GPT-5 Mini vs Kimi K2.6

Compare GPT-5 Mini and Kimi K2.6 on the metrics that decide an agent workload.

MetricGPT-5 MiniKimi K2.6
ProviderOpenAIFireworks AI
Input / 1M$0.25$0.95
Output / 1M$2.00$4.00
Cache read / 1M$0.03 (−90%)$0.16 (−83%)
Reuse-adj @55%$0.59$1.39
Context400K262K
Cache capture85%81%
Warm TTFT150ms (−63%)140ms (−63%)
Quality index8285

Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.

Pick GPT-5 Mini when

Pick GPT-5 Mini when it is cheaper once prefix reuse is priced in, it carries the larger 400K context window, it captures more of the available reuse.

Pick Kimi K2.6 when

Pick Kimi K2.6 when it scores higher on the composite quality index, it answers faster on warm cache hits, it is open-weights for on-prem and regulated lanes.

Verdict

Kimi K2.6 leads on quality while GPT-5 Mini leads on reuse-adjusted cost. Send latency- and budget-sensitive volume to GPT-5 Mini and reserve Kimi K2.6 for the hard requests. Zumik's aliases route between them automatically under policy.

GPT-5 Mini vs Kimi K2.6, answered.

Is GPT-5 Mini or Kimi K2.6 cheaper?

At 55% prefix reuse, GPT-5 Mini blends to about $0.59 per 1M tokens and Kimi K2.6 to about $1.39. GPT-5 Mini is cheaper on that basis.

Which has the larger context window?

GPT-5 Mini has the larger window: 400K vs 262K tokens.

Which captures more reuse?

GPT-5 Mini shows higher measured cache capture (85% vs 81%) 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.