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.
Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.
| Qwen3.8-Max alibaba/qwen3.8-max | Jev 1.14 typesafe/jev-1.14.0 | |
|---|---|---|
| Provider | Alibaba | Typesafe |
| Family | Qwen | |
| Modality | text | text |
| Context window | 1,000,000 tok | 32,000 tok |
| Max output | 131,072 tok | 32,000 tok |
| Released | 2026-08-02 | 2026-10-16 |
| Input price | $2.00 /1M | $0.042 /1M |
| Output price | $6.00 /1M | $0.0000 /1M |
| Cache read | — | — |
| Tools | yes | — |
| Streaming | yes | yes |
| Vision | yes | — |
| JSON mode | yes | — |
| Reasoning | yes | — |
| Prompt caching | — | — |
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.
Jev 1.14 is TypeSafe's structured evaluation model. It evaluates one state against typed Noul, Choice, Score, and Box questions and returns calibrated answers with probabilities and confidence. Image inputs and Box questions are beta and dreamer-ready, not recommended for production.
# 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 Jev 1.14 — same client, same key
client.chat.completions.create(
model="typesafe/jev-1.14.0",
messages=[{"role":"user","content":"hello"}],
)