Gemini 3.1 Pro vs Kimi K3
Google vs Moonshot AI · Prices checked 12 August 2026
Gemini 3.1 Pro is 24 per cent cheaper on blended cost, $5.00 per million tokens against $6.60. A single 100K-input, 10K-output job costs $0.320 on Gemini 3.1 Pro against $0.450 on Kimi K3.
Kimi K3 takes a 1,049,000-token context window against 1,000,000, giving a modest edge for long documents or whole-codebase work.
Pricing and capacity
| Metric | Gemini 3.1 Pro | Kimi K3 | Difference |
|---|---|---|---|
| Input / 1M tokens | $2.00 | $3.00 | 33% |
| Output / 1M tokens | $12.00 | $15.00 | 20% |
| Blended · 70/30calculated | $5.00 | $6.60 | 24% |
| Blended · 50/50calculated | $7.00 | $9.00 | 22% |
| Blended · 80/20calculated | $4.00 | $5.40 | 26% |
| Blended · 20/80calculated | $10.00 | $12.60 | 21% |
| Job cost · 100K + 10Kcalculated | $0.320 | $0.450 | 29% |
| Job cost · 1M + 100Kcalculated | $3.20 | $4.50 | 29% |
| Context window | 1,000,000 | 1,049,000 | 5% |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
These two models do not currently report scores on any of the same benchmark suites, so there is no like-for-like capability comparison to show. Rather than pad the page with one-sided numbers, the benchmark leaderboards list every score we do hold.
What each model is for
Gemini 3.1 Pro
Google · Frontier
A mid-cycle upgrade to Gemini 3 Pro, released after rapid iteration on feedback from the November 3 Pro launch. Google positions it for the most complex tasks, with the clearest gains in ambitious agentic workflows. Keeps the 1M-token context window and full multimodal input.
- Agentic workflow execution
- Complex multi-step reasoning
- 1M-token context
- Text, image, audio and video input
Kimi K3
Moonshot AI · Frontier
Moonshot AI's 2.7-trillion-parameter flagship, released in July 2026 as the largest open-weight model published to date and the first Chinese model widely treated as competitive with the top US frontier systems. It runs an always-on reasoning mode Moonshot calls "thinking mode", handles a 1M-token context window, and understands images natively. Two variants shipped: K3 Max for chat and agent work, K3 Swarm Max for large-scale parallel processing.
- Largest open-weight model released to date (2.7T parameters)
- Always-on "thinking mode" reasoning
- 1M-token context
- Native visual understanding
Frequently asked questions
Which is cheaper, Gemini 3.1 Pro or Kimi K3?
Gemini 3.1 Pro is 24 per cent cheaper on blended cost, $5.00 per million tokens against $6.60. A single 100K-input, 10K-output job costs $0.320 on Gemini 3.1 Pro against $0.450 on Kimi K3. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which has the larger context window, Gemini 3.1 Pro or Kimi K3?
Kimi K3 takes a 1,049,000-token context window against 1,000,000, giving a modest edge for long documents or whole-codebase work. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare Gemini 3.1 Pro and Kimi K3 on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.