AI model comparison

Gemini 1.5 Pro vs LongCat-2.0

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

Gemini 1.5 Pro and LongCat-2.0 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

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
VS

Meituan

LongCat-2.0

Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window

Context
1M
Max output
131.1K
Input / 1M
$0.75
Output / 1M
$3.00
Output speed

Accepts

  • Text input

Produces

  • Text output

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 LongCat-2.0 leads in recorded data

  • Maximum output: 131.1K
  • Input price: $0.75
  • Output price: $3.00

Context capacity

Higher listed limit

Gemini 1.5 Pro:2M

LongCat-2.0:1M

Gemini 1.5 Pro

Maximum output

Higher listed limit

Gemini 1.5 Pro:8.2K

LongCat-2.0:131.1K

LongCat-2.0

Input price

Lower recorded price

Gemini 1.5 Pro:$1.25

LongCat-2.0:$0.75

LongCat-2.0

Output price

Lower recorded price

Gemini 1.5 Pro:$5.00

LongCat-2.0:$3.00

LongCat-2.0

Output speed

Higher recorded throughput

Gemini 1.5 Pro:65 t/s

LongCat-2.0:

No complete comparison

Time to first token

Lower recorded latency

Gemini 1.5 Pro:0.90s

LongCat-2.0:

No complete comparison

Intelligence Index

Higher directory index

Gemini 1.5 Pro:75.8

LongCat-2.0:

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 ProLongCat-2.0
ProviderGoogleMeituan
Model familyGemini 1.5longcat
Accepted inputstext, image, audio, videotext
Produced outputstexttext
Context window2MRecorded lead1M
Max output8.2K131.1KRecorded lead
Intelligence Index75.8
Input price / 1M$1.25$0.75Recorded lead
Output price / 1M$5.00$3.00Recorded lead
Output speed65 t/s
Time to first token0.90s
Reasoning modeNot documentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedNot documented
Audio inputDocumentedNot documented
Structured outputDocumentedNot documented
LicenseProprietaryProprietary
ReleasedMay 14, 2024Jun 30, 2026

Workload guidance

Which model should you choose?

On the published numbers, Gemini 1.5 Pro accepts the larger context window and LongCat-2.0 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.

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