SSyncDev

AI model comparison

Qwen3.5 9B 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.

Qwen3.5 9B and GPT-5.6 Luna 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

Qwen3.5 9B

Qwen instruction model for multilingual chat, reasoning, and tool use

Context
262.1K
Max output
65.5K
Input / 1M
$0.04
Output / 1M
$0.15
Output speed
—

Accepts

  • Text input
  • Image input
  • Video 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 Qwen3.5 9B leads in recorded data

  • Input price: $0.04
  • Output price: $0.15

Where GPT-5.6 Luna leads in recorded data

  • Context capacity: 1.1M
  • Maximum output: 128K

Context capacity

Higher listed limit

Qwen3.5 9B:262.1K

GPT-5.6 Luna:1.1M

GPT-5.6 Luna

Maximum output

Higher listed limit

Qwen3.5 9B:65.5K

GPT-5.6 Luna:128K

GPT-5.6 Luna

Input price

Lower recorded price

Qwen3.5 9B:$0.04

GPT-5.6 Luna:$0.20

Qwen3.5 9B

Output price

Lower recorded price

Qwen3.5 9B:$0.15

GPT-5.6 Luna:$1.20

Qwen3.5 9B

Output speed

Higher recorded throughput

Qwen3.5 9B:—

GPT-5.6 Luna:—

No complete comparison

Time to first token

Lower recorded latency

Qwen3.5 9B:—

GPT-5.6 Luna:—

No complete comparison

Intelligence Index

Higher directory index

Qwen3.5 9B:—

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

SpecificationQwen3.5 9BGPT-5.6 Luna
ProviderAlibabaOpenAI
Model familyqwengpt-luna
Accepted inputstext, image, videotext, image, pdf
Produced outputstexttext
Context window262.1K1.1MRecorded lead
Max output65.5K128KRecorded lead
Intelligence Index——
Input price / 1M$0.04Recorded lead$0.20
Output price / 1M$0.15Recorded lead$1.20
Output speed——
Time to first token——
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputDocumentedDocumented
LicenseOpen weightsProprietary
ReleasedFeb 23, 2026Jul 9, 2026

Workload guidance

Which model should you choose?

On the published numbers, GPT-5.6 Luna accepts the larger context window and Qwen3.5 9B 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