AI model comparison

Qwen3.6 Flash vs Kimi K3

Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.

Qwen3.6 Flash and Kimi K3 both come up when teams are choosing a model for production work, and the honest answer usually depends on your workload rather than a leaderboard. This page puts their published specifications side by side — context window, token pricing, supported inputs and outputs — so you can see where they actually differ.

Side-by-sideReviewed by our team

Alibaba

Qwen3.6 Flash

Qwen vision-language model for visual reasoning, documents, and agent tasks

Context
1M
Max output
65.5K
Input / 1M
$0.19
Output / 1M
$1.13
Output speed

Accepts

  • Text input
  • Image input
  • Video input

Produces

  • Text output
VS

Moonshot AI

Kimi K3

Moonshot's frontier model — 2.8 trillion parameters, a million-token window, and thinking effort you can dial up when the task deserves it.

Context
1.0M
Max output
131.1K
Input / 1M
$3.00
Output / 1M
$15.00
Output speed

Accepts

  • Text input
  • Image input
  • Video input

Produces

  • Text output

At a glance

Decision snapshot

This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.

Where Qwen3.6 Flash leads in recorded data

  • Input price: $0.19
  • Output price: $1.13

Where Kimi K3 leads in recorded data

  • Context capacity: 1.0M
  • Maximum output: 131.1K

Context capacity

Higher listed limit

Qwen3.6 Flash:1M

Kimi K3:1.0M

Kimi K3

Maximum output

Higher listed limit

Qwen3.6 Flash:65.5K

Kimi K3:131.1K

Kimi K3

Input price

Lower recorded price

Qwen3.6 Flash:$0.19

Kimi K3:$3.00

Qwen3.6 Flash

Output price

Lower recorded price

Qwen3.6 Flash:$1.13

Kimi K3:$15.00

Qwen3.6 Flash

Output speed

Higher recorded throughput

Qwen3.6 Flash:

Kimi K3:

No complete comparison

Time to first token

Lower recorded latency

Qwen3.6 Flash:

Kimi K3:

No complete comparison

Intelligence Index

Higher directory index

Qwen3.6 Flash:

Kimi K3:

No complete comparison

Evidence

Verified shared benchmarks

A score appears only when both records include a verified source. It is not treated as a universal ranking.

These two models haven't been measured on the same benchmark yet, so there's nothing meaningful to chart. Comparing scores from different tests would tell you more about the tests than the models — the specs and pricing above are the better guide here.

Specifications

Pricing, limits and capabilities

SpecificationQwen3.6 FlashKimi K3
ProviderAlibabaMoonshot AI
Model familyqwen3.6kimi-k3
Accepted inputstext, image, videotext, image, video
Produced outputstexttext
Context window1M1.0MRecorded lead
Max output65.5K131.1KRecorded lead
Intelligence Index
Input price / 1M$0.19Recorded lead$3.00
Output price / 1M$1.13Recorded lead$15.00
Output speed
Time to first token
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputDocumentedDocumented
LicenseProprietaryOpen weights
ReleasedApr 27, 2026Jul 16, 2026

Workload guidance

Which model should you choose?

On the published numbers, Kimi K3 accepts the larger context window and Qwen3.6 Flash is cheaper per input token. Which matters more depends on whether your bottleneck is document size or spend — the table above has the exact figures.

Provenance

Sources and data limits

Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.

Questions people ask

It compares recorded context and output limits, token prices, output speed, time to first token, Intelligence Index, modality support, tool and structured-output capabilities, release information, and only source-linked benchmarks verified on both records. Missing information is labeled rather than inferred.

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Choose any two approved model records and review them with the same evidence rules.

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