What is the difference between Gemini 1.5 Pro and GLM 5.3?

Gemini 1.5 Pro is developed by Google AI while GLM 5.3 is developed by Zhipu AI. Gemini 1.5 Pro has a 1.0M token context window vs GLM 5.3's 1.3M. You can compare their actual outputs across 1 challenges on Rival to see how they differ in practice.

Which is better, Gemini 1.5 Pro or GLM 5.3?

It depends on your use case. Gemini 1.5 Pro and GLM 5.3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 1 challenges so you can judge which fits your needs best.

How much does Gemini 1.5 Pro cost compared to GLM 5.3?

Gemini 1.5 Pro costs $3.5/M input tokens and GLM 5.3 costs $0.6538/M input tokens. GLM 5.3 is $2.85/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare Gemini 1.5 Pro and GLM 5.3 on Rival?

This page shows a side-by-side comparison of Gemini 1.5 Pro and GLM 5.3 across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

Updated Aug 2026

Gemini 1.5 ProvsGLM 5.3

GLM 5.3 is cheaper than Gemini 1.5 Pro at $0.6538/M vs $3.5/M input tokens.

Gemini 1.5 Pro and GLM 5.3 compared across 1 shared prompts
Spec	Gemini 1.5 Pro	GLM 5.3
Input price	$3.5/M tokens	$0.6538/M tokens
Output price	$10.5/M tokens	$2.0548/M tokens
Context window	1.0M tokens	1.3M tokens
Weights	—	Open
Free API (OpenRouter)	No	No
Released	Feb 2024	Aug 2026

Our Verdict

Gemini 1.5 Pro

GLM 5.3

Not enough votes to call it. On the specs, nothing separates them.

GLM 5.3 costs 5.1x less per token.

Too close to call

API pricing

Cost per 1M tokens

Gemini 1.5 Pro

Input

$3.50

Output

$10.50

GLM 5.3

Input

$0.65

5.4× cheaper

Output

$2.05

5.1× cheaper

GLM 5.3 is cheaper on both: 5.4× input, 5.1× output.

Where to run it

30 hosts, cheapest first

Gemini 1.5 Pro

No hosts listed on OpenRouter.

GLM 5.330 hosts

HostInOutContextUptime

Baidu Qianfanfp8$0.65 in$2.05 out1M99.8% up Morph$0.71 in$2.24 out1M99.8% up Rekafp8$0.76 in$2.57 out262k99.4% up Sail Researchfp8$0.77 in$4.00 out1M99.9% up Novitafp8$0.78 in$2.46 out1M99.9% up io.netfp8$0.82 in$2.77 out262k99.7% up

24 more hosts

Phala$0.84 in$2.64 out1M99.5% up DeepInfrafp4$0.90 in$3.00 out1M98% up InferenceNetfp4$0.90 in$3.00 out1M98% up DigitalOcean$0.91 in$2.86 out1M99.8% up Inceptronfp4$1.04 in$3.39 out1M99.4% up GMI Cloudfp8$1.05 in$3.30 out1M99.5% up Makorafp4$1.05 in$4.20 out980k97.3% up SiliconFlowfp8$1.12 in$3.52 out1M99.7% up Alibaba Cloud$1.19 in$3.74 out1M100% up Decartfp4$1.19 in$3.74 out1M99.1% up Friendli$1.26 in$3.96 out1M100% up AkashMLfp8$1.30 in$4.40 out1M100% up AtlasCloudfp8$1.40 in$4.40 out1M99.4% up Basetenfp4$1.40 in$4.40 out1M99.7% up Cloudflare Workers AI$1.40 in$4.40 out1.3M99.8% up Crusoefp4$1.40 in$4.40 out1M98.3% up Fireworks$1.40 in$4.40 out1M99.5% up Mistralnvfp4$1.40 in$4.40 out1M99.7% up Modal$1.40 in$4.40 out1M99% up Parasailfp8$1.40 in$4.40 out1M99.1% up Together$1.40 in$4.40 out1M98.1% up Venice$1.40 in$4.40 out1M98.8% up Wafer$1.40 in$4.40 out1M99.9% up Z.aifp8$1.40 in$4.40 out1M99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

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Cost per 1M tokens

30 hosts, cheapest first

What we learned reading every model

Common questions

What is the difference between Gemini 1.5 Pro and GLM 5.3?

Which is better, Gemini 1.5 Pro or GLM 5.3?

How much does Gemini 1.5 Pro cost compared to GLM 5.3?

How can I compare Gemini 1.5 Pro and GLM 5.3 on Rival?

More comparisons

Against the newest arrivals

Same lab, same size, long tail

Model pages

Cost per 1M tokens

30 hosts, cheapest first

What we learned reading every model

Common questions

What is the difference between Gemini 1.5 Pro and GLM 5.3?

Which is better, Gemini 1.5 Pro or GLM 5.3?

How much does Gemini 1.5 Pro cost compared to GLM 5.3?

How can I compare Gemini 1.5 Pro and GLM 5.3 on Rival?

More comparisons

Against the newest arrivals

Same lab, same size, long tail

Model pages