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.
| Qwen3.8-27b qwen/qwen3.8-27b | Kimi-K2.6 moonshot/kimi-k2.6 | |
|---|---|---|
| Provider | Alibaba Qwen | Moonshot |
| Family | Qwen | Kimi |
| Modality | text | text |
| Context window | 262,144 tok | 262,144 tok |
| Max output | 32,768 tok | 16,384 tok |
| Released | 2026-08-17 | 2026-04-20 |
| Input price | $0.450 /1M | $0.950 /1M |
| Output price | $3.20 /1M | $4.00 /1M |
| Cache read | — | $0.160 /1M |
| Tools | yes | yes |
| Streaming | yes | yes |
| Vision | yes | yes |
| JSON mode | yes | yes |
| Reasoning | yes | yes |
| Prompt caching | — | yes |
Qwen 3.8 27B is a 27-billion-parameter instruction-tuned language model from Alibaba's Qwen family, designed for vision, efficient general-purpose text generation and agentic workloads.
Kimi K2.6 is a frontier-scale open-source 1T parameter model with a 262.1k context window, multi-turn tool calling, vision inputs, and structured outputs for agentic workloads.
# 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 Qwen3.8-27b
client.chat.completions.create(
model="qwen/qwen3.8-27b",
messages=[{"role":"user","content":"hello"}],
)
# Try Kimi-K2.6 — same client, same key
client.chat.completions.create(
model="moonshot/kimi-k2.6",
messages=[{"role":"user","content":"hello"}],
)