Claude Haiku 5.5 vs GLM 5.3
anthropic/claude-haiku-5.5 · z-ai/glm-5.3
As of November 1, 2026, GLM 5.3 is the cheaper API on UberLLM: $0.0008 per million input tokens and $0.0140 per million output, versus $0.0069 / $0.0347 for Claude Haiku 5.5, about 61% less when output is 3 tokens for every input token. These are the best prices on the market right now. Both work with one OpenAI-compatible key and UberLLM adds no fee. Choose GLM 5.3 to cut cost; choose Claude Haiku 5.5 when its capabilities fit your task better.
Claude Haiku 5.5 vs GLM 5.3, side by side
| Spec | Claude Haiku 5.5 | GLM 5.3 |
|---|---|---|
| Price · input / 1M | $0.0069 | $0.0008 |
| Price · output / 1M | $0.0347 | $0.0140 |
| Context length | 1,000,000 | 1,000,000 |
| Max output tokens | 128,000 | 131,072 |
| Input modalities | text, image, file | text |
| Output modalities | text | text |
| Tools / functions | Yes | Yes |
| Vision (image input) | Yes | — |
| Reasoning | Yes | Yes |
| % off list | 93.1% off | 99% off |
| First token, median (7 days) | — | 3.6 s (426 requests) |
Best prices on UberLLM right now. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated November 1, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?
Claude Haiku 5.5 vs GLM 5.3 — FAQ
Is Claude Haiku 5.5 or GLM 5.3 cheaper?
GLM 5.3 is cheaper on a blended token mix, by about 61%. A request costs what its provider charged, UberLLM adds no fee, and every request is listed with its cost in Activity.
What's the price difference between Claude Haiku 5.5 and GLM 5.3?
Claude Haiku 5.5: $0.0069 in / $0.0347 out per 1M tokens. GLM 5.3: $0.0008 in / $0.0140 out per 1M tokens. That's roughly a 61% blended difference. Prices are live; UberLLM adds no fee.
Can I use both Claude Haiku 5.5 and GLM 5.3 with one API?
Yes. Both are served through a single OpenAI-compatible endpoint — set the base URL to https://api.uberllm.dev/v1 and your UberLLM key, then switch between them by changing the model id. Anthropic SDKs work via https://api.uberllm.dev/v1/messages.