SSyncDev

AI model comparison

Llama 4 Scout 17B Instruct 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.

This Llama 4 Scout 17B Instruct vs Kimi K3 comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Llama 4 Scout 17B Instruct by Meta currently records 3.5M context, 16.4K maximum output, $0.18 input per 1M tokens, $0.59 output per 1M tokens. Kimi K3 by Moonshot AI records 1.0M context, 131.1K maximum output, $3.00 input per 1M tokens, $15.00 output per 1M tokens. The tables below separate documented capabilities, commercial limits, directory measurements, and source-linked benchmark evidence so you can see where the data is complete and where independent testing is still required.

Side-by-sideSpecs and pricing, compared

Meta

Llama 4 Scout 17B Instruct

Open Llama with long-context vision for efficient multimodal agents

Context
3.5M
Max output
16.4K
Input / 1M
$0.18
Output / 1M
$0.59
Output speed
—

Accepts

  • Text input
  • Image 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 Llama 4 Scout 17B Instruct leads in recorded data

  • Context capacity: 3.5M
  • Input price: $0.18
  • Output price: $0.59

Where Kimi K3 leads in recorded data

  • Maximum output: 131.1K

Context capacity

Higher listed limit

Llama 4 Scout 17B Instruct:3.5M

Kimi K3:1.0M

Llama 4 Scout 17B Instruct

Maximum output

Higher listed limit

Llama 4 Scout 17B Instruct:16.4K

Kimi K3:131.1K

Kimi K3

Input price

Lower recorded price

Llama 4 Scout 17B Instruct:$0.18

Kimi K3:$3.00

Llama 4 Scout 17B Instruct

Output price

Lower recorded price

Llama 4 Scout 17B Instruct:$0.59

Kimi K3:$15.00

Llama 4 Scout 17B Instruct

Output speed

Higher recorded throughput

Llama 4 Scout 17B Instruct:—

Kimi K3:—

No complete comparison

Time to first token

Lower recorded latency

Llama 4 Scout 17B Instruct:—

Kimi K3:—

No complete comparison

Intelligence Index

Higher directory index

Llama 4 Scout 17B Instruct:—

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

SpecificationLlama 4 Scout 17B InstructKimi K3
ProviderMetaMoonshot AI
Model familyllamakimi-k3
Accepted inputstext, imagetext, image, video
Produced outputstexttext
Context window3.5MRecorded lead1.0M
Max output16.4K131.1KRecorded lead
Intelligence Index——
Input price / 1M$0.18Recorded lead$3.00
Output price / 1M$0.59Recorded lead$15.00
Output speed——
Time to first token——
Reasoning modeNot documentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseOpen weightsOpen weights
ReleasedApr 5, 2025Jul 16, 2026

Workload guidance

Which model should you choose?

Llama 4 Scout 17B Instruct currently leads on larger context, lower recorded input price, lower recorded output price. Kimi K3 currently leads on larger maximum output. Choose according to the constraints that matter to your workload, then run the same representative prompts against both models before making a production commitment. Neither the larger number nor the lower price is automatically the better choice: prompt quality, tool reliability, modality support, rate limits, data policy, and provider implementation can change the result. Use this page to build a shortlist, confirm current terms in the linked sources, and validate quality, latency, and cost with your own traffic.

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