GPT-5.5 Pro vs GLM 5.3

Model Markets Rankings

Intelligence, Cost, and Efficiency

All rankings →
RankingGPT-5.5 ProGLM-5.3
CostLower is better · Published-token output estimateUnrankedNot in the 36-model eligible cohort#28 of 36$0.248 per LiveBench case

Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.

Benchmark Performance

Available Benchmarks

No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
FieldAt a Glance
OpenAI · activeGPT-5.5 ProVerified Sep 3, 2026
Z.ai · activeGLM 5.3Verified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldGPT-5.5 ProGLM-5.3
DeveloperOpenAIZ.ai
FamilyGpt 5 5Glm 5 3
ModelGPT-5.5 ProGLM-5.3
VersionGPT-5.5 ProGLM-5.3
Lifecycleactiveactive
Released2026-04-23Unknown
Knowledge cutoff2025-12-01Unknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window1,050K1,000K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessOpenai (Standard), Openrouter (Standard)Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolsagents, chat, reasoning, structured_outputs, tools

13 comparable fields · 8 material differences · Pair passes the primary-source comparison gate

GPT-5.5 Pro Capabilities

chatgenerationreasoningstructured outputstools
Input price$30.00
Output price$180.00
Serving providers2
Canonical IDopenai/gpt-5.5-pro

GLM 5.3 Capabilities

agentschatreasoningstructured outputstools
Input price$1.20
Output price$4.00
Serving providers4
Canonical IDzai-org/glm-5.3

Internal Comparison Graph

Related Comparisons

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Primary Evidence

Sources and Freshness

Questions

GPT-5.5 Pro vs GLM 5.3 FAQs

Is GPT-5.5 Pro or GLM 5.3 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5.5 Pro and GLM 5.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, GPT-5.5 Pro or GLM 5.3?+

GPT-5.5 Pro is $30.00 and GLM 5.3 is $1.20 per million tokens, so GLM 5.3 is cheaper on this metric. GPT-5.5 Pro is $180.00 and GLM 5.3 is $4.00 per million tokens, so GLM 5.3 is cheaper on this metric.

Which has a larger context window, GPT-5.5 Pro or GLM 5.3?+

GPT-5.5 Pro has the larger sourced context window. GPT-5.5 Pro supports 1,050K and GLM 5.3 supports 1,000K.

Which performs better in benchmarks, GPT-5.5 Pro or GLM 5.3?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can GPT-5.5 Pro or GLM 5.3 be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. GPT-5.5 Pro is not marked open weight; GLM 5.3 is not marked open weight.

Can GPT-5.5 Pro and GLM 5.3 understand images?+

GPT-5.5 Pro is documented with image input; GLM 5.3 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, GPT-5.5 Pro or GLM 5.3?+

GLM 5.3 has the larger sourced maximum output: GPT-5.5 Pro supports 128K and GLM 5.3 supports 131K output tokens.

Do GPT-5.5 Pro and GLM 5.3 support reasoning and tool use?+

GPT-5.5 Pro: reasoning, tool calling, and image input. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, GPT-5.5 Pro or GLM 5.3?+

GPT-5.5 Pro has 2 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.

Which offers better value, GPT-5.5 Pro or GLM 5.3?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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