Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.2 Codex (xhigh) | Kimi K3 (low) |
|---|---|---|
| Input ($/M tokens) | $1.75 | $3 |
| Output ($/M tokens) | $14 | $15 |
Verdict. Kimi K3 (low) takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the mid-tier / premium bracket for output-token pricing. At 0.9× the per-million-token cost, GPT-5.2 Codex (xhigh) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5.2 Codex (xhigh) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.2 Codex (xhigh) is strongest on Intelligence Index (41.2). Kimi K3 (low) leads on Coding Index (72.0), Intelligence Index (48.3).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. OpenAI and Kimi sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Kimi often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GPT-5.2 Codex (xhigh) costs $262.50 ($3150/year); Kimi K3 (low) costs $315.00 ($3780/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.2 Codex (xhigh) ≈ $36.75/run, Kimi K3 (low) ≈ $45.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.2 Codex (xhigh) ≈ $1750/run, Kimi K3 (low) ≈ $2100/run. GPT-5.2 Codex (xhigh) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Data from Artificial Analysis API — 12 benchmarks
GPT-5.2 Codex (xhigh) is cheaper overall. Its blended price (3:1 input/output ratio) is $4.81/M tokens vs $6.00/M for Kimi K3 (low).
Kimi K3 (low) wins 2 out of 12 benchmarks compared to 0 for GPT-5.2 Codex (xhigh). See the detailed benchmark chart above for per-category results.
Kimi K3 (low) generates tokens faster at 36 tok/s vs — tok/s. However, Kimi K3 (low) has lower time-to-first-token (2.82s vs —s).
Choose based on your priorities: GPT-5.2 Codex (xhigh) for lower cost, Kimi K3 (low) for stronger benchmark performance, and Kimi K3 (low) for faster generation. For latency-sensitive apps, check the TTFT comparison above.