Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Gemini Enterprise Agent Platform Reviews & Ratings
    4.3 out of 5 stars 1,178 Ratings
    Company Website for Gemini Enterprise Agent Platform
  • LM-Kit.NET Reviews & Ratings
    4.8 out of 5 stars 29 Ratings
    Company Website for LM-Kit.NET
  • SearchUnify Reviews & Ratings
    4.5 out of 5 stars 150 Ratings
    Company Website for SearchUnify
  • Google AI Studio Reviews & Ratings
    4.8 out of 5 stars 42 Ratings
    Company Website for Google AI Studio
  • OptiSigns Reviews & Ratings
    4.8 out of 5 stars 8,559 Ratings
    Company Website for OptiSigns
  • FinOpsly Reviews & Ratings
    4.7 out of 5 stars 3 Ratings
    Company Website for FinOpsly
  • Dialpad Support Reviews & Ratings
    4.4 out of 5 stars 1,629 Ratings
    Company Website for Dialpad Support
  • Square Payments Reviews & Ratings
    4.3 out of 5 stars 10,141 Ratings
    Company Website for Square Payments
  • iTacit Reviews & Ratings
    4.6 out of 5 stars 46 Ratings
    Company Website for iTacit
  • Mitti (by SafetyCulture) Reviews & Ratings
    4.6 out of 5 stars 872 Ratings
    Company Website for Mitti (by SafetyCulture)

What is SubQ 1.1 Small?

SubQ 1.1 Small is a long-context enterprise AI model developed by Subquadratic to address the limitations of traditional models that struggle with large artifacts. It is built for tasks where the full context matters, including analyzing entire codebases, reviewing lengthy contracts, comparing financial filings, and reasoning across document collections. The model uses Subquadratic Sparse Attention, which replaces dense attention with a learned sparse approach that scales more efficiently as context length grows. This allows SubQ 1.1 Small to process extremely large context windows while sharply reducing attention compute requirements. In benchmark testing, the model achieved near-perfect needle-in-a-haystack retrieval at 1M, 2M, 6M, and 12M tokens. It also scored 99.12% on the RULER 128K benchmark, demonstrating strength on tasks involving multi-hop reasoning, variable tracing, aggregation, and long-context understanding. Beyond retrieval, SubQ 1.1 Small maintains competitive performance in general knowledge, coding, and enterprise agent benchmarks such as GPQA Diamond, LiveCodeBench, and AutomationBench Finance. Its efficiency is a major advantage, requiring 64.5x less compute than dense attention and running 56x faster than FlashAttention-2 at 1M tokens on a single attention layer. The model was trained through staged context extension and continued pretraining on long-form artifacts such as books, documents, and repository-scale code. SubQ 1.1 Small is suited for financial analysis, legal work, software engineering, due diligence, long-horizon coding tasks, and enterprise workflows that depend on relationships spread across large bodies of information. It gives organizations a way to reason over complete artifacts more directly instead of relying only on retrieval pipelines, chunking strategies, and agentic scaffolding.

What is Big Pickle?

Big Pickle is an AI model available through OpenCode Zen, a provider that curates and validates models for coding-agent use cases. The model is listed under the OpenCode provider and can be accessed through an OpenAI-compatible completions API. Big Pickle supports text input and reasoning, making it suitable for developer workflows that require analysis, planning, code understanding, and multi-step execution. It is also described as supporting function calling, which helps developers connect model output with tools, agents, scripts, and automated workflows. Big Pickle’s large context window makes it useful for working with extended prompts, larger project files, documentation, codebases, and complex technical tasks. The model appears in OpenCode Zen’s model list alongside other coding and reasoning models, positioning it as part of a developer-focused model ecosystem. Third-party model directories list Big Pickle with free input and output token pricing, making it appealing for experimentation and cost-sensitive workloads. Developers can use Big Pickle for code assistance, refactoring, debugging, technical research, task decomposition, command-line workflows, and AI agent orchestration. Because some listings differ on exact output-token limits, teams should verify the current model configuration directly in their OpenCode environment before designing production workloads around a fixed limit. Big Pickle is especially useful for developers who want to test long-context AI coding workflows without committing to a more expensive model tier. Big Pickle helps engineering teams explore AI-assisted development, coding agents, tool calling, and long-context reasoning in a flexible and accessible way.

Media

Media

No images available

Integrations Supported

Claude Code
OpenAI
OpenAI Codex
SubQ

Integrations Supported

OpenCode

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Subquadratic

Date Founded

2026

Company Location

United States

Company Website

subq.ai/subq-1-1-small-technical-report

Company Facts

Organization Name

OpenCode

Company Website

opencode.ai/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Popular Alternatives

Claude Fable 5.1 Reviews & Ratings

Claude Fable 5.1

Anthropic
5.0 out of 5 stars

Popular Alternatives

Hy3 Reviews & Ratings

Hy3

Tencent
Ling 2.6 Flash Reviews & Ratings

Ling 2.6 Flash

Ant Group
Claude Fable 5 Reviews & Ratings

Claude Fable 5

Anthropic
5.0 out of 5 stars
Ling 2.6 Reviews & Ratings

Ling 2.6

Ant Group
MiniMax M3 Reviews & Ratings

MiniMax M3

MiniMax
5.0 out of 5 stars
MiniMax M3 Reviews & Ratings

MiniMax M3

MiniMax
5.0 out of 5 stars