TechCompare LogoTechCompare

Kimi K3 API Pricing & Cost Calculator

By TechCompare · Updated · How we check

Kimi K3 is cheaper than both Claude Opus 5 and GPT-5.6 Sol on input and output. Pair its 90% cache discount with long-context agentic workflows to cut the input bill.

Calculator

Cost Comparison

Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.Prices come live from OpenRouter at each maker's own price where it's listed. Temporary deals are left out.

Loading model prices
Same 100,000 in / 5,000 out (50% cached) scenario, pre-loaded. Adjust tokens, caching, or swap models.
Edit in the full tool

Kimi K3 is Moonshot AI's frontier reasoning model, sitting just behind Claude Opus 5 and GPT-5.6 Sol on the smartness tier but cheaper per token than either.

MoonshotAI: Kimi K3

Moonshot AI's own price

Input
$3
Output
$15
Cached
$0.30

per 1M tokens

Batch available

Price checked 2026-11-12

How this is calculated

Kimi K3 is priced at $3.00 per million input tokens and $15.00 per million output tokens, with a prompt caching discount of 90% ($0.30 per million). That puts it between Claude Sonnet 5 ($2/$10) and Claude Opus 5 ($5/$25).

Verdict

Kimi K3 lands at $3/M input and $15/M output, putting it between Sonnet 5 ($2/$10) and Opus 5 ($5/$25) on both rows. The 90% cache discount drops input to $0.30/M, which is where the long-context agentic case lives: stable system prompts and tool definitions reused across thousands of calls bill at that rate instead of the headline one.

At a representative 100K input + 5K output call the standard cost is about $0.375, and with 90,000 of the input tokens cached the input side falls to $0.057 while output stays the same, so the per-call math scales cleanly into the volume tier.

More API Standalones scenarios

Kimi K3.1 Pro vs Kimi K3
Compare Pro and K3 on base rates, cache reads, and where open weights can run.
View details
Kimi K3 vs Claude Opus 5
A frontier-tier reasoner from Moonshot AI against Anthropic's Opus 5. Compare the cost of a finished task.
View details
Kimi K3.1 Pro vs Claude Opus 5.5
Compare agent session costs, cache reads and writes, and what open weights add.
View details

Related guides

Kimi K3.1 Pro API pricing
See the rates for the post-trained K3.1 Pro.
View guide
Kimi K3.1 Pro vs Kimi K3
Compare the two models' input, output, and cache costs.
View guide
kimi k3 2 8t VRAM estimate
VRAM footprint for the kimi k3 2 8t model this pricing entry is for.
View guide
BPE tokenization explained
How tokenizers chunk text into the units VRAM serves.
View guide

Frequently asked questions

Is Kimi K3 cheaper than Claude Sonnet 5?
No. Kimi K3 costs $3.00 per million input and $15.00 per million output vs Sonnet 5's $2.00/$10.00. Kimi sits between Sonnet 5 and Opus 5, priced for buyers who need more intelligence than Sonnet without paying Opus rates.
How much does Kimi K3 cost per million output tokens?
Kimi K3 charges $15.00 per million output tokens, 40% cheaper than Claude Opus 5's $25/M. With its 90% prompt caching discount, cached input drops to $0.30 per million. There is no batch discount on Kimi K3, so asynchronous bulk work doesn't get the batch rates Anthropic offers on Opus 5 ($2.50/$12.50).
Is Kimi K3 actually cheaper than Claude Sonnet 5?
Not right now, even for high-volume live workloads. Kimi K3 charges $3/M input and $15/M output, identical to Sonnet 4.6. Against Sonnet 5's $2/$10, a 100K-input, 5K-output call with half the input cached costs $0.24 on Kimi K3 and $0.16 on Sonnet 5. Cached input costs $0.30/M on Kimi and $0.20/M on Sonnet 5, and both have a 1M context window. Kimi also has the smaller ecosystem and less mature tool-calling.

Related tools

LLM VRAM Calculator

Calculate the VRAM needed to run or fine-tune any LLM at any quantization.

Use tool

Power Cost Estimator

Estimate annual electricity costs for your PC, Server, or TV.

Use tool

Data Transfer Calculator

Estimate transfer times for files over USB, WiFi, Ethernet, and more.

Use tool

JSON Formatter

Validate, format, and minify JSON. Browse it as a tree, run JSONPath queries, compare two documents, or validate against a JSON Schema.

Use tool