it is best suited for teams comfortable with that tradeoff.

GPT-5.4

GPT-5.4 was built for the actual work that happens inside offices — financial modeling, legal analysis, complex codebases, and multi-step document workflows — rather than for chasing narrow benchmarks. That strategic shift shows in the numbers: it matched or outperformed human professionals in 83% of head-to-head comparisons, and developers have called its coding output "flawless," with some declaring it the definitive choice for complex software engineering work. Native computer-use capabilities let it operate browsers and desktop apps directly, and it scored above the human baseline on UI interaction tasks. The 1.05 million token context window handles large codebases and lengthy legal documents in a single pass, though you need to configure it explicitly — the default is 272K. Where GPT-5.4 falls short is nuance: it tends to interpret requests too literally, missing the intent behind ambiguous prompts in ways that Claude handles more naturally. Writing personality is another common frustration, with verbose follow-up suggestions that can feel mechanical. For structured professional tasks where thoroughness and tool integration matter more than prose feel, it is the strongest model in the GPT-5 line prior to the release of GPT-5.5.