Gemini 3.1 Pro vs Kimi K3
Google's Gemini 3.1 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
Gemini 3.1 Pro is the cheaper option — roughly 1.3x less on a blended workload, and it suits best price-to-reasoning ratio. Kimi K3 justifies its premium when you need natively multimodal long-horizon agents.
Google • Gemini 3.1
$2.00 / $12.00
/ 1M tokens (input / output)
Google's shipping flagship while 3.5 Pro remains unreleased, and the cheapest frontier model by a wide margin. It still tops several hard-reasoning boards including GPQA Diamond and ARC-AGI-2, making it the value choice for research-style workloads — provided you keep prompts under 200K tokens, where the price doubles.
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 50% more expensive than Gemini 3.1 Pro on input tokens.
Output price
Kimi K3 is 25% more expensive than Gemini 3.1 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 | Gemini 3.1 Pro | Kimi K3 | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $4 | $6 | $2 |
| Moderate — 10M in / 2M out | $44 | $60 | $16 |
| Heavy — 100M in / 20M out | $440 | $600 | $160 |
Specification comparison
| Attribute | Gemini 3.1 Pro | Kimi K3 |
|---|---|---|
| Input (/ 1M tokens) | $2.00 | $3.00 |
| Output (/ 1M tokens) | $12.00 | $15.00 |
| Cached input | — | $0.30 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Max output | 65,536 tokens | 131,072 tokens |
| Native reasoning | Yes | Yes |
| Knowledge cutoff | 2025-06 | 2026-02 |
| Relative latency | medium | high |
| Open weights | No | Kimi K3 License (commercial terms above $20M revenue) |
| API model ID | gemini-3.1-pro-preview | kimi-k3 |
| Status | preview | stable |
Gemini 3.1 Pro: Prompts over 200K tokens reprice to $4 input / $18 output per 1M.
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 Gemini 3.1 Pro if…
- Hard reasoning and research tasks
- Long-context document and video analysis
- Native multimodal pipelines
- Cost-conscious frontier 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 Gemini 3.1 Pro or Kimi K3 cheaper?
Gemini 3.1 Pro is cheaper. On a blended 3:1 input-to-output workload it costs about 1.3x less than Kimi K3.
Which has the larger context window, Gemini 3.1 Pro or Kimi K3?
Both accept up to 1.05M tokens, so context is not a differentiator here.
Should I use Gemini 3.1 Pro or Kimi K3?
Pick Gemini 3.1 Pro for best price-to-reasoning ratio. Pick Kimi K3 for natively multimodal long-horizon agents. If cost dominates the decision, Gemini 3.1 Pro wins; if you need the capability ceiling, benchmark both on your own evals before committing.