Gemini 3.5 Flash-LitevsGLM-5.3-Flash

Both language models, compared at each maker’s own API list prices. Every figure links to its source.

Compare at your usage

Every model priced for the same request
Prompt per request
Cache hits
Batch
Service tier

8,000 tokens in, 2,000 out

Gemini 3.5 Flash-Lite on Gemini APIGLM-5.3-Flash on Z.ai API
Rate appliedBase rateBase rate
Inputper 1M tokens$0.30 $0.15
Cache readper 1M tokens$0.030 $0.030
Outputper 1M tokens$2.50 $0.50
Cost per request$0.0074$0.0022
Per 1,000 requests$7.40$2.20

Every model is priced for the same request at its maker’s own list prices (each with its source and date), so bold marks the cheapest. A model that can’t serve the request is named, not ranked; a condition its seller doesn’t price says which rate was used.

Cost per request as prompts grow

2K tokens out, list price on each maker’s API.

0$0.10$0.20$0.300250K500K750K1Mprompt tokens per request8KGemini 3.5 Flash-Lite$0.0074 at 8KGLM-5.3-Flash$0.0022 at 8K
  • Gemini 3.5 Flash-Lite · Gemini API
  • GLM-5.3-Flash · Z.ai API

Where each stands among all scored models

Each line runs from the lowest to the highest score on the board; the tick is the median.

Epoch Capabilities Index#77 vs #49 of 118GLM-5.3-Flash: 153.6Gemini 3.5 Flash-Lite: 145.6LMArena Text#47 vs #27 of 163GLM-5.3-Flash: 1,477Gemini 3.5 Flash-Lite: 1,456LMArena Text · Coding#50 vs #22 of 163GLM-5.3-Flash: 1,526Gemini 3.5 Flash-Lite: 1,502LMArena Vision#33 vs #18 of 89GLM-5.3-Flash: 1,294Gemini 3.5 Flash-Lite: 1,269
  • Gemini 3.5 Flash-Lite
  • GLM-5.3-Flash

Key differences

OutputMaker’s official API · global · USD
$2.50 / 1M tokens Gemini API pricing · as of Nov 3, 2026
$0.50 / 1M tokens Pricing · as of Nov 1, 2026
Context
1,048,576 Gemini 3.5 Flash Lite model · as of Nov 1, 2026
1,000,000 GLM-5.3-Flash/FlashX · as of Nov 1, 2026
Max output
65,536 Gemini 3.5 Flash Lite model · as of Nov 1, 2026
128,000 GLM-5.3-Flash/FlashX · as of Nov 1, 2026
Input modalities
Text, Image, Video, Audio, PDF Gemini 3.5 Flash Lite model · as of Nov 1, 2026
Text, Image, Video GLM-5.3-Flash/FlashX · as of Nov 1, 2026

These differences use verified vendor specifications or each maker’s official API on the same region, currency, meter and billing conditions. Different conditions remain side by side in the full table; they do not establish which model is cheaper. Declared features describe support, not measured quality or a recommendation. Missing evidence does not mean a feature is unsupported.

Full comparison

Gemini 3.5 Flash-Lite Google GLM-5.3-Flash Zhipu AI
Overview
ReleasedJul 21, 2026 Aug 26, 2026
Open weights— Yes
Knowledge cutoffMar 2026 Not stated
Specs
Context1.05M 1M
Max input1M Not stated
Max output65.54K 128K
Input modalitiesText, Image, Video, Audio, PDF Text, Image, Video
Output modalitiesText Text
ReasoningYes Yes
Reasoning effortsminimal, low, medium, high low, high, max
Reasoning can be offNot stated —
Tool useYes Yes
Structured outputYes Yes
Built-in toolsWeb search, Web fetch, Code execution, Computer use, Maps Not stated
Pricing · per 1M tokens
Input price$0.30Also priced under other conditions: Image tokens, Video tokens, Audio tokens, Batch, Flex tier, Priority tier $0.15
Output price$2.50Also priced under other conditions: Batch, Flex tier, Priority tier $0.50
Cache read price$0.030Also priced under other conditions: Batch, Flex tier, Priority tier $0.030
Blended price (3 input : 1 output)$0.85 $0.2375
Pricing under conditions · per 1M tokens
Batch input price$0.15Batch Not offered
Batch output price$1.25Batch Not offered
Flex tier input price$0.15Flex tier Not offered
Flex tier output price$1.25Flex tier Not offered
Priority tier input price$0.54Priority tier Not offered
Priority tier output price$4.50Priority tier Not offered
Cited scores
Epoch Capabilities Index145.6 153.6
LMArena Text1,456 1,477
LMArena Text · Coding1,502 1,526
LMArena Vision1,269 1,294
LMArena Text · Chinese1,483 1,530
Epoch AI · GPQA Diamond83.3% high effort90.2% max effort
Epoch AI · FrontierMath Tiers 1–326% high effort55.8% max effort

Headline prices may come from different channels, regions or tiers. Check each source before choosing a model; missing facts stay blank.

Model details and sources

Cited scores