SSyncDev

AI model comparison

Claude Haiku 4.5 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.

Claude Haiku 4.5 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

Anthropic

Claude Haiku 4.5

Fast Claude model for responsive assistance, classification, and lightweight agents

Context
200K
Max output
64K
Input / 1M
$1.00
Output / 1M
$5.00
Output speed
—

Accepts

  • Text input
  • Image input
  • PDF input

Produces

  • Text output
Full model profileVendor docs ↗
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
Full model profileVendor docs ↗

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 Claude Haiku 4.5 leads in recorded data

  • Input price: $1.00
  • Output price: $5.00

Where Kimi K3 leads in recorded data

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

Context capacity

Higher listed limit

Claude Haiku 4.5:200K

Kimi K3:1.0M

Kimi K3

Maximum output

Higher listed limit

Claude Haiku 4.5:64K

Kimi K3:131.1K

Kimi K3

Input price

Lower recorded price

Claude Haiku 4.5:$1.00

Kimi K3:$3.00

Claude Haiku 4.5

Output price

Lower recorded price

Claude Haiku 4.5:$5.00

Kimi K3:$15.00

Claude Haiku 4.5

Output speed

Higher recorded throughput

Claude Haiku 4.5:—

Kimi K3:—

No complete comparison

Time to first token

Lower recorded latency

Claude Haiku 4.5:—

Kimi K3:—

No complete comparison

Intelligence Index

Higher directory index

Claude Haiku 4.5:—

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

SpecificationClaude Haiku 4.5Kimi K3
ProviderAnthropicMoonshot AI
Model familyclaude-haikukimi-k3
Accepted inputstext, image, pdftext, image, video
Produced outputstexttext
Context window200K1.0MRecorded lead
Max output64K131.1KRecorded lead
Intelligence Index——
Input price / 1M$1.00Recorded lead$3.00
Output price / 1M$5.00Recorded lead$15.00
Output speed——
Time to first token——
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseProprietaryOpen weights
ReleasedOct 15, 2025Jul 16, 2026

Workload guidance

Which model should you choose?

On the published numbers, Kimi K3 accepts the larger context window and Claude Haiku 4.5 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.

Compare a different pair

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

Open model comparison