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Kimi K3.1 Pro Review: Always-On Thinking, 1M Tokens In and Out

Pick Kimi K3.1 Pro for long-context work with screenshots and clips when you accept always-on thinking; so far we have run only launch checks, no scored tests.

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Spicy Index

80.4/ 100

Preliminary

Freedom Score

Not yet tested

Price
$4.00 per 1M mixed tokens (3 input : 1 output)
Output speed
30 tok/s
Success rate
Collecting data

Kimi K3.1 Pro is Moonshot AI's new thinking model, released on 23 October 2026 as the first of the K3.1 series. On our API it is one OpenAI-compatible chat endpoint that reads text, images and video, holds 1,048,576 tokens of input and allows replies up to 1,048,576 tokens, with the thinking counted inside that number.

The verdict

Two behaviours shape how you use it. Thinking is always on: reasoningeffort accepts low, high or max (default max) and cannot be switched off. And sampling is fixed by Moonshot, so temperature and topp are not accepted. Together that means a default request reasons hard before every answer, and a small max_tokens can be spent on thinking before any visible text appears.

This is a launch-day review. On 28 October 2026 our platform ran a real request through the endpoint as part of launch: one neutral message, answered without streaming at low reasoning effort. It returned a complete answer. We have not run a quality blind test or a content-level test on K3.1 Pro, and this page does not score the model.

Try Kimi K3.1 Pro →

Key facts

  • Tested: one real launch request on 28 Oct 2026 (neutral prompt, low reasoning effort, no streaming), plus an integration check of image input. No scored runs yet.
  • Price: $2 per million input tokens, $0.20 cached and $10 output. The live price is on the model page.
  • Limits: 1,048,576-token context, replies up to 1,048,576 tokens (default 4,096, thinking included), text, image and video input, 256 messages and 128 tool definitions per request.
  • Reasoning: reasoning_effort takes low, high or max (default max); thinking is always on.
  • Sampling: fixed by the model; temperature and top_p are not accepted.
  • Sources: scoring rules are on our review methodology page, full parameters on the Kimi K3.1 Pro model page.

What we liked and what held it back

What we liked

  • A million tokens in and a matching reply ceiling. A whole repository or a long research thread travels as written, and a very long answer fits in one reply.
  • Video and images next to the question. A failing UI screenshot with the stack trace, or a short screen recording with the bug report, goes into the same message as the instruction.
  • Three reasoning dials. Low keeps replies quick, high suits multi-step problems, max gives the model the most room on a hard task.
  • Tool calling is on the endpoint. Up to 128 function definitions per request, paralleltoolcalls on by default, toolchoice and responseformat accepted; we have not graded tool-use quality yet.
  • A familiar request shape. The same OpenAI-compatible body as the rest of our chat models, so switching is a model-name change.

What held it back

  • Thinking cannot be turned off. There is no none, medium or xhigh, so even a simple rewrite pays for a reasoning pass unless you pick low.
  • max is the default effort. Every request reasons at full depth unless you set a lower level, which adds tokens and latency to quick turns.
  • No temperature or top_p. You cannot push for more varied prose with sampling; use the prompt, reasoning_effort and stop sequences instead.
  • Reasoning is paid for out of max_tokens. The default cap is 4,096, so a small cap at max effort can run out before the answer starts.
  • No audio input, and no quality numbers of our own yet.

What we tested

On 28 October 2026 our platform sent Kimi K3.1 Pro one real request as part of launch: a single neutral user message, answered without streaming at low reasoning effort with a 1,024-token cap. It returned a complete answer, and the request was priced at the published rate. The endpoint also passed our pre-launch checks of its price table and request limits. During integration a request with an image attached was also accepted and answered.

That is a working-endpoint check, not a benchmark. We have not compared K3.1 Pro's answers with K3 or another model, tested video input on real clips, measured speed, or tried a prompt near the 1,048,576-token limit. Moonshot's own claims about accuracy are Moonshot's; we have not reproduced them.

Prompts to start from

These starting prompts come from the model page's published examples. We have not graded the outputs, so they are a place to begin rather than prompts proven on this model.

1. A planning brief. Give it the brief and a standard for what a good plan looks like.

text
Turn a project brief into a dependency-ordered implementation plan with verifiable milestones. Work from the material I provide, cite the relevant evidence, distinguish facts from assumptions, and identify missing information before proposing changes.

