by Moonshot AI
MoonshotAI: Kimi K3.
multimodal
open weights
1M ctx
Cheapest input
$2.6481/M
on OpenRouter
Cheapest output
$13.2827/M
on OpenRouter
Hosted equiv.
~$4.78/hr
@ 100 tok/s on OpenRouter
Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...
Where to use it
Cheapest hosted endpoints.
FAQ
Frequently asked.
How do I run MoonshotAI: Kimi K3?
MoonshotAI: Kimi K3 is open-weight, so you can self-host on rented GPUs. See the Run It Yourself tab for GPU configurations + cost estimates, or use one of the hosted inference providers listed on this page.
Where can I access MoonshotAI: Kimi K3?
MoonshotAI: Kimi K3 is available via Fireworks AI, Together AI, DeepInfra, OpenRouter. Each access option lists its own pricing (per million tokens or hourly hosting).
How much does it cost to run MoonshotAI: Kimi K3?
API pricing starts at $3.0/M input tokens and $15.0/M output tokens. Self-hosting cost depends on the GPU you rent — see the Run It Yourself tab.
Is MoonshotAI: Kimi K3 open-source or proprietary?
MoonshotAI: Kimi K3 is open-weight under the license. You can download and self-host it.
API pricing
Per provider
What it costs per month across providers.
Estimate your monthly bill for MoonshotAI: Kimi K3 across every host that publishes per-token pricing. Slide your token volumes; the chart + table re-rank cheapest-first.
Cheapest
$53.05
OpenRouter
Most expensive
$60.0
Together AI
Spread
$6.95
max − min
Providers
3
with priced rows
Monthly bill
Cheapest provider on the left.
Total monthly cost — input + output tokens combined.
Loading...
Bill breakdown.
Full calculator
Want to compare token volumes across other models too?
Open the standalone API pricing tool →
Context window
How much it can remember.
1M tokens
≈ 786,432 English words
4K
32K
128K
1M
Capabilities
What it can do.
·
Vision input
·
Audio input
·
Video input
·
Function calling
·
Tool use
·
JSON mode
✓
Streaming
·
Fine-tuning