Claude Opus 4.8 vs GLM 5.2
At a Glance
| Compare | Claude Opus 4.8Anthropic |  GLM 5.2Z.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #18 of 4670.1 score · 3/3 sources · complete | #23 of 4661.9 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 41.3–74.6 |
| CostLower is better · Published-token output estimate | #42 of 44$0.604 per LiveBench case | #12 of 44$0.056 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #35 of 3840.5 score · 3/3 sources · complete | #7 of 3861.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 51.0–67.6 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | $0.75Deepinfra ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $25.00Anthropic ↗ · Sep 3, 2026 | $2.40Deepinfra ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 1,000K | 1,049K |
| Model facts checked | Aug 29, 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
| Benchmark | Claude Opus 4.8 | GLM-5.2 |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | 8.19100% of row best · score · Claude Opus 4.8 (High); 95% CI [6.91963673, 9.45737628]; sessions 39731; observations 2097389; rank 6 | 4.3796% of row best · score · GLM 5.2 (Max); 95% CI [3.67608698, 5.05982987]; sessions 76766; observations 4943866; rank 14 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,452.6699% of row best · rating · claude-opus-4-8; 95% CI [1448.52490690, 1456.79817098]; votes 53446; rank 40 | 1,466.93100% of row best · rating · glm-5.2-max; 95% CI [1462.35303996, 1471.51268346]; votes 36798; rank 29 |
| LiveBench2026-06-25 · overall · leader | 81.18100% of row best · percent · claude-opus-4-8-max-effort · 24,171 output tokens / case | 76.9695% of row best · percent · glm-5.2 · 23,463 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 87.91100% of row best · points · Claude Opus 4.8 (max effort) · 24,846 output tokens / case | 82.1493% of row best · points · GLM-5.2 · 5,633 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 2 benchmark winsOverall lead | 1 benchmark win |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Opus 4.8 | GLM-5.2 |
|---|---|---|
| Developer | Anthropic | Z.ai |
| Family | Claude 4 8 | Glm 5 2 |
| Model | Claude Opus 4.8 | GLM-5.2 |
| Version | Claude Opus 4.8 | GLM-5.2 |
| Lifecycle | active | active |
| Released | 2026-05-28 | Unknown |
| Knowledge cutoff | 2026-01-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,049K |
| Total parameters | Unknown | 753.3B |
| Active parameters | Unknown | Unknown |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard), Deepinfra (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
Claude Opus 4.8 Capabilities
GLM 5.2 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.8 vs GLM 5.2 FAQs
Is Claude Opus 4.8 or GLM 5.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.8 and GLM 5.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 4.8 or GLM 5.2?+
Claude Opus 4.8 is $5.00 and GLM 5.2 is $0.75 per million tokens, so GLM 5.2 is cheaper on this metric. Claude Opus 4.8 is $25.00 and GLM 5.2 is $2.40 per million tokens, so GLM 5.2 is cheaper on this metric.
Which has a larger context window, Claude Opus 4.8 or GLM 5.2?+
GLM 5.2 has the larger sourced context window. Claude Opus 4.8 supports 1,000K and GLM 5.2 supports 1,049K.
Which performs better in benchmarks, Claude Opus 4.8 or GLM 5.2?+
Claude Opus 4.8 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 4.8 or GLM 5.2 be self-hosted?+
GLM 5.2 is the only model in this pair currently marked as self-hostable. Claude Opus 4.8 is not marked open weight; GLM 5.2 is open weight.
Can Claude Opus 4.8 and GLM 5.2 understand images?+
Claude Opus 4.8 is documented with image input; GLM 5.2 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 4.8 or GLM 5.2?+
Neither has a larger sourced maximum output. Claude Opus 4.8 is 128K and GLM 5.2 is —.
Do Claude Opus 4.8 and GLM 5.2 support reasoning and tool use?+
Claude Opus 4.8: reasoning, tool calling, and image input. GLM 5.2: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 4.8 or GLM 5.2?+
Claude Opus 4.8 has 2 sourced provider routes; GLM 5.2 has 5, so GLM 5.2 has broader tracked availability.
Which offers better value, Claude Opus 4.8 or GLM 5.2?+
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.