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text model comparison

Gemini 3.5 Flash-Lite vs LongCat-2.5

Gemini 3.5 Flash-Lite and LongCat-2.5 are both current text models, from Google and Meituan. Both cost $0.30 per 1M input tokens. Both accept 1,048,576 tokens of context.

Data verified November 3, 2026 · Dataset 2026-11-03

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Side by side

Gemini 3.5 Flash-Lite and LongCat-2.5, line by line

Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.

FactGemini 3.5 Flash-LiteLongCat-2.5
Price
Price per 1M input tokens$0.30$0.30
Price per 1M output tokens$2.50$1.20 (better)
Independent benchmarks
Arena Text1456 Elo (#31 of 51)Not measured
Arena WebDev1434 Elo (#39 of 45)Not measured
FrontierMath Tiers 1-3 (v2)26% (#40 of 42)Not measured
GPQA Diamond83.3% (#36 of 41)Not measured
Specs
ProviderGoogleMeituan
Release dateJuly 21, 2026November 2, 2026
AccessAPI onlyAPI only
Context window1,048,576 tokens1,048,576 tokens
Max output65,536 tokens262,144 tokens
Inputtext, image, audio, videotext, image, video
Outputtexttext

No independent benchmark has scored both models yet. Each rank counts the current models scored on that benchmark.

Scores:Arena · 2026-11-03Epoch AI · 2026-11-03

Charts

Against every current text model

Where Gemini 3.5 Flash-Lite and LongCat-2.5 land among the current models of their task, on every independent benchmark, on price and on context.

Where each stands

Only Gemini 3.5 Flash-Lite has a current Arena Text score: #31 of 51. Each bar is the share of current models it beats.

Gemini 3.5 Flash-Lite and LongCat-2.5 among the current text models, one row per benchmark, price and context window.

Independent benchmarks

Arena Text

Gemini 3.5 Flash-Lite:#31of 51

1,456 Elo · ahead of 40%

LongCat-2.5: Not scored

Arena WebDev

Gemini 3.5 Flash-Lite:#39of 45

1,434 Elo · ahead of 14%

LongCat-2.5: Not scored

FrontierMath Tiers 1-3 (v2)

Gemini 3.5 Flash-Lite:#40of 42

26% · ahead of 5%

LongCat-2.5: Not scored

GPQA Diamond

Gemini 3.5 Flash-Lite:#36of 41

83.3% · ahead of 13%

LongCat-2.5: Not scored

Price and context

Price per 1M input tokens

Gemini 3.5 Flash-Lite:#11of 52

$0.30 · cheaper than 75%

LongCat-2.5:#11of 52

$0.30 · cheaper than 75%

Price per 1M output tokens

Gemini 3.5 Flash-Lite:#17of 52

$2.50 · cheaper than 65%

LongCat-2.5:#10of 52

$1.20 · cheaper than 76%

Context window

Gemini 3.5 Flash-Lite:#11of 64

1.05M tokens · longer than 67%

LongCat-2.5:#11of 64

1.05M tokens · longer than 67%

Quality against price

Arena Text · measured October 28, 2026

Gemini 3.5 Flash-Lite scores 1,456 at $0.85 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.

Quality against priceArena Text score against price for 43 text models, Gemini 3.5 Flash-Lite and LongCat-2.5 marked.1,2501,3001,3501,4001,4501,5001,550$0.30$1$3$10MOST ATTRACTIVE QUADRANTMedian price $3Median 1,475Blended price per 1M tokens (3 input : 1 output), log scaleArena Text (Elo)Gemini 3.5 Flash-Lite
Quality against price: the data
Arena Text score against price for 43 text models, Gemini 3.5 Flash-Lite and LongCat-2.5 marked.
ModelProviderBlended price per 1M tokensArena Text (Elo)
Gemini 4 ArgonGoogle$41,520
Claude Opus 5.5Anthropic$81,509
Muse WonderMeta$81,507
Claude Fable 5Anthropic$201,504
Claude Fable 5.1Anthropic$201,504
Gemini 3.8 FlashGoogle$1.501,496
Muse Spark 1.3Meta$21,495
Claude Opus 5Anthropic$101,492
Kimi K3Moonshot Kimi$61,488
GPT-5.6 SolOpenAI$81,485
Gemini 3.6 FlashGoogle$31,483
GPT-5.5OpenAI$111,482
Claude Opus 4.8Anthropic$101,482
Qwen3.8-MaxAlibaba Qwen$31,482
GPT-6.1 SolOpenAI$41,481
GLM-5.3Z.ai$2.151,481
MiMo-V2.6-ProXiaomi MiMo$0.541,480
Claude Sonnet 5.5Anthropic$41,477
GLM-5.3-FlashZ.ai$0.241,477
GPT-6 AstraOpenAI$201,476
DeepSeek-V4.1-FlashDeepSeek$0.521,476
GPT-5.4OpenAI$5.631,475
Gemini 3 Flash PreviewGoogle$1.131,473
Grok 4.20xAI$1.561,472
GPT-5.6 TerraOpenAI$4.501,467
Grok 4.5xAI$31,465
DeepSeek-V4-ProDeepSeek$1.981,465
Claude Sonnet 5Anthropic$41,462
GPT-6 SolOpenAI$41,458
Gemini 3.5 Flash-LiteGoogle$0.851,456
Grok 4.6xAI$31,455
GPT-5.6 LunaOpenAI$0.451,453
MiMo-V2.6-FlashXiaomi MiMo$0.181,448
Step 5 PreviewStepFun$1.431,448
Grok 4.3xAI$1.561,442
GPT-6 LunaOpenAI$0.201,441
Grok 4.7xAI$31,441
Mistral Large 4Mistral AI$1.051,432
Claude Haiku 5.5Anthropic$0.201,425
GPT-4.1OpenAI$3.501,415
Solar Pro 4Upstage$0.521,388
GPT-4.1 miniOpenAI$0.701,383
GPT-4.1 nanoOpenAI$0.181,322

