Head-to-head

DeepSeek-V4-Pro vs GPT-5.5 Pro

Compare DeepSeek-V4-Pro and GPT-5.5 Pro on the metrics that decide an agent workload.

MetricDeepSeek-V4-ProGPT-5.5 Pro
ProviderFireworks AIOpenAI
Input / 1M$1.74$30.00
Output / 1M$3.48$180.00
Cache read / 1M$0.14 (−92%)$30.00 (−0%)
Reuse-adj @55%$1.52$67.50
Context1M1.1M
Cache capture81%80%
Warm TTFT130ms (−63%)900ms (−53%)
Quality index8686

Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.

Pick DeepSeek-V4-Pro when

Pick DeepSeek-V4-Pro when it is cheaper once prefix reuse is priced in, it answers faster on warm cache hits, it captures more of the available reuse.

Pick GPT-5.5 Pro when

Pick GPT-5.5 Pro when it carries the larger 1.1M context window.

Verdict

DeepSeek-V4-Pro wins on both reuse-adjusted cost and quality here, so it is the default pick. Reach for GPT-5.5 Pro only when a specific constraint (modality, latency floor, or licensing) forces it.

Frequently asked

DeepSeek-V4-Pro vs GPT-5.5 Pro, answered.

Is DeepSeek-V4-Pro or GPT-5.5 Pro cheaper?

At 55% prefix reuse, DeepSeek-V4-Pro blends to about $1.52 per 1M tokens and GPT-5.5 Pro to about $67.50. DeepSeek-V4-Pro is cheaper on that basis.

Which has the larger context window?

GPT-5.5 Pro has the larger window: 1.1M vs 1M tokens.

Which captures more reuse?

DeepSeek-V4-Pro shows higher measured cache capture (81% vs 80%) in the Zumik corpus.

Let an alias pick for you.

Route to whichever model wins under current policy automatically. Zumik resolves the alias to the best fit per request, so you never hard-code a loser.