Qwen3.8-Max 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
Qwen · activeQwen3.8-MaxVerified Aug 29, 2026
Z.ai · activeGLM-5V-TurboVerified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldQwen3.8-MaxGLM-5V-Turbo
DeveloperQwenZ.ai
FamilyQwen3 8 MaxGlm 5v
ModelQwen3.8-MaxGLM-5V-Turbo
VersionQwen3.8-MaxGLM-5V-Turbo
Lifecycleactiveactive
ReleasedUnknownUnknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, VideoText, Image, Video, Document
Output modalitiesTextText
Context window1,000,000200,000
Total parameters2,400,000,000,000Unknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessAlibaba Cloud Model Studio (Standard), Deepinfra (Standard), Openrouter (Standard)Z.ai (Standard)
Capabilitiesagents, chat, reasoning, structured_outputs, tools, visionagents, chat, computer-use, reasoning, tools, vision

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

Qwen3.8-Max Capabilities

agentschatreasoningstructured outputstoolsvision
Input price$1.65
Output price$4.951
Serving providers3
Canonical IDqwen/qwen3.8-max

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
vsfamily variantsimage, text, video
vsfamily variantsimage, text, video
vsfamily variantsimage, text, video
vscross-developer peersimage, text, video
vscross-developer peersimage, text, video
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text
vsfamily variantsimage, text
vscross-developer peersimage, text
vscross-developer peerstext
vscross-developer peerstext

Primary Evidence

Sources and Freshness

Questions

Qwen3.8-Max vs GLM-5V-Turbo FAQs

Is Qwen3.8-Max or GLM-5V-Turbo better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8-Max and GLM-5V-Turbo, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.8-Max or GLM-5V-Turbo?+

Only Qwen3.8-Max has a directly sourced input price: $1.65 per million tokens. Only Qwen3.8-Max has a directly sourced output price: $4.951 per million tokens.

Which has a larger context window, Qwen3.8-Max or GLM-5V-Turbo?+

Qwen3.8-Max has the larger sourced context window. Qwen3.8-Max supports 1,000,000 and GLM-5V-Turbo supports 200,000.

Which performs better in benchmarks, Qwen3.8-Max 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 Qwen3.8-Max or GLM-5V-Turbo be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Qwen3.8-Max is not marked open weight; GLM-5V-Turbo is not marked open weight.

Can Qwen3.8-Max and GLM-5V-Turbo understand images?+

Qwen3.8-Max 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, Qwen3.8-Max or GLM-5V-Turbo?+

Neither has a larger sourced maximum output. Qwen3.8-Max is 131,072 and GLM-5V-Turbo is 131,072.

Do Qwen3.8-Max and GLM-5V-Turbo support reasoning and tool use?+

Qwen3.8-Max: 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, Qwen3.8-Max or GLM-5V-Turbo?+

Qwen3.8-Max has 3 sourced provider routes; GLM-5V-Turbo has 1, so Qwen3.8-Max has broader tracked availability.

Which offers better value, Qwen3.8-Max 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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