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.

All models

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 4.5 for comparable context depth. Without public benchmarks, you're trading proven performance data for price arbitrage on long-document tasks. Best for teams willing to validate quality in-house on high-volume workflows where context length matters more than cutting-edge reasoning.

Best for

  • Cost-sensitive long-document processing
  • High-volume context-heavy workflows
  • Internal validation before production scale
  • Budget-constrained research prototyping

Strengths

The 262K context window matches frontier models while pricing undercuts them significantly — input costs run about 50% below Claude Sonnet 4.5. This makes Ring-2.6-1T viable for batch jobs that need to ingest full codebases, legal documents, or transcripts without chunking. The cost structure favors read-heavy tasks where you pass large context but generate concise outputs.

Trade-offs

No public benchmark data means you're flying blind on reasoning quality, instruction-following accuracy, and domain-specific performance. Early adopters will need to run their own evals before trusting production workloads. The output pricing ($0.63/Mtok) climbs steeply if your use case generates verbose responses, eroding the input-cost advantage. Expect less community support and fewer integration examples than established models.

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

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

ProviderContextInputOutputP50 latencyThroughput30d uptime
inclusionai262k$0.07/Mtok$0.63/Mtok

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

Extract Codebase Patterns

Review all files in this repository. Identify the main architectural patterns (MVC, microservices, event-driven, etc.), list the core dependencies, and note any inconsistent naming conventions or anti-patterns.
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Compare Research Papers

Compare the methodologies and conclusions across these three research papers. Highlight where findings conflict, note differences in sample size or experimental design, and suggest which study offers the strongest evidence.
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Audit Meeting Transcripts

Read these meeting transcripts from the past month. Extract all action items with assigned owners, list unresolved questions that came up multiple times, and summarize the main points of disagreement.
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Validate Data Pipeline Logs

Analyze this complete log file from our data pipeline run. Identify the root cause of the failure, list all error codes that appeared, and recommend specific configuration changes to prevent recurrence.
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Data last verified 4 hours ago.Sources aggregated hourly to weekly. See docs/architecture/model-directory.md.