compare/Qwen3.8-MaxvsO3

Qwen3.8-Max vs O3

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.
 Qwen3.8-Max
alibaba/qwen3.8-max
O3
openai/o3
ProviderAlibabaOpenAI
FamilyQweno-series
Modalitytexttext
Context window1,000,000 tok200,000 tok
Max output131,072 tok100,000 tok
Released2026-08-022026-05-22
Input price$2.00 /1M$2.00 /1M
Output price$6.00 /1M$8.00 /1M
Cache read——
Toolsyes—
Streamingyesyes
Visionyes—
JSON modeyes—
Reasoningyes—
Prompt caching——
Qwen3.8-Max
alibaba/qwen3.8-max
Full spec →

Alibaba's Qwen 3.8 Max is a 2.4-trillion-parameter MoE flagship built for professional-grade coding and long-horizon autonomous work, capable of delivering complete, production-grade projects spanning 10+ days across legal, financial, design, and other specialized domains. Native visual understanding of images and extended video runs through the full plan-execute-verify cycle, served via DashScope's OpenAI-compatible endpoint.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
O3
openai/o3
Full spec →

o3 is OpenAI’s general-purpose reasoning model, balancing strong analytical performance with reasonable latency and cost.

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 Qwen3.8-Max
client.chat.completions.create(
    model="alibaba/qwen3.8-max",
    messages=[{"role":"user","content":"hello"}],
)

# Try O3 — same client, same key
client.chat.completions.create(
    model="openai/o3",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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