Head-to-head
GPT-5.5 Pro vs Kimi K2.6
Compare GPT-5.5 Pro and Kimi K2.6 on the metrics that decide an agent workload.
| Metric | GPT-5.5 Pro | Kimi K2.6 |
|---|---|---|
| Provider | OpenAI | Fireworks AI |
| Input / 1M | $30.00 | $0.95 |
| Output / 1M | $180.00 | $4.00 |
| Cache read / 1M | $30.00 (−0%) | $0.16 (−83%) |
| Reuse-adj @55% | $67.50 | $1.39 |
| Context | 1.1M | 262K |
| Cache capture | 80% | 82% |
| Warm TTFT | 900ms (−53%) | 140ms (−63%) |
| Quality index | 86 | 87 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
Pick GPT-5.5 Pro when it carries the larger 1.1M context window.
Pick Kimi K2.6 when it scores higher on the composite quality index, it is cheaper once prefix reuse is priced in, it answers faster on warm cache hits.
Kimi K2.6 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
GPT-5.5 Pro vs Kimi K2.6, answered.
Is GPT-5.5 Pro or Kimi K2.6 cheaper?
At 55% prefix reuse, GPT-5.5 Pro blends to about $67.50 per 1M tokens and Kimi K2.6 to about $1.39. Kimi K2.6 is cheaper on that basis.
Which has the larger context window?
GPT-5.5 Pro has the larger window: 1.1M vs 262K tokens.
Which captures more reuse?
Kimi K2.6 shows higher measured cache capture (82% 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.