Kimi K3 vs GLM 4.5
moonshotai/kimi-k3 · z-ai/glm-4.5
As of November 5, 2026, GLM 4.5 is the cheaper API on UberLLM: $0.0059 per million input tokens and $0.0216 per million output, versus $0.0154 / $1.28 for Kimi K3, about 98% 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 4.5 to cut cost; choose Kimi K3 when context size wins. Kimi K3 carries the larger context window (1,000,000 vs 128,000 tokens), which can matter for long-document work.
Kimi K3 vs GLM 4.5, side by side
| Spec | Kimi K3 | GLM 4.5 |
|---|---|---|
| Price · input / 1M | $0.0154 | $0.0059 |
| Price · output / 1M | $1.28 | $0.0216 |
| Context length | 1,000,000 | 128,000 |
| Max output tokens | 131,072 | 32,768 |
| Input modalities | text, image | text |
| Output modalities | text | text |
| Tools / functions | Yes | Yes |
| Vision (image input) | Yes | — |
| Reasoning | Yes | Yes |
| % off list | 92% off | 99% off |
| First token, median (7 days) | 4.6 s (2,605 requests) | — |
Best prices on UberLLM right now. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated November 5, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?
Kimi K3 vs GLM 4.5 — FAQ
Is Kimi K3 or GLM 4.5 cheaper?
GLM 4.5 is cheaper on a blended token mix, by about 98%. 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 Kimi K3 and GLM 4.5?
Kimi K3: $0.0154 in / $1.28 out per 1M tokens. GLM 4.5: $0.0059 in / $0.0216 out per 1M tokens. That's roughly a 98% blended difference. Prices are live; UberLLM adds no fee.
Can I use both Kimi K3 and GLM 4.5 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.