Meet Upcube

Upcube is our Mixture-of-Experts system tuned for real work: grounded retrieval, math/coding help, and multi-step workflows that plan, call tools, and complete objectives. Upcube doesn’t just respond; it executes.

Active params
32B (per-token experts)
Total params
~1T (sparse MoE)
Context
256K tokens
Pretraining
15.5T tokens
Modalities
Chat • Search • Voice • Images
Focus
Agentic tools • Grounding • Coding

Editions

  • Upcube-Base — foundation for teams that want deeper control over fine-tuning, safety rules, and specialized behaviors.
  • Upcube-Instruct — drop-in edition for chat, search, voice, and images with reflex-grade responsiveness (no “long thinking” required).

Who benefits from Upcube Chat

Organizations that want natural, personal automation: instant answers, guided troubleshooting, order/status lookups, and content generation—without spinning up heavy infrastructure.

Whether you’re a developer, product team, or support lead, Upcube helps you deliver better experiences, save time, and reduce workload with control, customization, and clarity.

How Upcube Chat works

  1. Interpret user intent and context.
  2. Decide the next best action (answer, ask, search, call a tool, generate an image, speak back).
  3. Respond in real time and maintain state across the thread.

This loop keeps conversations coherent, helpful, and fast—across one or many simultaneous sessions.

What Upcube handles (core modes)

  • Chatbot — long-context conversations, instruction following, and structured outputs (JSON, markdown, code).
  • Search — blend your knowledge base with the open web; return quotes, citations, and links so claims are verifiable.
  • Voice — low-latency, full-duplex talking you can interrupt naturally; clear, expressive responses.
  • Image generation — photorealistic or stylized visuals for product shots, banners, ad concepts, and thumbnails with presets and aspect controls.

Feel the difference

  • Faster, clearer answers: high-context memory reduces repetition and confusion.
  • On-brand control: lock voice, tone, and safety rules; iterate quickly without vendor lock-in.
  • Less busywork: automate FAQs, status checks, triage, and routing so staff can focus on high-value work.
  • Built-in trust: grounded search with citations and transparent steps—verify before you decide.

Clarity & insight for smarter decisions

Dashboards reveal what customers ask, where they struggle, and how responses perform. Track patterns, set alerts, and refine flows—no specialized skills required. Real-time insights keep teams informed and confident.

Conversation health Deflection rate First-contact resolution CSAT proxy Tool-call success

Technical specifications

ArchitectureMixture-of-Experts transformer with token-level expert routing; reduced head count for long-context efficiency; increased MoE sparsity for token efficiency.
Parameter counts~1T total parameters across experts; 32B activated per token on average.
Context length256K tokens (prompt + output). Optimized attention for long documents and multi-file coding sessions.
Pretraining scale15.5T tokens; mixed domains with emphasis on code, math, technical writing, and grounded content.
OptimizerMuonClip (qk-clip stabilization) building on Moonlight/Muon; prevents exploding attention logits while preserving performance.
Inference precisionBF16/FP16; INT8/INT4 via supported engines (quantization-aware inference).
Tool useNative tool calls (functions, web search, code exec shells), retrieval connectors, and structured outputs (JSON) with schema adherence.
Security & opsRole-based access, audit logs, feature kill-switches, traffic shaping, tenant rate limits.

Benchmarks (non-thinking settings)

Coding & tools

  • SWE-bench Verified (Agentless / Agentic)
  • SWE-bench Multilingual
  • LiveCodeBench v6
  • OJBench, MultiPL-E
  • Tau2-bench (weighted) • AceBench (en)

Math & knowledge

  • AIME 2025 • HMMT 2025 • CNMO 2024
  • MATH-500 • PolyMath-en
  • GPQA-Diamond • SuperGPQA
  • MMLU • MMLU-Redux • MMLU-Pro
  • LiveBench (recency-sensitive)

Notes: Bold = global SOTA; underline = open-source SOTA when published. Most metrics at 8k output; SWE-bench Agentless at 16k. Avg@k for stability on logic/maths.

