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Text / ReasoningAvailable via API1.6T total · 49B active

Vikasit Titan 1.6T

Flagship frontier MoE. 1.6T parameters, 1M-token context. Most capable model.

Overview

Vikasit Titan 1.6T is the flagship frontier model — 1.6T total / 49B active, trained on 32T+ tokens, with a 1M-token context window and state-of-the-art coding, reasoning, and agentic performance. The most capable model in the Vikasit lineup. Served live via the Vikasit API.

Specifications

Total parameters
1.6T total
Active parameters
49B active
Architecture
Mixture-of-Experts — Compressed Sparse Attention (CSA) + Heavily Compressed Attention (HCA), mHC connections
Context window
1M tokens
Modalities
Text in → text out
License
MIT

Capabilities

  • State-of-the-art coding and reasoning
  • 1M-token context window
  • Frontier agentic / terminal performance
  • Novel compressed-attention efficiency
Multilingual.

Benchmarks

BenchmarkScore
MMLU-Pro87.5
GPQA-Diamond90.1
LiveCodeBench93.5
SWE-bench Verified80.6
Humanity's Last Exam37.7
Terminal-Bench 2.067.9
HMMT Feb 202695.2

Numbers from the DeepSeek V4-Pro official model card + technical report (V4-Pro Max flagship column). Note: the base is text-only despite its scale; context is 1M tokens, text.

Hardware & deployment

PrecisionMemory
bf16~3.2 TB
INT4~800 GB

Quick start

Call Vikasit Titan 1.6T through the OpenAI-compatible Vikasit AI API at https://api.vikasit.ai/v1 using the model id vikasit-titan-1.6t.

OpenAI-compatible Python (Vikasit AI API)
# pip install openai
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.vikasit.ai/v1",
    api_key=os.environ["VIKASIT_API_KEY"],
)

resp = client.chat.completions.create(
    model="vikasit-titan-1.6t",
    messages=[
        {"role": "user", "content": "Explain Vikasit Titan 1.6T in one sentence."}
    ],
)

print(resp.choices[0].message.content)
# or with curl
curl https://api.vikasit.ai/v1/chat/completions \
  -H "Authorization: Bearer $VIKASIT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "vikasit-titan-1.6t",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Limitations

  • Text-only (no vision/audio)
  • Frontier-scale serving — cluster required

Vikasit Titan 1.6T FAQ

How much does Vikasit Titan 1.6T cost?

Vikasit Titan 1.6T is served through the Vikasit AI API on usage-based, pay-as-you-go pricing billed per million input and output tokens — see the Vikasit AI pricing page for current rates. Because it is built on the open-weight DeepSeek V4-Pro (DeepSeek, MIT), you can also self-host the weights for free under the MIT licence and pay only for your own compute.

Is Vikasit Titan 1.6T open weight?

Yes. Vikasit Titan 1.6T is built on DeepSeek V4-Pro (DeepSeek, MIT) and distributed under the MIT licence, so the weights are openly available for self-hosting, fine-tuning, and commercial use, subject to the upstream licence terms.

How do I use Vikasit Titan 1.6T with the OpenAI SDK?

The Vikasit AI API is OpenAI-compatible. Point the OpenAI client's base URL at https://api.vikasit.ai/v1, set your Vikasit API key, and pass "vikasit-titan-1.6t" as the model. The quick-start snippet above shows the exact Python call.

What context window does Vikasit Titan 1.6T support?

Vikasit Titan 1.6T supports a 1M tokens context window. It is a 1.6T total (49B active) Mixture-of-Experts — Compressed Sparse Attention (CSA) + Heavily Compressed Attention (HCA), mHC connections model — full specifications are listed in the table above.

License & attribution

MIT

Built on DeepSeek V4-Pro (DeepSeek, MIT). Upstream copyright, license, and attribution notices are retained.