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.
| Kimi-K2.7-Code moonshot/kimi-k2.7-code | Grok Imagine Image Quality xai/grok-imagine-image-quality | |
|---|---|---|
| Provider | Moonshot | xAI |
| Family | Kimi | |
| Modality | text | image |
| Context window | 262,144 tok | — |
| Max output | 16,384 tok | — |
| Released | 2026-06-12 | 2026-05-22 |
| Input price | $0.950 /1M | $0.050 /img |
| Output price | $4.00 /1M | — |
| Cache read | — | — |
| Tools | yes | — |
| Streaming | yes | — |
| Vision | yes | — |
| JSON mode | yes | — |
| Reasoning | yes | — |
| Prompt caching | — | — |
Kimi K2.7 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.
xAI's higher-fidelity text-to-image model optimized for sharper details, more accurate compositions, and stronger text rendering. Supports image editing via reference images and masks. Trades speed for quality compared to grok-imagine-image. Default output at 2k resolution.
# 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 Kimi-K2.7-Code
client.chat.completions.create(
model="moonshot/kimi-k2.7-code",
messages=[{"role":"user","content":"hello"}],
)
# Try Grok Imagine Image Quality — same client, same key
client.chat.completions.create(
model="xai/grok-imagine-image-quality",
messages=[{"role":"user","content":"hello"}],
)