Run this prompt on Kimi K3.1 Pro →

2. A tool step. Confirms your function-calling loop end to end with a trivial function.

text
Call report_status with status ready.

Settings that matter: set reasoningeffort to low for routine turns and keep max for hard planning; leave several thousand tokens of maxtokens headroom, since thinking shares the budget; send video and audio inline and keep them under 14 MB combined.

How far it writes

We have not run our content-level test on Kimi K3.1 Pro, so we have no result to report here. The model page states the position plainly: the platform adds no content filter of its own, content decisions come from the model, and behaviour can change between versions. The previous generation, Kimi K3, has a full content-level review; do not assume K3.1 Pro behaves the same.

Not tested yet: the content-level ladder, multi-turn behaviour over a long session, languages other than English, video understanding on real clips, and whether low effort changes any of the above.

Every character in a request should be an adult, keep real, identifiable people out of it, and you are responsible for the law where you publish.

What the community says

On the launch thread one reader took the vendor's numbers at face value: "It appears to be generally frontier-level." Another objected to how the open-weight version is being limited: "Ah, the version available to us mortals is nerfed in cybersecurity just like the US models :("

Alternatives

  • The previous generation with a full content-level review? Kimi K3 reads 1,000,000 tokens and carries our Unrestricted label; see the Kimi K3 review.
  • Another 1M-class reasoning model? DeepSeek V4 Pro is on the same API; compare it on your own prompts.
  • A hard-coding model with tool calls? GPT 6.1 Sol takes images, allows temperature and offers five reasoning levels.

How Kimi K3.1 Pro earns its Spicy Index

Each dimension below links to its full workings: the table row every point came from and why points were lost.

Public leaderboards 40% of quality
Not yet tested

No exact match on a tracked public leaderboard yet. How it works

Role-play 15% of quality
Not yet tested

Our role-play suite hasn’t run on this model yet. How it works

Creative writing 15% of quality
72.0
Instruction following 15% of quality
100.0
Long-context memory 15% of quality
Not yet tested

Our long-context suite hasn’t run on this model yet. How it works

Capability 10.5% weight
49.0
Freedom Score 30% weight
Not yet tested

Freedom evidence is untested or insufficient. The Index retains the original quality and capability score, is marked preliminary and still receives a rank. Missing evidence is not zero. How it works

Freedom evidence is untested or insufficient. The Index retains the original quality and capability score, is marked preliminary and still receives a rank. Missing evidence is not zero.

Open the full test report →

Capability, item by item

Points from the public scoring table. Upscaled tiers and limits we set ourselves don’t count.

Context window (creator-published)Not declared
0.0 / 30
Input modalities on SpicyAPIText, plus images
12.0 / 25
Tool useTools and tool_choice
15.0 / 15
Structured outputAccepted, schema adherence verified
15.0 / 15
Reasoning control3 levels: low · high · max
7.0 / 15

What Kimi K3.1 Pro can do on SpicyAPI

Straight from the live model specification on SpicyAPI. Some creators offer more in their own apps; this is what you can call through our API today.

Capabilities by endpoint
FeatureChat
Context window1,048,576 tokens
Max output per request1,048,576 tokens
Reasoning levelslow · high · max
Tool callingYes
Structured outputYes
See every parameter and code sample →

How long it really takes

Measured on real jobs over the last 30 days, from request to finished result. Times include our own test runs.

Output speed
30 tok/sIncludes time to first token
Success rate
Collecting data

A time appears once at least 10 completed jobs are in. Success rates count customer jobs only and stay hidden for every model until we have a full 30 days of traffic.

What people say about Kimi K3.1 Pro

1 positive · 0 mixed · 1 negative

  • It appears to be generally frontier-level.

    hacker-news· Oct 23, 2026· PositiveSource

  • Ah, the version available to us mortals is nerfed in cybersecurity just like the US models :(

    hacker-news· Oct 23, 2026· NegativeSource

Quotes are verbatim from public posts, linked to the original. They are not ratings and don’t feed any score.

Models to consider instead of Kimi K3.1 Pro

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Kimi K3.1 Pro FAQ

Try Kimi K3.1 Pro yourself

Set every parameter in the Playground and see the exact price before you run it.

$4.00 per 1M mixed tokens (3 input : 1 output)

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