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GPT-6 Luna vs Qwen3.8 2.4T A95B

openai/gpt-6-luna · qwen/qwen3.8-2.4t-a95b

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 $0.0028 / $0.0141 for GPT-6 Luna, about 54% 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 GPT-6 Luna when context size wins. GPT-6 Luna carries the larger context window (1,050,000 vs 1,000,000 tokens), which can matter for long-document work.

GPT-6 Luna vs Qwen3.8 2.4T A95B, side by side

SpecGPT-6 LunaQwen3.8 2.4T A95B
Price · input / 1M$0.0028$0.0021
Price · output / 1M$0.0141$0.0063
Context length1,050,0001,000,000
Max output tokens128,000262,144
Input modalitiestext, image, filetext
Output modalitiestexttext
Tools / functionsYesYes
Vision (image input)Yes—
ReasoningYesYes
% off list97.2% off99.9% 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?

GPT-6 Luna vs Qwen3.8 2.4T A95B — FAQ

Is GPT-6 Luna or Qwen3.8 2.4T A95B cheaper?

Qwen3.8 2.4T A95B is cheaper on a blended token mix, by about 54%. 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 GPT-6 Luna and Qwen3.8 2.4T A95B?

GPT-6 Luna: $0.0028 in / $0.0141 out per 1M tokens. Qwen3.8 2.4T A95B: $0.0021 in / $0.0063 out per 1M tokens. That's roughly a 54% blended difference. Prices are live; UberLLM adds no fee.

Can I use both GPT-6 Luna and Qwen3.8 2.4T A95B 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.

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