DeepSeek-V4-Pro vs GPT-5 Mini
Compare DeepSeek-V4-Pro and GPT-5 Mini on the metrics that decide an agent workload.
| Metric | DeepSeek-V4-Pro | GPT-5 Mini |
|---|---|---|
| Provider | Fireworks AI | OpenAI |
| Input / 1M | $1.74 | $0.25 |
| Output / 1M | $3.48 | $2.00 |
| Cache read / 1M | $0.14 (−92%) | $0.03 (−90%) |
| Reuse-adj @55% | $1.52 | $0.59 |
| Context | 1M | 400K |
| Cache capture | 80% | 85% |
| Warm TTFT | 130ms (−63%) | 150ms (−63%) |
| Quality index | 88 | 82 |
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 scores higher on the composite quality index, it carries the larger 1M context window, it answers faster on warm cache hits.
Pick GPT-5 Mini when it is cheaper once prefix reuse is priced in, it captures more of the available reuse.
DeepSeek-V4-Pro leads on quality while GPT-5 Mini leads on reuse-adjusted cost. Send latency- and budget-sensitive volume to GPT-5 Mini and reserve DeepSeek-V4-Pro for the hard requests. Zumik's aliases route between them automatically under policy.
DeepSeek-V4-Pro vs GPT-5 Mini, answered.
Is DeepSeek-V4-Pro or GPT-5 Mini cheaper?
At 55% prefix reuse, DeepSeek-V4-Pro blends to about $1.52 per 1M tokens and GPT-5 Mini to about $0.59. GPT-5 Mini is cheaper on that basis.
Which has the larger context window?
DeepSeek-V4-Pro has the larger window: 1M vs 400K tokens.
Which captures more reuse?
GPT-5 Mini shows higher measured cache capture (85% 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.