SSyncDev

AI model comparison

Qwen/Qwen2.5-Omni-7B vs GPT-5.6 Sol

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

This Qwen/Qwen2.5-Omni-7B vs GPT-5.6 Sol comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Qwen/Qwen2.5-Omni-7B by Qwen currently records 32.8K context, 2.0K maximum output, $0.10 input per 1M tokens, $0.40 output per 1M tokens. GPT-5.6 Sol by OpenAI records 1.1M context, 128K maximum output, $5.00 input per 1M tokens, $30.00 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

Qwen

Qwen/Qwen2.5-Omni-7B

Qwen/Qwen2.5-Omni-7B is a source-linked Hugging Face repository assigned to Any-to-any. Its recorded task interface accepts text, image, audio, video and produces text, image, audio, video.

Context
32.8K
Max output
2.0K
Input / 1M
$0.10
Output / 1M
$0.40
Output speed
—

Accepts

  • Text input
  • Image input
  • Audio input
  • Video input

Produces

  • Text output
  • Image output
  • Audio output
  • Video output
Full model profileVendor docs ↗
VS

OpenAI

GPT-5.6 Sol

Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows

Context
1.1M
Max output
128K
Input / 1M
$5.00
Output / 1M
$30.00
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 Qwen/Qwen2.5-Omni-7B leads in recorded data

  • Input price: $0.10
  • Output price: $0.40

Where GPT-5.6 Sol leads in recorded data

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

Context capacity

Higher listed limit

Qwen/Qwen2.5-Omni-7B:32.8K

GPT-5.6 Sol:1.1M

GPT-5.6 Sol

Maximum output

Higher listed limit

Qwen/Qwen2.5-Omni-7B:2.0K

GPT-5.6 Sol:128K

GPT-5.6 Sol

Input price

Lower recorded price

Qwen/Qwen2.5-Omni-7B:$0.10

GPT-5.6 Sol:$5.00

Qwen/Qwen2.5-Omni-7B

Output price

Lower recorded price

Qwen/Qwen2.5-Omni-7B:$0.40

GPT-5.6 Sol:$30.00

Qwen/Qwen2.5-Omni-7B

Output speed

Higher recorded throughput

Qwen/Qwen2.5-Omni-7B:—

GPT-5.6 Sol:—

No complete comparison

Time to first token

Lower recorded latency

Qwen/Qwen2.5-Omni-7B:—

GPT-5.6 Sol:—

No complete comparison

Intelligence Index

Higher directory index

Qwen/Qwen2.5-Omni-7B:—

GPT-5.6 Sol:—

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

SpecificationQwen/Qwen2.5-Omni-7BGPT-5.6 Sol
ProviderQwenOpenAI
Model family—gpt-sol
Accepted inputstext, image, audio, videotext, image, pdf
Produced outputstext, image, audio, videotext
Context window32.8K1.1MRecorded lead
Max output2.0K128KRecorded lead
Intelligence Index——
Input price / 1M$0.10Recorded lead$5.00
Output price / 1M$0.40Recorded lead$30.00
Output speed——
Time to first token——
Reasoning modeNot documentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputDocumentedNot documented
Structured outputNot documentedDocumented
LicenseNot documentedProprietary
ReleasedDec 1, 2024Jul 9, 2026

Workload guidance

Which model should you choose?

Qwen/Qwen2.5-Omni-7B currently leads on lower recorded input price, lower recorded output price. GPT-5.6 Sol currently leads on larger context, 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.

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

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