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Claude Opus 5 vs GLM 5.3

Market Position

LiveBench Quality Versus Estimated Output Cost

Full ranking →
Efficiency FrontierLiveBench overall · output estimate
Upper-left is better
xAIDeepSeekZ.aiMiniMaxOpenAIQwenGoogle DeepMindMoonshot AIAnthropic
LiveBench quality versus score-adjusted output costEach dot is a reviewed major-model configuration and is colored by developer. Higher means a better LiveBench overall score. Farther left means lower estimated output cost after adjusting by the score. A dotted line connects the non-dominated frontier observations. When models are selected, their sourced families remain prominent, unrelated observations retain their developer colors at lower opacity, and an orange ring identifies each selected model.$0.0050$0.010$0.020$0.050$0.100$0.200$0.5006873788287Grok Build 0.1GLM 5.3 FlashGPT-5.6 Luna (max)DeepSeek V4 Flash Vision ExpGPT-5.6 Sol (max)Score-adjusted output cost per LiveBench case (log) →LiveBench overall →
The dotted frontier connects measured, non-dominated major-model observations. With a selection, sourced families stay prominent, unrelated observations retain their developer colors at lower opacity, and orange rings mark the selected model or models. Family lines connect models only when their sourced family and generation match. Cost is estimated from published output tokens and the lowest current USD output rate; it excludes input, caching, batch discounts, and provider-specific benchmark execution details.

This current-market view appears only when both compared models are reviewed current models with publisher-reported LiveBench token accounting and current sourced USD output rates.

Model Markets Rankings

Intelligence, Cost, and Efficiency

All rankings →
RankingClaude Opus 5GLM-5.3
IntelligenceHigher is better · MM Intelligence v1.2#2 of 2294.1 scoreUnrankedNot in the 22-model eligible cohort
CostLower is better · Published-token output estimate#33 of 36$0.371 per LiveBench case#28 of 36$0.248 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.0#7 of 2256.8 scoreUnrankedNot in the 22-model eligible cohort

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

All benchmark results →
BenchmarkClaude Opus 5GLM-5.3
LMArena Agent Arenaagent-2026-08-31-011508720696 · outcome_score · leader11.61100% of row best · score · Claude Opus 5 (Max); 95% CI [9.58391463, 13.64552719]; sessions 17073; observations 2093237; rank 23.8293% of row best · score · GLM 5.3 (Max); 95% CI [3.01733683, 4.62585790]; sessions 41022; observations 2958163; rank 20
LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader1,504.96100% of row best · rating · claude-opus-5-max; 95% CI [1499.16488972, 1510.76500615]; votes 16839; rank 11,474.4998% of row best · rating · glm-5.3-max; 95% CI [1467.12172899, 1481.86064533]; votes 7401; rank 18
LiveBench2026-06-25 · overall · leader83.44100% of row best · percent · claude-opus-5-max-effort · 14,826 output tokens / case79.1595% of row best · percent · glm-5.3 · 62,090 output tokens / case
Overall ResultCounted from the protocol-matched rows above3 benchmark winsOverall lead0 benchmark wins

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

FieldAt a Glance
Anthropic · activeClaude Opus 5Verified Aug 28, 2026
Z.ai · activeGLM 5.3Verified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldClaude Opus 5GLM-5.3
DeveloperAnthropicZ.ai
FamilyClaude 5Glm 5 3
ModelClaude Opus 5GLM-5.3
VersionClaude Opus 5GLM-5.3
Lifecycleactiveactive
Released2026-07-24Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window1,000K1,000K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessAnthropic (Standard), Deepinfra (Standard), Openrouter (Standard)Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard)
Capabilitieschat, generation, reasoning, toolsagents, chat, reasoning, structured_outputs, tools

13 comparable fields · 7 material differences · Pair passes the primary-source comparison gate

Claude Opus 5 Capabilities

chatgenerationreasoningtools
Input price$5.00
Output price$25.00
Serving providers3
Canonical IDanthropic/claude-opus-5

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

All text comparisons →
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Primary Evidence

Sources and Freshness

Models overview | Claude Platform DocsAnthropic · observed Aug 28, 2026GLM-5.3 | Z.AI Developer DocumentZ.ai · observed Aug 29, 2026LMArena Agent Arena agent-2026-08-31-011508720696 score tableLMArena · observed Sep 4, 2026LMArena Text Arena text-2026-09-01-011508720696 score tableLMArena · observed Sep 4, 2026LiveBench 2026-06-25 score tableLiveBench · observed Sep 4, 2026LiveBench 2026-06-25 token accountingLiveBench · observed Sep 4, 2026

Questions

Claude Opus 5 vs GLM 5.3 FAQs

Is Claude Opus 5 or GLM 5.3 better for coding?+

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

Which is cheaper, Claude Opus 5 or GLM 5.3?+

Claude Opus 5 is $5.00 and GLM 5.3 is $1.20 per million tokens, so GLM 5.3 is cheaper on this metric. Claude Opus 5 is $25.00 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, Claude Opus 5 or GLM 5.3?+

Neither model has a larger sourced context window in this comparison. Claude Opus 5 is 1,000K and GLM 5.3 is 1,000K.

Which performs better in benchmarks, Claude Opus 5 or GLM 5.3?+

Claude Opus 5 leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.

Can Claude Opus 5 or GLM 5.3 be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Claude Opus 5 is not marked open weight; GLM 5.3 is not marked open weight.

Can Claude Opus 5 and GLM 5.3 understand images?+

Claude Opus 5 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, Claude Opus 5 or GLM 5.3?+

GLM 5.3 has the larger sourced maximum output: Claude Opus 5 supports 128K and GLM 5.3 supports 131K output tokens.

Do Claude Opus 5 and GLM 5.3 support reasoning and tool use?+

Claude Opus 5: 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, Claude Opus 5 or GLM 5.3?+

Claude Opus 5 has 3 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.

Which offers better value, Claude Opus 5 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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