Qwen3.8 2.4T A95B vs GLM 5V Turbo
qwen/qwen3.8-2.4t-a95b · z-ai/glm-5v-turbo
As of November 6, 2026, Qwen3.8 2.4T A95B is the cheaper API on UberLLM: $0.0021 per million input tokens and $0.0063 per million output, versus $0.6926 / $2.31 for GLM 5V Turbo, about 100% 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 Qwen3.8 2.4T A95B to cut cost; choose GLM 5V Turbo when its capabilities fit your task better.
Qwen3.8 2.4T A95B vs GLM 5V Turbo, side by side
| Spec | Qwen3.8 2.4T A95B | GLM 5V Turbo |
|---|---|---|
| Price · input / 1M | $0.0021 | $0.6926 |
| Price · output / 1M | $0.0063 | $2.31 |
| Context length | 1,000,000 | 200,000 |
| Max output tokens | 262,144 | 32,768 |
| Input modalities | text | text, image |
| Output modalities | text | text |
| Tools / functions | Yes | Yes |
| Vision (image input) | — | Yes |
| Reasoning | Yes | Yes |
| % off list | 99.9% off | 42.3% off |
Best prices on UberLLM right now. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated November 6, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?
Qwen3.8 2.4T A95B vs GLM 5V Turbo — FAQ
Is Qwen3.8 2.4T A95B or GLM 5V Turbo cheaper?
Qwen3.8 2.4T A95B is cheaper on a blended token mix, by about 100%. 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 Qwen3.8 2.4T A95B and GLM 5V Turbo?
Qwen3.8 2.4T A95B: $0.0021 in / $0.0063 out per 1M tokens. GLM 5V Turbo: $0.6926 in / $2.31 out per 1M tokens. That's roughly a 100% blended difference. Prices are live; UberLLM adds no fee.
Can I use both Qwen3.8 2.4T A95B and GLM 5V Turbo 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.