Claude Opus 4.8 vs GLM 5.3
Benchmark Performance
Available Benchmarks
| Benchmark | Claude Opus 4.8 | GLM-5.3 |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,451.9898% of row best · rating · claude-opus-4-8; 95% CI [1447.69484580, 1456.25837678]; votes 49123; rank 38 | 1,474.49100% of row best · rating · glm-5.3-max; 95% CI [1467.12172899, 1481.86064533]; votes 7401; rank 18 |
| LiveBench2026-06-25 · overall · leader | 81.18100% of row best · percent · claude-opus-4-8-max-effort · 24,171 output tokens / case | 79.1597% of row best · percent · glm-5.3 · 62,090 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winTied overall | 1 benchmark winTied overall |
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 4.8 | GLM-5.3 |
|---|---|---|
| Developer | Anthropic | Z.ai |
| Family | Claude 4 8 | Glm 5 3 |
| Model | Claude Opus 4.8 | GLM-5.3 |
| Version | Claude Opus 4.8 | GLM-5.3 |
| 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 | 1,000K |
| 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, tools | agents, chat, reasoning, structured_outputs, tools |
13 comparable fields · 7 material differences · Pair passes the primary-source comparison gate
Claude Opus 4.8 Capabilities
GLM 5.3 Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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Claude Opus 4.8Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
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Claude Opus 4.8Anthropic | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Claude Opus 4.8Anthropic | cross-developer peersimage, text |
Claude Opus 4.8Anthropic | vs |  Hy4 previewTencent | cross-developer peerstext |
Claude Opus 4.8Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Opus 4.8Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Claude Opus 4.8Anthropic | vs | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.8 vs GLM 5.3 FAQs
Is Claude Opus 4.8 or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.8 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 4.8 or GLM 5.3?+
Claude Opus 4.8 is $5.00 and GLM 5.3 is $1.20 per million tokens, so GLM 5.3 is cheaper on this metric. Claude Opus 4.8 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 4.8 or GLM 5.3?+
Neither model has a larger sourced context window in this comparison. Claude Opus 4.8 is 1,000K and GLM 5.3 is 1,000K.
Which performs better in benchmarks, Claude Opus 4.8 or GLM 5.3?+
There is no overall benchmark winner: The verified common benchmarks do not produce a majority winner.
Can Claude Opus 4.8 or GLM 5.3 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Opus 4.8 is not marked open weight; GLM 5.3 is not marked open weight.
Can Claude Opus 4.8 and GLM 5.3 understand images?+
Claude Opus 4.8 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 4.8 or GLM 5.3?+
GLM 5.3 has the larger sourced maximum output: Claude Opus 4.8 supports 128K and GLM 5.3 supports 131K output tokens.
Do Claude Opus 4.8 and GLM 5.3 support reasoning and tool use?+
Claude Opus 4.8: 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 4.8 or GLM 5.3?+
Claude Opus 4.8 has 2 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, Claude Opus 4.8 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.