Flagship Model

Monopole Core v4.2

A foundational reasoning model engineered for technical workflows — coding, scientific computation, structured retrieval, and long-context analysis. Tuned for institutional reliability.

Monopole Core Baseline
Live Metric
0
Inferences served today
12.4% vs yesterday
System Status
  • Inference APIOperational
  • EmbeddingsOperational
  • Fine-tuningOperational
  • EU-WestDegraded
All regions reporting · 99.982% / 30d
Products

A modular AI stack

Each product is engineered as a focused module — combine them into pipelines, or use them in isolation through a single typed API.

Monopole Code

Repository-aware code synthesis with deterministic refactors, structured edit traces, and seamless test feedback loops.

  • Refactoring
  • Edit traces
  • Test loops

Monopole Search

Hybrid retrieval over private corpora with structured reasoning over results.

Monopole Insight

Tabular and time-series analysis with grounded narrative reports.

Monopole Embed

Dense and sparse vector embeddings, multilingual, evaluation-tuned.

Monopole Forge

Custom fine-tuning with parameter-efficient adapters, governed datasets, and evaluation suites that gate every promotion.

42
eval suites
7
adapter formats
3
SOC certifications

Monopole Studio

Visual prompt engineering with versioning and offline replay.

Benchmarks

Measured against the field

Independent evaluations across reasoning, code, retrieval, and instruction-following — published in full.

Reasoning · MMLU-Pro
0 %
Five-shot · pass@1
Code · HumanEval+
0%
Python · pass@1
3.2ppvs v3.8
Retrieval · BEIR
0
nDCG@10 · 18 datasets
8.7%vs prior gen
Latency · p95
0ms
First token · streaming
Multilingual · XNLI · 14 languages
  • English91%
  • German88%
  • French89%
  • Spanish87%
  • Mandarin84%
  • Korean82%
  • Japanese83%
  • Arabic79%
Context Window
0k
tokens · long-context
vs v3
Research

Open work, careful releases

Selected publications from the monopole AI research group.

Reasoning 2026-02

Compositional Tool-use through Structured Edit Traces

L. Ostrov, M. Kanade, S. Beier, et al.

Retrieval 2026-01

Sparse-Dense Hybrid Embeddings for Long-Form QA

N. Marek, R. Tani, P. Holm

Alignment 2025-11

Process Supervision for Long-Horizon Code Tasks

A. Vaill, J. Choe, K. Lindberg

Evaluation 2025-09

A Benchmark Suite for Repository-Aware Edits

T. Marlow, V. Dasari, U. Eiken

Company

A research lab building durable infrastructure.

monopole AI is an applied research company headquartered in Stockholm, with engineering offices in Seoul and Boulder. We build models, tools, and platforms used by institutions where reliability is not optional.

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Founded
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Engineers & researchers
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Countries served
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