DeepSeek V4-Pro vs Kimi K3
DeepSeek's DeepSeek V4-Pro and Moonshot AI's Kimi K3 both target production language workloads, but they price and behave differently. Here is the side-by-side.
Pricing checked against provider documentation on . How we verify
The short answer
DeepSeek V4-Pro is the cheaper option — roughly 6.1x less on a blended workload, and it suits frontier-adjacent reasoning at open-weight prices. Kimi K3 justifies its premium when you need natively multimodal long-horizon agents.
DeepSeek • DeepSeek V4
$0.66 / $1.98
/ 1M tokens (input / output)
A 1.6T-parameter mixture-of-experts model with 49B active, released under MIT and callable through DeepSeek's own API with configurable reasoning effort. Since 16 August 2026 DeepSeek bills on a peak/off-peak schedule, so the hour you run a job changes the bill by exactly 2x — which makes it unusually well suited to scheduled batch work.
Moonshot AI • Kimi K
$3.00 / $15.00
/ 1M tokens (input / output)
At 2.8T total parameters with 104B active, Kimi K3 is the largest open-weight model in general circulation and the only one here that ingests video natively. Reasoning is always on with configurable effort. The licence is the catch: it is not a standard open licence, and organisations above $20M in revenue need a separate commercial agreement.
Input price
Kimi K3 is 4.5x the price than DeepSeek V4-Pro on input tokens.
Output price
Kimi K3 is 7.6x the price than DeepSeek V4-Pro on output tokens — usually the side that dominates the bill.
Monthly cost at three workload sizes
Standard (non-batch, non-cached) rates. Reasoning models will exceed these figures because thinking tokens bill as output.
| Workload | DeepSeek V4-Pro | Kimi K3 | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $1 | $6 | $5 |
| Moderate — 10M in / 2M out | $11 | $60 | $49 |
| Heavy — 100M in / 20M out | $106 | $600 | $494 |
Specification comparison
| Attribute | DeepSeek V4-Pro | Kimi K3 |
|---|---|---|
| Input (/ 1M tokens) | $0.66 | $3.00 |
| Output (/ 1M tokens) | $1.98 | $15.00 |
| Cached input | $0.02 | $0.30 |
| Context window | 1,000,000 tokens | 1,048,576 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Native reasoning | Yes | Yes |
| Knowledge cutoff | 2026-03 | 2026-02 |
| Relative latency | medium | high |
| Open weights | MIT | Kimi K3 License (commercial terms above $20M revenue) |
| API model ID | deepseek-v4-pro | kimi-k3 |
| Status | stable | stable |
DeepSeek V4-Pro: Off-peak rate shown. Peak rates are exactly double ($1.32 input / $3.96 output) during 01:00–04:00 and 06:00–10:00 UTC, Monday to Friday. Cache hits cost roughly 3% of a cache miss.
Kimi K3: The custom licence requires a separate commercial agreement once the licensee and its affiliates exceed $20M revenue over any consecutive 12 months.
Choose DeepSeek V4-Pro if…
- Overnight batch reasoning jobs
- Self-hosted deployments needing MIT terms
- Cost-sensitive coding agents
- Chinese-language workloads
Choose Kimi K3 if…
- Multimodal agent workflows
- Video and image understanding at length
- Ambitious long-horizon automation
- Research requiring open weights at scale
Frequently asked
Is DeepSeek V4-Pro or Kimi K3 cheaper?
DeepSeek V4-Pro is cheaper. On a blended 3:1 input-to-output workload it costs about 6.1x less than Kimi K3.
Which has the larger context window, DeepSeek V4-Pro or Kimi K3?
Kimi K3 has the larger window at 1.05M tokens versus 1M.
Should I use DeepSeek V4-Pro or Kimi K3?
Pick DeepSeek V4-Pro for frontier-adjacent reasoning at open-weight prices. Pick Kimi K3 for natively multimodal long-horizon agents. If cost dominates the decision, DeepSeek V4-Pro wins; if you need the capability ceiling, benchmark both on your own evals before committing.