Claude Opus 4.6 vs GLM OCR

At a Glance

Compare
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#12 of 4676.2 score · 3/3 sources · completeUnrankedNot in the 46-model eligible cohort
CostLower is better · Published-token output estimate#33 of 44$0.241 per LiveBench caseUnrankedNot in the 44-model eligible cohort
EfficiencyHigher is better · MM Efficiency v1.5#19 of 3853.2 score · 3/3 sources · completeUnrankedNot in the 38-model eligible cohort
Pricing and Limits
Input priceFrom · USD / 1M tokens$5.00Anthropic · Sep 3, 2026Not reported
Output priceFrom · USD / 1M tokens$25.00Anthropic · Sep 3, 2026Not reported
Context windowMaximum documented tokens1,000K131K
Model facts checkedSep 3, 2026View model evidence →Aug 28, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldClaude Opus 4.6GLM-OCR
DeveloperAnthropicZ.ai
FamilyClaude 4Glm OCR
ModelClaude Opus 4.6GLM-OCR
VersionClaude Opus 4.6GLM-OCR
Lifecycleactiveactive
Released2026-02-05Unknown
Knowledge cutoff2025-05-01Unknown
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window1,000K131K
Total parametersUnknown1.3B
Active parametersUnknownUnknown
LicenseUnknownmit
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessAnthropic (Standard)Together Ai (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolschat, generation, tools

Claude Opus 4.6 Capabilities

chatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDanthropic/claude-opus-4-6

GLM OCR Capabilities

chatgenerationtools
Serving providers1
Canonical IDzai-org/GLM-OCR

Primary Evidence

Sources and Freshness

Questions

Claude Opus 4.6 vs GLM OCR FAQs

Is Claude Opus 4.6 or GLM OCR better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.6 and GLM OCR, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Claude Opus 4.6 or GLM OCR?+

Only Claude Opus 4.6 has a directly sourced input price: $5.00 per million tokens. Only Claude Opus 4.6 has a directly sourced output price: $25.00 per million tokens.

Which has a larger context window, Claude Opus 4.6 or GLM OCR?+

Claude Opus 4.6 has the larger sourced context window. Claude Opus 4.6 supports 1,000K and GLM OCR supports 131K.

Which performs better in benchmarks, Claude Opus 4.6 or GLM OCR?+

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

Can Claude Opus 4.6 or GLM OCR be self-hosted?+

GLM OCR is the only model in this pair currently marked as self-hostable. Claude Opus 4.6 is not marked open weight; GLM OCR is open weight.

Can Claude Opus 4.6 and GLM OCR understand images?+

Claude Opus 4.6 is documented with image input; GLM OCR is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Claude Opus 4.6 or GLM OCR?+

Neither has a larger sourced maximum output. Claude Opus 4.6 is 128K and GLM OCR is —.

Do Claude Opus 4.6 and GLM OCR support reasoning and tool use?+

Claude Opus 4.6: reasoning, tool calling, and image input. GLM OCR: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Claude Opus 4.6 or GLM OCR?+

Claude Opus 4.6 has 1 sourced provider route; GLM OCR has 1, a tie.

Which offers better value, Claude Opus 4.6 or GLM OCR?+

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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