SSyncDev

AI model comparison

Gemini 1.5 Pro vs Qwen2.5 72B Instruct

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

This Gemini 1.5 Pro vs Qwen2.5 72B Instruct comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Gemini 1.5 Pro by Google currently records 2M context, 8.2K maximum output, $1.25 input per 1M tokens, $5.00 output per 1M tokens, 65 t/s recorded output speed, 0.90s recorded time to first token. Qwen2.5 72B Instruct by Deepinfra via Requesty records 131.1K context, $0.23 input per 1M tokens, $0.40 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

Google

Gemini 1.5 Pro

Google's long-context multimodal model with up to 2M token windows.

Context
2M
Max output
8.2K
Input / 1M
$1.25
Output / 1M
$5.00
Output speed
65 t/s

Accepts

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

Produces

  • Text output
Full model profileVendor docs ↗
VS

Deepinfra via Requesty

Qwen2.5 72B Instruct

Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique ability to switch seamlessly between a thinking mode for complex reasoning and a non-thinking mode for efficient dialogue ensures versatile, high-quality performance. Significantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.

Context
131.1K
Max output
—
Input / 1M
$0.23
Output / 1M
$0.40
Output speed
—

Accepts

  • Text 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 Gemini 1.5 Pro leads in recorded data

  • Context capacity: 2M

Where Qwen2.5 72B Instruct leads in recorded data

  • Input price: $0.23
  • Output price: $0.40

Context capacity

Higher listed limit

Gemini 1.5 Pro:2M

Qwen2.5 72B Instruct:131.1K

Gemini 1.5 Pro

Maximum output

Higher listed limit

Gemini 1.5 Pro:8.2K

Qwen2.5 72B Instruct:—

No complete comparison

Input price

Lower recorded price

Gemini 1.5 Pro:$1.25

Qwen2.5 72B Instruct:$0.23

Qwen2.5 72B Instruct

Output price

Lower recorded price

Gemini 1.5 Pro:$5.00

Qwen2.5 72B Instruct:$0.40

Qwen2.5 72B Instruct

Output speed

Higher recorded throughput

Gemini 1.5 Pro:65 t/s

Qwen2.5 72B Instruct:—

No complete comparison

Time to first token

Lower recorded latency

Gemini 1.5 Pro:0.90s

Qwen2.5 72B Instruct:—

No complete comparison

Intelligence Index

Higher directory index

Gemini 1.5 Pro:75.8

Qwen2.5 72B Instruct:—

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

SpecificationGemini 1.5 ProQwen2.5 72B Instruct
ProviderGoogleDeepinfra via Requesty
Model familyGemini 1.5—
Accepted inputstext, image, audio, videotext
Produced outputstexttext
Context window2MRecorded lead131.1K
Max output8.2K—
Intelligence Index75.8—
Input price / 1M$1.25$0.23Recorded lead
Output price / 1M$5.00$0.40Recorded lead
Output speed65 t/s—
Time to first token0.90s—
Reasoning modeNot documentedNot documented
Tool callingDocumentedDocumented
Image inputDocumentedNot documented
Audio inputDocumentedNot documented
Structured outputDocumentedDocumented
LicenseProprietaryNot documented
ReleasedMay 14, 2024Not documented

Workload guidance

Which model should you choose?

Gemini 1.5 Pro currently leads on larger context. Qwen2.5 72B Instruct currently leads on 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.

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