Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
Workload (per month)
Google: Gemini 2.5 Pro
Qwen: Qwen3.8 Max (0902)
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$294
$270
Qwen: Qwen3.8 Max (0902) saves $23.75
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$250
$300
Google: Gemini 2.5 Pro saves $50.00
Coding / tool-using agent
2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens)
$270
$312
Google: Gemini 2.5 Pro saves $42.00
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$160
$196
Google: Gemini 2.5 Pro saves $36.00
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$72.50
$106
Google: Gemini 2.5 Pro saves $33.50
Capabilities side by side
Capability
Google: Gemini 2.5 Pro
Qwen: Qwen3.8 Max (0902)
What it lets you do
Tool / function calling
✓ Yes
✓ Yes
call your APIs and run agent loops
Structured output (JSON schema)
✓ Yes
✓ Yes
return JSON that validates against your schema
Reasoning / thinking mode
✓ Yes
✓ Yes
spend extra tokens thinking before answering hard problems
Image input
✓ Yes
✓ Yes
read screenshots, charts and scanned pages
Audio input
✓ Yes
—
take speech or audio directly
File / PDF input
✓ Yes
—
accept documents without your own parsing step
Image output
—
—
generate images, not just text
Built-in web search
✓ Yes
—
answer from live web results
Seed (reproducible sampling)
✓ Yes
✓ Yes
repeat a generation for tests and evals
Log-probabilities
—
✓ Yes
read token confidence for classification and scoring
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
Google: Gemini 2.5 Pro: price unchanged since we started tracking it on 2026-03-10.
Qwen: Qwen3.8 Max (0902): price unchanged since we started tracking it on 2026-09-06.
Which should you choose?
Choose Google: Gemini 2.5 Pro if…
you need audio input — to take speech or audio directly; Qwen: Qwen3.8 Max (0902) does not advertise it
you need file / PDF input — to accept documents without your own parsing step; Qwen: Qwen3.8 Max (0902) does not advertise it
you need built-in web search — to answer from live web results; Qwen: Qwen3.8 Max (0902) does not advertise it
Choose Qwen: Qwen3.8 Max (0902) if…
cost matters at scale — it is 13% cheaper on a typical 3:1 input/output mix ($270 vs $294 a month for 50,000 support chats)
you need log-probabilities — to read token confidence for classification and scoring; Google: Gemini 2.5 Pro does not advertise it
you generate long outputs in one go — up to 131K tokens (about 98,300 words) per response
you want the newer model — released 2026-09-03, 15 months after the other
Frequently asked questions
Is Google: Gemini 2.5 Pro better than Qwen: Qwen3.8 Max (0902)?
Neither wins outright: Google: Gemini 2.5 Pro is the pick when you need audio input, Qwen: Qwen3.8 Max (0902) when cost matters at scale. In short: Google: Gemini 2.5 Pro when you need audio input, you need file / PDF input, you need built-in web search; Qwen: Qwen3.8 Max (0902) when cost matters at scale, you need log-probabilities, you generate long outputs in one go, you want the newer model.
Which is cheaper, Google: Gemini 2.5 Pro or Qwen: Qwen3.8 Max (0902)?
Qwen: Qwen3.8 Max (0902) is cheaper: $3.00 vs $3.44 per 1M tokens at a typical 3:1 input/output mix, 13% less. For 50,000 support conversations a month that is $270 against $294.
How much do Google: Gemini 2.5 Pro and Qwen: Qwen3.8 Max (0902) cost per million tokens?
Google: Gemini 2.5 Pro costs $1.25 per 1M input tokens and $10.00 per 1M output tokens; Qwen: Qwen3.8 Max (0902) costs $2.00 input and $6.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemini 2.5 Pro or Qwen: Qwen3.8 Max (0902)?
Google: Gemini 2.5 Pro: 1.0M tokens, about 1,573 pages, against 1M (about 1,500 pages) for Qwen: Qwen3.8 Max (0902).
Do Google: Gemini 2.5 Pro and Qwen: Qwen3.8 Max (0902) support function calling and JSON output?
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...