DeepSeek-V4-Pro vs GPT-5.5
Compare DeepSeek-V4-Pro and GPT-5.5 on the metrics that decide an agent workload.
| Metric | DeepSeek-V4-Pro | GPT-5.5 |
|---|---|---|
| Provider | Fireworks AI | OpenAI |
| Input / 1M | $1.74 | $5.00 |
| Output / 1M | $3.48 | $30.00 |
| Cache read / 1M | $0.14 (−92%) | $0.50 (−90%) |
| Reuse-adj @55% | $1.52 | $9.39 |
| Context | 1M | 1.1M |
| Cache capture | 80% | 88% |
| Warm TTFT | 130ms (−63%) | 240ms (−67%) |
| Quality index | 88 | 96 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
Pick DeepSeek-V4-Pro when it is cheaper once prefix reuse is priced in, it answers faster on warm cache hits, it is open-weights for on-prem and regulated lanes.
Pick GPT-5.5 when it scores higher on the composite quality index, it carries the larger 1.1M context window, it captures more of the available reuse.
GPT-5.5 leads on quality while DeepSeek-V4-Pro leads on reuse-adjusted cost. Send latency- and budget-sensitive volume to DeepSeek-V4-Pro and reserve GPT-5.5 for the hard requests. Zumik's aliases route between them automatically under policy.
DeepSeek-V4-Pro vs GPT-5.5, answered.
Is DeepSeek-V4-Pro or GPT-5.5 cheaper?
At 55% prefix reuse, DeepSeek-V4-Pro blends to about $1.52 per 1M tokens and GPT-5.5 to about $9.39. DeepSeek-V4-Pro is cheaper on that basis.
Which has the larger context window?
GPT-5.5 has the larger window: 1.1M vs 1M tokens.
Which captures more reuse?
GPT-5.5 shows higher measured cache capture (88% 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.