Cost

What each costs

Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.

The same work, priced

For 10M input and 2M output tokens, Gemini 3.5 Flash-Lite costs 1.5 times as much as LongCat-2.5, at each provider's listed rates.

What Gemini 3.5 Flash-Lite and LongCat-2.5 cost for the same work, at the rates each provider lists.
  • 10M input and 2M output tokens

    Gemini 3.5 Flash-Lite costs 1.5× as much

    Gemini 3.5 Flash-Lite
    $8
    LongCat-2.5
    $5.40
  • The same, with 9M of the input tokens cached

    Gemini 3.5 Flash-Lite costs 2.0× as much

    Gemini 3.5 Flash-Lite
    $5.57
    LongCat-2.5
    $2.75
Workload or rateGemini 3.5 Flash-LiteLongCat-2.5
Example workloads
10M input and 2M output tokens$8$5.40 (better)
The same, with 9M of the input tokens cached$5.57$2.75 (better)
Other listed rates
1M input tokens, cached$0.03$0.006 (better)

Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.

Launch price $100, regular price $150

Book the cost audit

Verdict

When to choose each

Gemini 3.5 Flash-Lite

Where it leads

  • Accepts audio input

Best for

  • High-volume extraction, structured parsing, and cost-sensitive subagent trials

Watch out for

  • The represented prices are standard API rates; batch, flex, and priority consumption use different rates

LongCat-2.5

Where it leads

  • Lower price per 1M output tokens, $1.20 vs $2.50
  • Longer responses, up to 262,144 vs 65,536 output tokens
  • Cheaper cached input, $0.006 vs $0.03 per 1M tokens

Best for

  • Coding agents working through whole projects in Claude Code, Codex or similar harnesses
  • Visual coding and design work that mixes screenshots or screen recordings with code

Watch out for

  • The recorded rates are a limited-time discount: Meituan publishes no list price and no end date
  • API only: no weights had been published when this record was made
  • Released on 2 November 2026, so no independent benchmark score is recorded here yet

From benchmark to production

Building on Gemini 3.5 Flash-Lite or LongCat-2.5?

Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.

AI Model Cost AuditLaunch price $100, regular price $150What the audit includes

FAQ

Gemini 3.5 Flash-Lite vs LongCat-2.5 FAQ

Which is cheaper, Gemini 3.5 Flash-Lite or LongCat-2.5?

Both cost $0.30 per 1M input tokens. For 10M input and 2M output tokens, Gemini 3.5 Flash-Lite costs $8 and LongCat-2.5 $5.40 at standard rates.

Which is cheaper with prompt caching, Gemini 3.5 Flash-Lite or LongCat-2.5?

Gemini 3.5 Flash-Lite charges $0.03 per 1M cached input tokens, 90% below its standard input rate, and LongCat-2.5 $0.006, 98% below. With 9M of 10M input tokens cached and 2M output tokens, Gemini 3.5 Flash-Lite costs $5.57 and LongCat-2.5 $2.75.

Which has the larger context window, Gemini 3.5 Flash-Lite or LongCat-2.5?

Both accept 1,048,576 tokens of context. LongCat-2.5 returns up to 262,144 tokens per response, Gemini 3.5 Flash-Lite 65,536.

How do Gemini 3.5 Flash-Lite and LongCat-2.5 differ in features?

Gemini 3.5 Flash-Lite takes text, image, audio and video input; LongCat-2.5 takes text, image and video.

Production evaluation

Choosing between Gemini 3.5 Flash-Lite and LongCat-2.5?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty