Inference & pricing
Model comparison

Vikasit 3 Max vs Qwen3-235B-A22B

Qwen3-235B-A22B is a very cheap large MoE; Vikasit 3 Max is our tuned flagship. Qwen3-235B is unbeatable on price-per-token for a big model. Vikasit 3 Max trades higher cost for flagship tuning, consistency, and support.

Pricing comparison

MetricVikasit 3 MaxQwen3-235B-A22B
Input ($ / 1M tokens)$0.81$0.09
Output ($ / 1M tokens)$2.85$0.10
Blended (3:1 in:out)$1.32$0.09
OpenAI-compatible APIYesYes

Prices are per 1M tokens in USD. Blended cost assumes a 3:1 input-to-output token ratio, a common pattern for chat and generation workloads. Actual cost depends on your traffic. Vikasit 3 Max is available through the Vikasit Inference API.

Choose Vikasit 3 Max when

  • You want a polished, supported flagship default
  • Consistency and formatting reliability matter
  • Single-vendor simplicity across products

Choose Qwen3-235B-A22B when

  • You want the lowest price for a large model
  • You can absorb more output variance
  • Cost is the dominant decision factor

Quick start with Vikasit 3 Max

Call Vikasit 3 Max through the OpenAI-compatible Vikasit Inference API at https://api.vikasit.ai/v1. Change two lines in your existing OpenAI code — the base URL and your key.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.vikasit.ai/v1",
    api_key="sk-vikasit-...",
)

resp = client.chat.completions.create(
    model="vikasit-3-max",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(resp.choices[0].message.content)

FAQ

Is Vikasit 3 Max cheaper than Qwen3-235B-A22B?

Per 1M tokens, Vikasit 3 Max costs $0.81 input / $2.85 output, while Qwen3-235B-A22B costs $0.09 input / $0.10 output. On output tokens — which usually dominate generation cost — Qwen3-235B-A22B is the cheaper option.

Can I call Vikasit 3 Max with the OpenAI SDK?

Yes. The Vikasit Inference API is OpenAI-compatible. Point any OpenAI SDK at https://api.vikasit.ai/v1 with your Vikasit API key and set the model id — chat completions, streaming, and tool calls all work.

Should I choose Vikasit 3 Max or Qwen3-235B-A22B?

Qwen3-235B-A22B is a very cheap large MoE; Vikasit 3 Max is our tuned flagship. Qwen3-235B is unbeatable on price-per-token for a big model. Vikasit 3 Max trades higher cost for flagship tuning, consistency, and support.

Start with Vikasit 3 Max

Get an API key and 2M free tokens a day on Vikasit Nova. Pay-as-you-go, no minimums, OpenAI-compatible.