SSyncDev

AI model comparison

Claude Haiku 3.5 vs GPT-5.6 Luna

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

This Claude Haiku 3.5 vs GPT-5.6 Luna comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Claude Haiku 3.5 by Anthropic currently records 200K context, 8.2K maximum output, $0.80 input per 1M tokens, $4.00 output per 1M tokens. GPT-5.6 Luna by OpenAI records 1.1M context, 128K maximum output, $0.20 input per 1M tokens, $1.20 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

Anthropic

Claude Haiku 3.5

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

Context
200K
Max output
8.2K
Input / 1M
$0.80
Output / 1M
$4.00
Output speed
—

Accepts

  • Text input
  • Image input
  • PDF input

Produces

  • Text output
Full model profileVendor docs ↗
VS

OpenAI

GPT-5.6 Luna

Cost-efficient GPT-5.6 model for fast, high-volume workloads

Context
1.1M
Max output
128K
Input / 1M
$0.20
Output / 1M
$1.20
Output speed
—

Accepts

  • Text input
  • Image input
  • PDF 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 3.5 leads in recorded data

No complete recorded factor currently favors this model. That does not establish lower real-world quality.

Where GPT-5.6 Luna leads in recorded data

  • Context capacity: 1.1M
  • Maximum output: 128K
  • Input price: $0.20
  • Output price: $1.20

Context capacity

Higher listed limit

Claude Haiku 3.5:200K

GPT-5.6 Luna:1.1M

GPT-5.6 Luna

Maximum output

Higher listed limit

Claude Haiku 3.5:8.2K

GPT-5.6 Luna:128K

GPT-5.6 Luna

Input price

Lower recorded price

Claude Haiku 3.5:$0.80

GPT-5.6 Luna:$0.20

GPT-5.6 Luna

Output price

Lower recorded price

Claude Haiku 3.5:$4.00

GPT-5.6 Luna:$1.20

GPT-5.6 Luna

Output speed

Higher recorded throughput

Claude Haiku 3.5:—

GPT-5.6 Luna:—

No complete comparison

Time to first token

Lower recorded latency

Claude Haiku 3.5:—

GPT-5.6 Luna:—

No complete comparison

Intelligence Index

Higher directory index

Claude Haiku 3.5:—

GPT-5.6 Luna:—

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 3.5GPT-5.6 Luna
ProviderAnthropicOpenAI
Model familyclaude-haikugpt-luna
Accepted inputstext, image, pdftext, image, pdf
Produced outputstexttext
Context window200K1.1MRecorded lead
Max output8.2K128KRecorded lead
Intelligence Index——
Input price / 1M$0.80$0.20Recorded lead
Output price / 1M$4.00$1.20Recorded lead
Output speed——
Time to first token——
Reasoning modeNot documentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseProprietaryProprietary
ReleasedOct 22, 2024Jul 9, 2026

Workload guidance

Which model should you choose?

Claude Haiku 3.5 has no complete recorded factor that establishes a lead. GPT-5.6 Luna currently leads on larger context, larger maximum output, lower recorded input price, lower recorded output price. 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