Claude Opus 4.7 vs GLM 5.3
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| IntelligenceHigher is better · MM Intelligence v1.2 | #6 of 2278.9 score | UnrankedNot in the 22-model eligible cohort |
| CostLower is better · Published-token output estimate | #31 of 36$0.286 per LiveBench case | #28 of 36$0.248 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.0 | #12 of 2251.8 score | UnrankedNot 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
| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| LMArena Agent Arenaagent-2026-08-31-011508720696 · outcome_score · leader | 6.33100% of row best · score · Claude Opus 4.7; 95% CI [4.91001873, 7.74575053]; sessions 37121; observations 1470793; rank 10 | 3.8298% 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 · statistical tie | 1,483.21100% of row best · rating · claude-opus-4-7; 95% CI [1479.33960820, 1487.07067536]; votes 61256; rank 10 | 1,474.4999% of row best · rating · glm-5.3-max; 95% CI [1467.12172899, 1481.86064533]; votes 7401; rank 18 |
| LiveBench2026-06-25 · overall · leader | 80.97100% of row best · percent · claude-opus-4-7-xhigh-effort · 11,460 output tokens / case | 79.1598% of row best · percent · glm-5.3 · 62,090 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 2 benchmark winsOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| Developer | Anthropic | Z.ai |
| Family | Claude 4 | Glm 5 3 |
| Model | Claude Opus 4.7 | GLM-5.3 |
| Version | Claude Opus 4.7 | GLM-5.3 |
| Lifecycle | active | active |
| Released | 2026-04-16 | Unknown |
| Knowledge cutoff | 2026-01-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,000K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Anthropic (Standard), Deepinfra (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | agents, chat, reasoning, structured_outputs, tools |
13 comparable fields · 7 material differences · Pair passes the primary-source comparison gate
Claude Opus 4.7 Capabilities
GLM 5.3 Capabilities
Internal Comparison Graph
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|---|---|---|---|
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Claude Opus 4.7Anthropic | vs | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.7 vs GLM 5.3 FAQs
Is Claude Opus 4.7 or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.7 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 4.7 or GLM 5.3?+
Claude Opus 4.7 is $5.00 and GLM 5.3 is $1.20 per million tokens, so GLM 5.3 is cheaper on this metric. Claude Opus 4.7 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 4.7 or GLM 5.3?+
Neither model has a larger sourced context window in this comparison. Claude Opus 4.7 is 1,000K and GLM 5.3 is 1,000K.
Which performs better in benchmarks, Claude Opus 4.7 or GLM 5.3?+
Claude Opus 4.7 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 4.7 or GLM 5.3 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Opus 4.7 is not marked open weight; GLM 5.3 is not marked open weight.
Can Claude Opus 4.7 and GLM 5.3 understand images?+
Claude Opus 4.7 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 4.7 or GLM 5.3?+
GLM 5.3 has the larger sourced maximum output: Claude Opus 4.7 supports 128K and GLM 5.3 supports 131K output tokens.
Do Claude Opus 4.7 and GLM 5.3 support reasoning and tool use?+
Claude Opus 4.7: 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 4.7 or GLM 5.3?+
Claude Opus 4.7 has 2 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, Claude Opus 4.7 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.