DeepSeek-V4-Pro vs OpenAI gpt-oss-120b
Open-weights reasoning for cost-sensitive and regulated lanes.
| Metric | DeepSeek-V4-Pro | OpenAI gpt-oss-120b |
|---|---|---|
| Provider | Fireworks AI | Fireworks AI |
| Input / 1M | $1.74 | $0.15 |
| Output / 1M | $3.48 | $0.60 |
| Cache read / 1M | $0.14 (−92%) | $0.01 (−90%) |
| Reuse-adj @55% | $1.52 | $0.21 |
| Context | 1M | 131K |
| Cache capture | 80% | 79% |
| Warm TTFT | 130ms (−63%) | 120ms (−64%) |
| Quality index | 88 | 79 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
You want the stronger reasoning quality and higher measured capture of DeepSeek V4 Pro.
You need an OpenAI-lineage open model for on-prem or regulated deployments with BYOC purge evidence.
DeepSeek V4 Pro is the better generalist; GPT-OSS 120B is the safer pick when provenance and on-prem constraints lead.
DeepSeek-V4-Pro vs OpenAI gpt-oss-120b, answered.
Is DeepSeek-V4-Pro or OpenAI gpt-oss-120b cheaper?
At 55% prefix reuse, DeepSeek-V4-Pro blends to about $1.52 per 1M tokens and OpenAI gpt-oss-120b to about $0.21. OpenAI gpt-oss-120b is cheaper on that basis.
Which has the larger context window?
DeepSeek-V4-Pro has the larger window: 1M vs 131K tokens.
Which captures more reuse?
DeepSeek-V4-Pro shows higher measured cache capture (80% vs 79%) 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.