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Text / ReasoningAvailable via API~1T total · ~63B active

Vikasit Reasoner 1T

Trillion-scale reasoning MoE. Deep multi-step reasoning, long-horizon agents.

Overview

Vikasit Reasoner 1T is a trillion-parameter reasoning MoE tuned for deep, multi-step reasoning and long-horizon agentic tasks. Configurable reasoning effort (high / extra-high). Served live via the Vikasit API.

Specifications

Total parameters
~1T total
Active parameters
~63B active
Architecture
Mixture-of-Experts (reasoning-tuned)
Context window
128K native, 256K via YaRN
Modalities
Text in → text out
License
MIT

Capabilities

  • Deep chain-of-thought reasoning
  • Long-horizon agentic planning
  • Configurable reasoning effort (high / xhigh)
  • Strong abstract / ARC-style reasoning
Multilingual.

Benchmarks

BenchmarkScore
GPQA-Diamond88.3
SWE-bench Verified74.0
AIME 202695.8
ARC-AGI-V266.2
MMLU-ProN/A
LiveCodeBenchN/A

Numbers from the Ring-2.6-1T HuggingFace model card (inclusionAI / Ant Group). Architecture internals (expert/layer counts) are not published on the official card; active-param figure is vendor/secondary.

Hardware & deployment

PrecisionMemory
bf16~2 TB
INT4~500 GB

Quick start

Call Vikasit Reasoner 1T through the OpenAI-compatible Vikasit AI API at https://api.vikasit.ai/v1 using the model id vikasit-reasoner-1t.

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-reasoner-1t",
    messages=[
        {"role": "user", "content": "Explain Vikasit Reasoner 1T 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-reasoner-1t",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Limitations

  • Text-only; no multimodal
  • Architecture internals not disclosed by base
  • Vendor-reported benchmarks; limited third-party reproduction

Vikasit Reasoner 1T FAQ

How much does Vikasit Reasoner 1T cost?

Vikasit Reasoner 1T 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 Ring-2.6-1T (inclusionAI / Ant Group, MIT), you can also self-host the weights for free under the MIT licence and pay only for your own compute.

Is Vikasit Reasoner 1T open weight?

Yes. Vikasit Reasoner 1T is built on Ring-2.6-1T (inclusionAI / Ant Group, 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 Reasoner 1T 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-reasoner-1t" as the model. The quick-start snippet above shows the exact Python call.

What context window does Vikasit Reasoner 1T support?

Vikasit Reasoner 1T supports a 128K native, 256K via YaRN context window. It is a ~1T total (~63B active) Mixture-of-Experts (reasoning-tuned) model — full specifications are listed in the table above.

License & attribution

MIT

Built on Ring-2.6-1T (inclusionAI / Ant Group, MIT). Upstream copyright, license, and attribution notices are retained.