GLM-5.3-Flash vs GLM-5V-Turbo

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
Z.ai · activeGLM-5.3-FlashVerified Sep 2, 2026
Z.ai · activeGLM-5V-TurboVerified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldGLM-5.3-FlashGLM-5V-Turbo
DeveloperZ.aiZ.ai
FamilyGlm 5 3 FlashGlm 5v
ModelGLM-5.3-FlashGLM-5V-Turbo
VersionGLM-5.3-FlashGLM-5V-Turbo
Lifecycleactiveactive
Released2026-09-02Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, DocumentText, Image, Video, Document
Output modalitiesTextText
Context window1,000,000200,000
Total parameters320,000,000,000Unknown
Active parameters18,000,000,000Unknown
LicenseMITUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Z.ai (Standard)Z.ai (Standard)
Capabilitiesagents, chat, computer-use, reasoning, structured_outputs, tools, visionagents, chat, computer-use, reasoning, tools, vision

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

GLM-5.3-Flash Capabilities

agentschatcomputer-usereasoningstructured outputstoolsvision
Input price$0.075
Output price$0.25
Serving providers2
Canonical IDzai-org/glm-5.3-flash

GLM-5V-Turbo Capabilities

agentschatcomputer-usereasoningtoolsvision
Input price
Output price
Serving providers1
Canonical IDzai-org/glm-5v-turbo

Internal Comparison Graph

Related Comparisons

All image comparisons →
APairBContext
vscross-developer peersimage, text
vscross-developer peersimage, text, video
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vscross-developer peersimage, text, video
vscross-developer peersimage, text, video
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vscross-developer peersimage, text
vscross-developer peersimage, text
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vsfamily variantsimage, text
vsfamily variantsimage, text
vscross-developer peerstext

Primary Evidence

Sources and Freshness

Questions

GLM-5.3-Flash vs GLM-5V-Turbo FAQs

Is GLM-5.3-Flash or GLM-5V-Turbo better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both GLM-5.3-Flash and GLM-5V-Turbo, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, GLM-5.3-Flash or GLM-5V-Turbo?+

Only GLM-5.3-Flash has a directly sourced input price: $0.075 per million tokens. Only GLM-5.3-Flash has a directly sourced output price: $0.25 per million tokens.

Which has a larger context window, GLM-5.3-Flash or GLM-5V-Turbo?+

GLM-5.3-Flash has the larger sourced context window. GLM-5.3-Flash supports 1,000,000 and GLM-5V-Turbo supports 200,000.

Which performs better in benchmarks, GLM-5.3-Flash or GLM-5V-Turbo?+

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

Can GLM-5.3-Flash or GLM-5V-Turbo be self-hosted?+

GLM-5.3-Flash is the only model in this pair currently marked as self-hostable. GLM-5.3-Flash is open weight; GLM-5V-Turbo is not marked open weight.

Can GLM-5.3-Flash and GLM-5V-Turbo understand images?+

GLM-5.3-Flash is documented with image input; GLM-5V-Turbo is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, GLM-5.3-Flash or GLM-5V-Turbo?+

Neither has a larger sourced maximum output. GLM-5.3-Flash is 131,072 and GLM-5V-Turbo is 131,072.

Do GLM-5.3-Flash and GLM-5V-Turbo support reasoning and tool use?+

GLM-5.3-Flash: reasoning, tool calling, and image input. GLM-5V-Turbo: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, GLM-5.3-Flash or GLM-5V-Turbo?+

GLM-5.3-Flash has 2 sourced provider routes; GLM-5V-Turbo has 1, so GLM-5.3-Flash has broader tracked availability.

Which offers better value, GLM-5.3-Flash or GLM-5V-Turbo?+

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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