Custom Comparison
Compare 2 AI Models
GLM-5.3-Flash vs Claude Opus 4.8
GLM-5.3-FlashZhipu AI
Claude Opus 4.8Anthropic
Up to 3 models. Every selection is in the address bar, so the comparison is a link you can send.
Interactive Comparison
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$0.15 / $0.50 per million tokens | $5 / $25 per million tokens | |
|---|---|---|
| Identity | ||
| Developer | Zhipu AI | Anthropic |
| Released | Aug 2026 | May 2026 |
| Status | GA | Available (legacy) |
| Licence | MIT (weights on Hugging Face, zai-org/GLM-5.3-Flash) | Proprietary |
| Self-hostable | Yes - MIT weights published at launch | No |
| Cost | ||
| Blended $/1M tokensinput × 0.75 + output × 0.25 | $0.237 / 1M tokens | $10.000 / 1M tokens |
| Input price | $0.150 / 1M tokens | $5.000 / 1M tokens |
| Output price | $0.500 / 1M tokens | $25.000 / 1M tokens |
| Cached input | 0.03 | $0.50 / 1M tokens (cache hit) |
| Batch discount | Not offered; GLM Coding Plan applies a 50% off-peak points reduction | 50% off input/output (Batch API) |
| Free tier | Not offered; included in the GLM Coding Plan at 3x the GLM-5.3 quota | Small trial credit for new accounts, no ongoing free tier |
| Capacity | ||
| Context window | 1M tokens | 1M tokens |
| Max output | 128k tokens | 128k tokens |
| Long-context surcharge | Not published | None (full 1M window at standard pricing) |
| Capability | ||
| Vision in | Yes - text, image, video and file input | Yes |
| Audio in | Not documented | No |
| Function calling | Yes | Yes |
| Structured output | Yes | Yes |
| Extended reasoning | Yes - thinking mode | No (adaptive thinking) |
| Web search | Not documented | Yes |
| Code execution | Not documented | Yes |
| Access | ||
| API | Yes | Yes |
| Chat app | Yes | Yes |
| Cloud marketplaces | Not documented | AWS Bedrock, Google Cloud, Microsoft Foundry |
| Fine-tuning | Not offered | No |
| Measured quality | ||
| LMArena Elo | 1474 (checked Oct 2026) | 1474 (checked Oct 2026) |
| LMArena rank | Rank 41 | Rank 40 |
| GPQA Diamond | 90 · max effort | — |
| Elo per dollarLMArena Elo ÷ blended $/1M tokens | 6206 | 147 |
