How much cheaper is Kimi K3.1 Pro via tokenra.io?

tokenra.io serves Kimi K3.1 Pro at $0.40 input and $2.00 output per 1M tokens on its kimi-k3.1-pro-0.2x model ID, which is 80% off the official list price of $2.00 and $10.00 — one fifth of the cost for identical model weights.

Do I have to rewrite my code to switch to K3.1 Pro?

No. Both models use an OpenAI-compatible chat completions interface, so switching means changing the model name and, if you use a reseller, the base URL and API key. Request and response shapes stay the same.

Is Kimi K3 still supported after K3.1 Pro launches?

Kimi K3 remains callable through the official API and through resellers such as tokenra.io and OpenRouter. Vendors generally keep the prior generation available for a long deprecation window, but confirm current availability on the provider's model list before you commit a production workload.

Home › Comparisons › Kimi K3.1 Pro vs Kimi K3

Kimi K3.1 Pro vs Kimi K3: What Actually Changed

Q: Is Kimi K3.1 Pro better than Kimi K3?

Across the benchmarks we track, K3.1 Pro scores above K3, with the widest gap on agentic coding: Terminal-Bench 4.0 rose from 13% to 67%. No long-context accuracy figures have been published for either model. For short, simple prompts the two are close enough that the difference is hard to measure.

Updated October 25, 2026 · Prices in USD per 1M tokens · Official list price verified against the vendor pricing page

Short answer: K3.1 Pro is a capability upgrade on agentic coding, reasoning and reliability — and a price cut, not a new premium tier. On the official API it lists at $2.00 input / $10.00 output per 1M tokens, and tokenra.io serves the same model at $0.40 / $2.00 — 80% off. If your evaluation set shows K3.1 Pro beating K3 on your own prompts, the upgrade costs you nothing in engineering (same request shape) and costs less than what you pay today — a third less at official list prices, and less again through a reseller.

Kimi K3.1 Pro vs Kimi K3 at a glance

Prices per 1,000,000 tokens, USD, checked October 25, 2026. Benchmark figures are vendor-reported or measured by Artificial Analysis — sources on the benchmarks page.
Dimension	Kimi K3.1 Pro	Kimi K3
Official price — input	$2.00	$3.00
Official price — output	$10.00	$15.00
tokenra.io — input / output 80% off	$0.40 / $2.00 `kimi-k3.1-pro-0.2x`	$2.54 / $12.69 15% off
Context window	1,048,576 tokens	1,048,576 tokens
Reasoning / multi-step tasks	Clear improvement — Artificial Analysis Intelligence Index 55 vs 44	Baseline
Long-document retrieval	No accuracy figures at 100K / 500K / 1M published for either model — test on your own documents
Code generation	The widest measured gap — Terminal-Bench 4.0 67% vs 13%	Baseline
API compatibility	OpenAI-compatible chat completions	OpenAI-compatible chat completions
Migration effort	Change the `model` string — nothing else. Request and response schemas are identical.

Where the difference actually shows up

Reasoning and multi-step work

This is the reason to upgrade. On prompts that need several dependent steps — a calculation that feeds a second calculation, an agent loop that has to re-read its own output — K3.1 Pro holds the chain together more often, and it recovers from a wrong intermediate step instead of compounding it. On single-shot questions with a short answer, you will struggle to tell the two models apart.

Long context

Both models share the same 1,048,576-token window, and neither Moonshot nor Artificial Analysis has published accuracy at 100K, 500K or 1M tokens for either model — so there is no measured evidence yet that K3.1 Pro recalls deep context better than K3. If your product is a document Q&A, contract reviewer, or codebase assistant, run both models on your own longest documents before you count on a difference.

Code

K3.1 Pro applies multi-file edits more consistently — fewer cases where it updates the function but forgets the caller. It also follows an explicit style constraint (naming, error handling) through a longer file before drifting. Neither model replaces a review step; the difference is how much of the review you can skip.

Cost per request

Both models bill input and output separately, and output runs at five times the input rate on both. Because K3.1 Pro cut both rates by the same third — $2.00 / $10.00 against K3's $3.00 / $15.00 — the upgrade lowers the official bill by 33% whatever your mix. A search summarizer with 2,000-token inputs and 200-token outputs is dominated by input cost; a code generator with 500-token inputs and 4,000-token outputs is dominated by output; both save the same third. Price your own mix with the token cost calculator.

Should you upgrade?

Upgrade to K3.1 Pro if…

Your evaluation set shows K3 failing on multi-step or long-document prompts
You ship a coding assistant, document Q&A, or agent pipeline
Cost per token is a visible line on your bill — tokenra.io cuts it by 80%
You want headroom before you next touch the prompt layer

Stay on Kimi K3 if…

Your prompts are short and single-step and already score well
You measure latency per request and cannot absorb any change
Your integration is frozen and the benefit is unproven on your data

Rule of thumb: run twenty of your own hardest production prompts through both models before you decide. A benchmark gap on someone else's dataset is not evidence about your workload.

How to switch — one line of code

Both models speak the same OpenAI-compatible interface. If you call the official API, change the model name. If you call through a reseller, point the base URL at it and keep your existing request code untouched.

from openai import OpenAI

# Before — Kimi K3 on the official API
client = OpenAI(api_key=OFFICIAL_KEY, base_url="https://api.moonshot.ai/v1")
resp = client.chat.completions.create(model="kimi-k3", messages=[...])

# After — Kimi K3.1 Pro through tokenra.io at 80% off official pricing
client = OpenAI(api_key=TOKENRA_KEY, base_url="https://tokenra.io/v1")
resp = client.chat.completions.create(model="kimi-k3.1-pro-0.2x", messages=[...])
# everything else in your code stays the same

Base URLs and model IDs checked against each provider's documentation on October 25, 2026. On tokenra.io, kimi-k3.1-pro-0.2x bills at 80% off and plain kimi-k3.1-pro at 20% off. See API providers compared for the full route-by-route breakdown.

Frequently asked questions

Is Kimi K3.1 Pro better than Kimi K3?

On the benchmarks we track, yes — the lead is widest on agentic coding, where Terminal-Bench 4.0 went from 13% to 67%. No long-context accuracy figures have been published for either model. On short, simple prompts the two are close enough that the difference is hard to measure, so "better" depends on what you are asking it to do.

Should I migrate from Kimi K3 to K3.1 Pro?

Migrate if your product depends on reasoning depth, agentic workflows, or code generation. Stay on K3 if your prompts are short, latency-sensitive, and already scoring well. Run your own hardest prompts through both first — the upgrade only pays off when your evaluation set shows a real gap.

How much cheaper is Kimi K3.1 Pro through a reseller?

tokenra.io serves Kimi K3.1 Pro at $0.40 input / $2.00 output per 1M tokens on its kimi-k3.1-pro-0.2x model ID — 80% off the official $2.00 / $10.00, or one fifth of the cost, for identical model weights.

Do I have to rewrite my code to switch?

No. Both use an OpenAI-compatible chat completions interface. Switching means changing the model name, plus the base URL and key if you move to a reseller. Request and response shapes are unchanged.

Is Kimi K3 still available after K3.1 Pro ships?

Yes — K3 remains callable through the official API and through resellers. Vendors normally keep a prior generation up for a long deprecation window, but confirm current availability on your provider's model list before committing production traffic.