Agentic capabilities

  • Planning: decomposes tasks; progress-aware retries.
  • Tool calling: functions, retrieval/search, code shells, file IO (scoped).
  • Structured output: JSON schemas with self-repair on mismatch.
  • Grounding: prefers source-linked answers; quotes & citations where feasible.
  • Voice & images: low-latency voice with barge-in; brand-consistent image-gen presets.

Example workflow: Salary analysis (end-to-end)

Give Upcube a 2020–2025 dataset and ask, “How does remote-work ratio affect salary across EN/MI/SE/EX?” Upcube will: inspect schema, segment years, categorize remote ratios, run ANOVA or pairwise tests (as appropriate), generate charts and interaction plots, summarize findings, and output a polished HTML report with an interactive simulator recommending remote vs. on-site. One coherent session—chat, search, voice narration, and image assets as needed.

For builders

  • Clean JSON APIs for chat, search, voice, and images.
  • Embeddable widgets for websites and products.
  • Role/system prompts to lock tone, rules, and brand voice.
  • Webhooks & tools to read/write where your work lives (calendars, docs, data stores, dashboards) with your permissions.

Where Upcube excels

Automated, personal conversations that improve CX: support inquiries, instant answers, guided workflows, and info retrieval—with clarity and control. If you need extremely specialized, deeply embedded functions, Upcube-Base offers the control surface to go further.

A day in the life with Upcube Chat

Start with a dashboard showing live engagement. Routine questions are handled automatically; tricky threads get routed with context intact. Alerts flag emerging issues, while reports highlight improvement opportunities. By evening, response times are down, satisfaction is up, and your team is focused on the work that matters.

Deployment & inference

Engines

  • vLLM, SGLang, KTransformers, TensorRT-LLM
  • KV-cache offloading; paged attention for 256K contexts
  • Quant paths: INT8/INT4 where supported

Scaling tips

  • Pin batch sizes per context tier (≤8K, 32K, 128K, 256K) to avoid tail latency.
  • Warm routing caches; monitor expert hot-spots.
  • Per-tenant token & tool-call rate limits.

Resource planning

Context tierTypical useNotes
≤32KGeneral chat, short RAGHighest throughput; default for most apps.
32–128KMulti-doc QA, code sessionsTune batch + KV cache; prefer paged attention.
128–256KLarge docs, audits, long meetingsExpect lower concurrency; consider request sharding.

API compatibility

  • Compatible request/response shapes with popular chat/completions schemas.
  • Function/tool calling with JSON schemas; structured outputs; parallel tool attempts (engine-dependent).
  • Streaming tokens and tool calls; server-sent events for incremental UI.

Docs: /docs • Examples: /examples

Built for trust, designed for security

  • Granular permissions, role-based controls, and audit logs protect your data.
  • Embed on your site, product, or messaging channels via widgets, webhooks, and action handlers.
  • You keep oversight of behavior, content, and routing—maintaining brand integrity and user privacy.

See also: SafetySecurity & PrivacyPrivacy Policy

Known limits

  • Very long jobs may benefit from chunking for best latency and reliability.
  • When a source can’t be verified, Upcube flags uncertainty rather than guessing.
  • Image outputs are synthetic; teams should review for brand, claims, and compliance.
  • Hard reasoning / unclear tool specs may over-generate; throttle or tighten schemas as needed.

Getting started

Choose Upcube-Instruct for quick launches (assistants, help centers, research, creative) or Upcube-Base for deeper control and domain-specific guardrails. Connect your tools, set your prompts, and pick your mode—chatbot, search, voice, or image generation—backed by 256K context.

JSON APIs Embeddable widgets System & role prompts Webhooks & tools Citations & grounding

Contact

Upcube Inc.
New York, NY 10005, USA
upcubeco@gmail.com

Support: /support • Report an issue: /report • GitHub: /github