Documentation Index
Fetch the complete documentation index at: https://docs.kymaapi.com/llms.txt
Use this file to discover all available pages before exploring further.
Available models
| Model ID | Parameters | Context | Speed | Best For |
|---|
deepseek-v4-pro | 1.6T (49B active, MoE) | 1M | Medium | Top reasoning, complex coding |
deepseek-v4-flash | 284B (13B active, MoE) | 1M | Fast | General + coding, best value V4 |
deepseek-r1 | 671B (MoE) | 64K | Slow | Reasoning, math, analysis |
deepseek-v3 | 671B (MoE) | 160K | Medium | Previous-gen flagship, stable |
V4 vs V3 — When to upgrade?
| DeepSeek V4 Pro | DeepSeek V4 Flash | DeepSeek V3 |
|---|
| Tier | Flagship | Value | Previous-gen |
| Context | 1M | 1M | 160K |
| Max output | 65K | 65K | 8K |
| Speed | Medium | Fast | Medium |
| Reasoning | Native | Native | No |
| License | MIT | MIT | MIT |
| Release | Preview | Preview | Stable |
deepseek-v4-flash for new work — it gives you 1M context, native reasoning, and the same family behavior at a fraction of the cost. Upgrade to deepseek-v4-pro when quality matters more than price. Stay on deepseek-v3 if you have a stable production workload that’s already tuned to it.
V4 vs R1 — When to use which?
V4 (both Pro and Flash) has reasoning built in, so it’s broadly capable on the same tasks R1 was made for. R1 still has its place for pure step-by-step chain-of-thought work where you want the deeper, slower reasoning trace. Most users will find V4 covers both general and reasoning needs.
Recommendation
Default to deepseek-v4-flash — the new V4 baseline. 1M context, MIT license, native reasoning, lowest V4-tier price.
Step up to deepseek-v4-pro for top-tier reasoning, complex coding, or research-grade work.
Use deepseek-r1 for pure reasoning tasks where you want a slower, deeper chain-of-thought trace. It maps to the reasoning model alias.
from openai import OpenAI
client = OpenAI(base_url="https://kymaapi.com/v1", api_key="ky-...")
# General + coding — use V4 Flash
response = client.chat.completions.create(
model="deepseek-v4-flash",
messages=[{"role": "user", "content": "Refactor this module and explain the tradeoffs."}]
)
# Top reasoning — use V4 Pro
response = client.chat.completions.create(
model="deepseek-v4-pro",
messages=[{"role": "user", "content": "Walk through the proof, then propose a tighter bound."}]
)
Model aliases
| Alias | Resolves to |
|---|
reasoning | deepseek-r1 |
# Using alias
model="reasoning" # → deepseek-r1
