LLMinclusionai

inclusionAI: Ring-2.6-1T

Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency. It is optimized for coding agents, tool...

Anyone in the Space can @-mention inclusionAI: Ring-2.6-1T with the team's shared context — pooled credits, one chat, one memory.

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Starter is free forever — 1 Space, 100 credits/month, 1 MCP. No card.

Verdict

Ring-2.6-1T offers a 262K context window at $0.07/$0.63 per Mtok — roughly half the cost of Claude Sonnet 4 for long-context work. Without public benchmarks, you're betting on price-performance for document-heavy tasks where you can validate output quality yourself. Best for teams with tight budgets who need to process large contracts, transcripts, or codebases and can afford to spot-check results. Skip it if you need proven accuracy on complex reasoning or can't tolerate occasional hallucinations.

Best for

Budget-conscious long-document summarization
Processing large contracts or legal filings
Transcript analysis with human review
Codebase-wide refactoring on a budget
High-volume document classification tasks

Strengths

The 262K context window handles full-length books, multi-hour transcripts, or entire codebases in one pass. At $0.07 input per Mtok, it costs half what you'd pay for Claude Sonnet 4's context, making it viable for high-volume document pipelines. The pricing structure favors read-heavy workloads — ingest a 200K-token contract for $0.014, then generate a 2K summary for $0.00126. For teams running dozens of long-context jobs daily, the cost savings compound quickly.

Trade-offs

No public benchmarks means you're flying blind on accuracy relative to GPT-4o, Claude, or Gemini. Expect to invest time validating outputs on your specific use case — this isn't a drop-in replacement for proven models on high-stakes reasoning tasks. The $0.63 output rate climbs fast if you generate long responses, so it's best suited for extract-and-summarize workflows rather than creative writing or extended dialogue. Without benchmark data on math, code, or instruction-following, budget extra QA cycles.

Specifications

Provider: inclusionai
Category: llm
Context length: 262,144 tokens
Max output: 65,536 tokens
Modalities: text
License: proprietary
Released: 2026-05-08

Pricing

Input: $0.07/Mtok
Output: $0.63/Mtok
Model ID: inclusionai/ring-2.6-1t

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool — one plan, one balance for everyone.

Team cost calculator

Seats5 peopleMessages / seat / day80Avg turn size2 ktokOutput share30 %

Estimated monthly spend

$4.22

17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool — one plan, one balance for everyone.

Providers

Provider-level routing data is not available yet for this model.

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Spaces have used this model yet to share anonymised team stats. We wait for at least 50 distinct Spaces per week before publishing any aggregate.

Starter prompts

Summarize Legal Contract

Read this contract in full. List all parties, key obligations with deadlines, termination clauses, and any liability caps or indemnification terms. Format as a bulleted summary under clear headings.

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Analyze Meeting Transcript

Review this meeting transcript. Identify all action items with assigned owners, decisions made, and unresolved questions. Present as a table with columns: Item, Owner, Deadline, Status.

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Extract Data from Reports

Scan this annual report. Extract revenue by segment, year-over-year growth rates, and any forward guidance mentioned. Return as JSON with keys: segment, revenue_current, revenue_prior, growth_pct, guidance.

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Compare Policy Documents

Compare these two policy documents. Highlight all substantive changes: additions, deletions, and modifications to requirements or procedures. Ignore formatting or typo fixes. List changes in order of appearance.

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Codebase Refactoring Plan

Analyze this codebase. Identify deprecated patterns, duplicated logic, and functions that should be consolidated. Propose a refactoring plan with specific file and function names, ordered by impact and risk.

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