Kimi K2 Thinking
Retired May 2026Reasoning variant of Kimi K2, Moonshot AI's 1T-parameter MoE, designed for deep multi-step reasoning and complex analysis.
- Params
- 1T, 32B active
- Context
- 262K tokens
- License
- Modified MIT
Hosted API price
Cheapest via Novita · per 1M tokens
- Input
- $0.60 /1M
- Output
- $2.50 /1M
- Hosted by
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2 providers
Hosted API pricing
How we price
Order
Providers are listed cheapest input rate first, then by output rate, a tie going to the creator's own listing. A provider that lists the model without a published rate sits at the end.
Prices
Base-tier, on-demand rates in USD per 1M tokens, converted at ECB reference rates where a provider publishes in another currency. Cached-input and batch rates show only where a provider publishes them. "Cheapest" marks the one provider with the lowest input and output pair; a tie wears no badge.
Cost
Input rate times the input tokens plus output rate times the output tokens, at the monthly volume set above the table. Cached-input, batch, long-context and reasoning-token billing are not modelled.
Transparency and funding
- Affiliates: Affiliate links are marked. We may earn a commission if you click them, but commissions never affect the order.
Every provider serving Kimi K2 Thinking, cheapest input first. Set your monthly volume to see what each would bill.
| Provider | Input /1M | Output /1M | Cached input /1M | Cost at 10M in + 2M out | Link |
|---|---|---|---|---|---|
|
|
$0.60 | $2.50 | $0.15 | $11.00 | Visit website |
|
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Open weights, no hosted price | Visit website | |||
Heads up: Base-tier, on-demand rates per 1M tokens; cached, batch and long-context tiers excluded. A provider may serve a shorter context or a quantized build than the creator's release. Verify before provisioning. More on how we price.
Estimated cost to self-host
Kimi K2 Thinking needs about 554 GB of GPU memory at 4-bit with 32K context. The cheapest rental that fits is 8× A100 at about $9,850 a month.
That costs the same as roughly 11B tokens a month on Novita's API. Self-hosting is more expensive below that volume.
| Precision | Memory | Cheapest fit (32K context) | Cost /mo | Break-even vs API |
|---|---|---|---|---|
| 4-bit INT4 / FP4 | 554 GB |
|
$9,850 | 11B tokens /mo |
| 8-bit FP8 / INT8 | 1,003 GB |
|
$22,723 | 25B tokens /mo |
| 16-bit FP16 / BF16 | 2,004 GB |
|
$45,446 | 50B tokens /mo |
Estimates based on median on-demand rates for Nvidia GPUs. Memory is weights plus KV cache for one request, using FP8 KV cache where supported and FP16/BF16 otherwise. Break-even assumes a 5:1 input-to-output ratio. No guarantee of runtime support, usable performance, or that a matching quantized build exists. Pricing methodology.
Similarly priced models
The models nearest Kimi K2 Thinking by blended rate, each at its own cheapest provider.
| Model | Blended /1M | Input /1M | Output /1M | Context | Cutoff | vs Kimi K2 Thinking |
|---|---|---|---|---|---|---|
|
|
$0.7333 | $0.40 | $2.40 | 1M | −20% | |
|
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$0.7667 | $0.60 | $1.60 | 200K | −16% | |
|
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$0.80 | $0.80 | $0.80 | 131K | −13% | |
|
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$0.8667 | $0.60 | $2.20 | 205K | −5% | |
|
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$0.9167 | $0.50 | $3.00 | 1M | Jan 2025 | 0% |
|
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$0.9167 | $0.60 | $2.50 | 262K | ||
|
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$0.9167 | $0.50 | $3.00 | 1M | 0% | |
|
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$0.95 | $0.70 | $2.20 | 1M | +4% | |
|
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$0.99 | $0.66 | $2.64 | 1M | Sep 2025 | +8% |
|
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$1.00 | $0.70 | $2.50 | 128K | +9% | |
|
|
$1.00 | $0.70 | $2.50 | 64K | +9% |
USD per 1M tokens at each model's cheapest listed provider. Blended is the cost of 10M input plus 2M output tokens, spread over the 12M.
Capabilities
What Kimi K2 Thinking accepts and can do, as published by Moonshot AI.
- Text Accepts and generates natural-language text.
- Reasoning Thinks before it answers, always on or as a switchable mode.
- Function calling Connect to external tools, APIs, and systems.
- Structured output Return responses in structured formats like JSON.
- Web search Search the web for up-to-date information.
Common questions
What is Kimi K2 Thinking good for?
Multi-step reasoning and long tool-calling chains: Moonshot built it as a thinking agent that mixes chain-of-thought with tool calls. Modified MIT weights allow self-hosting, on a multi-GPU node.
When is Kimi K2 Thinking not a good fit?
New deployments: Moonshot retired it in May 2026, and the later Kimi models carry the line on. Text only, and running the weights yourself takes a multi-GPU node.
What is the cheapest way to run Kimi K2 Thinking?
Can I self-host Kimi K2 Thinking?
Yes. The weights are Modified MIT licensed. At 4-bit it needs about 554 GB of GPU memory, which starts at roughly $9,850 a month on the cheapest rental that fits.
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