Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Kimi K2.6 (Non-reasoning) | DeepSeek R1 (Jan '25) |
|---|---|---|
| Input ($/M tokens) | $0.95 | $2 |
| Output ($/M tokens) | $4 | $4 |
Verdict. Kimi K2.6 (Non-reasoning) and DeepSeek R1 (Jan '25) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, DeepSeek R1 (Jan '25) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). DeepSeek R1 (Jan '25) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Kimi K2.6 (Non-reasoning) is strongest on Intelligence Index (35.4). DeepSeek R1 (Jan '25) leads on Coding Index (24.6), Intelligence Index (18.6).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Kimi and DeepSeek sell to overlapping but distinct developer audiences: Kimi tends to ship frontier reasoning models with premium positioning, while DeepSeek 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): Kimi K2.6 (Non-reasoning) costs $88.50 ($1062/year); DeepSeek R1 (Jan '25) costs $120.00 ($1440/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Kimi K2.6 (Non-reasoning) ≈ $12.75/run, DeepSeek R1 (Jan '25) ≈ $18.00/run. At agent/realtime scale (200M input / 100M output per million requests): Kimi K2.6 (Non-reasoning) ≈ $590/run, DeepSeek R1 (Jan '25) ≈ $800/run. Kimi K2.6 (Non-reasoning) 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.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Kimi K2.6 (Non-reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $1.71/M tokens vs $2.50/M for DeepSeek R1 (Jan '25).
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
Kimi K2.6 (Non-reasoning) generates tokens faster at 40 tok/s vs — tok/s. Kimi K2.6 (Non-reasoning) also has lower time-to-first-token (2.76s vs —s).
Choose based on your priorities: Kimi K2.6 (Non-reasoning) for lower cost, both perform similarly on benchmarks, and Kimi K2.6 (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.