compare/Qwen Image 3.0 ProvsGemini 2.5 Pro

Qwen Image 3.0 Pro vs Gemini 2.5 Pro

Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.

RUN BOTH LIVE

Paste a prompt. Watch them race.

Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.

Sign in to runLive streaming uses your own key. It's free to sign up.
 Qwen Image 3.0 Pro
alibaba/qwen-image-3.0-pro
Gemini 2.5 Pro
google/gemini-2.5-pro
ProviderAlibabaGoogle
FamilyQwen
Modalityimagetext
Context window1,000,000 tok
Max output65,536 tok
Released2026-08-112026-05-22
Input price$0.040 /img$1.25 /1M
Output price$10.00 /1M
Cache read
Tools
Streamingyes
Visionyes
JSON mode
Reasoning
Prompt caching
Qwen Image 3.0 Pro
alibaba/qwen-image-3.0-pro
Full spec →

Alibaba's Qwen Image 3.0 Pro generates images from text prompts with a focus on complex layout generation, small-text precision, and multilingual font rendering. Supports up to 6 image variants per call, negative prompts, seed control, and optional prompt rewriting.

Strengths
  • Text-to-image generation
  • Creative control
Gemini 2.5 Pro
google/gemini-2.5-pro
Full spec →

Google's most capable Gemini 2.5 model with strong reasoning, thinking support, and a 1M token context window.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
SWITCH BETWEEN THEM

One key, both models, one line different.

# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI

client = OpenAI(
    base_url="https://api.aigateway.sh/v1",
    api_key="sk-aig-...",
)

# Try Qwen Image 3.0 Pro
client.chat.completions.create(
    model="alibaba/qwen-image-3.0-pro",
    messages=[{"role":"user","content":"hello"}],
)

# Try Gemini 2.5 Pro — same client, same key
client.chat.completions.create(
    model="google/gemini-2.5-pro",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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