OpenAI gpt-oss-120b vs Kimi K2.6
Compare OpenAI gpt-oss-120b and Kimi K2.6 on the metrics that decide an agent workload.
| Metric | OpenAI gpt-oss-120b | Kimi K2.6 |
|---|---|---|
| Provider | Fireworks AI | Fireworks AI |
| Input / 1M | $0.15 | $0.95 |
| Output / 1M | $0.60 | $4.00 |
| Cache read / 1M | $0.01 (−90%) | $0.16 (−83%) |
| Reuse-adj @55% | $0.21 | $1.39 |
| Context | 131K | 262K |
| Cache capture | 79% | 81% |
| Warm TTFT | 120ms (−64%) | 140ms (−63%) |
| Quality index | 79 | 85 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
Pick OpenAI gpt-oss-120b when it is cheaper once prefix reuse is priced in, it answers faster on warm cache hits.
Pick Kimi K2.6 when it scores higher on the composite quality index, it carries the larger 262K context window, it captures more of the available reuse.
Kimi K2.6 leads on quality while OpenAI gpt-oss-120b leads on reuse-adjusted cost. Send latency- and budget-sensitive volume to OpenAI gpt-oss-120b and reserve Kimi K2.6 for the hard requests. Zumik's aliases route between them automatically under policy.
OpenAI gpt-oss-120b vs Kimi K2.6, answered.
Is OpenAI gpt-oss-120b or Kimi K2.6 cheaper?
At 55% prefix reuse, OpenAI gpt-oss-120b blends to about $0.21 per 1M tokens and Kimi K2.6 to about $1.39. OpenAI gpt-oss-120b is cheaper on that basis.
Which has the larger context window?
Kimi K2.6 has the larger window: 262K vs 131K tokens.
Which captures more reuse?
Kimi K2.6 shows higher measured cache capture (81% 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.