Kali Gamma
DeepOur most capable model. Plans multi-step work, reasons through tricky bugs, and holds large codebases in view.
Kali Gamma, Beta and Epsilon are tuned for depth, balance and speed. Chat here, or reach them from any OpenAI-compatible client.
Our most capable model. Plans multi-step work, reasons through tricky bugs, and holds large codebases in view.
Extended context and steady judgment for everyday coding, writing and review.
Quick answers and tight iteration loops when latency matters more than depth.
Every paid plan unlocks all three models and the API. Higher tiers give more usage in every window. Without a plan you get Kali Epsilon with ₪50,000 a day.
| Plan | Monthly | Annual, per month | 5-hour window | Weekly window |
|---|---|---|---|---|
| Starter To try it properly | $8 | $6.67 Billed annually, $80 a year | ₪560,000 | ₪920,000 |
| PlusRecommended For regular use | $24 | $20 Billed annually, $240 a year | ₪1,360,000 | ₪2,200,000 |
| Pro For daily work | $44 | $36.67 Billed annually, $440 a year | ₪2,160,000 | ₪3,680,000 |
| Max For heavy use | $109 | $90.83 Billed annually, $1,090 a year | ₪4,320,000 | ₪9,200,000 |
| Ultra For the heaviest use | $219 | $182.50 Billed annually, $2,190 a year | ₪8,000,000 | ₪18,400,000 |
Every conversation is saved to your account. Switch models mid-thread; the history comes along.
Replies stream token by token. When a model thinks before it answers, you can read the thought process.
The same models sit behind an OpenAI-compatible endpoint. Point your SDK or editor at it with your session token.
Email verification, session management per device, and a password reset flow that does not need support.
Sign in, grab the token from the login response, and send it as a bearer. Streaming, reasoning deltas and the usual chat-completions shape all work.
Full referencecurl https://estro.help/v1/chat/completions \
-H "Authorization: Bearer $ESTRO_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"model": "kali-gamma",
"stream": true,
"messages": [{ "role": "user", "content": "Refactor this function and explain the tradeoffs." }]
}'