Cohere

Introducing North Mini Code: Cohere's first open-source agentic coding model. Built for sovereign developers, this efficient 30B MoE model delivers strong software development performance with minimal hardware requirements.

Generating coherent and controllable long-form content remains a persistent challenge for Large Language Models (LLMs). While reasoning-enhanced models have demonstrated success in logic-intensive domains, our evaluation reveals that they suffer from a severe length collapse in open-ended writing, where performance degrades sharply as target lengths exceed 2,000 words. We attribute this failure to the limitation of static hierarchical planning, which struggles to provide dynamic guidance over extended contexts. To bridge this gap, we introduce the Interleaved Structural Chain-of-Thought (IS-C...

Whisper, a widely adopted ASR model, is known to suffer from hallucinations - coherent transcriptions generated for non-speech audio entirely disconnected from the input. We investigate whether hallucinations can be detected and mitigated through Whisper's internal representations. We extract audio encoder activations and evaluate two representation spaces: raw Whisper activations and Sparse AutoEncoder (SAE) latents. We show that both spaces encode linearly separable hallucination-related information, with discriminative power concentrated in a sparse feature subset and increasing toward dee...

Indoor scene generation is crucial for robot simulation and modern interior design. However, complex layouts together with scarce 3D scene data make learning-based generation challenging. Existing methods often rely on hand-crafted rules or focus on isolated sub-tasks (e.g., floorplan synthesis or single-room furnishing), producing whole-home scenes that lack global coherence, realism, and simulation readiness. To mitigate these limitations, we propose a unified hierarchical framework that decomposes indoor scene synthesis into controllable stages. First, we curate a large-scale dataset of 30...

A blog about how Cohere Labs built coplot, a data visualization tool that not only helps their releases, but also their research process.

Vision language models (VLMs) excel at many tasks but still struggle with spatial reasoning when critical information is not directly observable. Many such problems require imaginative perception: inferring what would be seen from an unseen viewpoint, tracing paths through occluded spaces, or integrating partial observations into a coherent spatial representation. We introduce Imaginative Perception Tokens (IPT), intermediate perceptual representations that externalize what a VLM would perceive under alternative spatial configurations while remaining consistent with the observed input. To stu...

Conversational AI agents require memory systems that are both scalable and semantically coherent across long interaction horizons. Existing approaches rely predominantly on large language model (LLM)-based summarisation at write time, which introduces non-determinism, escalating token costs, and opacity in pruning decisions. We present the Deterministic Memory Framework (DMF), a CPU-first approach that replaces generative memory compression with a fully deterministic pipeline grounded in classical NLP analysis, vector geometry, and mathematical scoring. DMF assigns each conversational interac...

Effective "all-team" summarization in high-complexity settings like the Neonatal Intensive Care Unit (NICU) requires aggregating insights from diverse disciplines (physicians, nurses, therapists) spread across hundreds of clinical free-text notes. Simply pooling heterogeneous text often leads to incoherent outputs. Structured summarization therefore first requires accurate categorization of sentence-level provenance across multi-source notes. This pilot study introduces a clinical provenance categorization pipeline using supervised fine-tuning (SFT) of large language models (LLMs). We adapted...

Order-agnostic language models (OALMs), including discrete diffusion language models (dLLMs), are trained to predict masked tokens under arbitrary conditioning sets, allowing sequences to be generated or scored under arbitrary reveal orders at inference time. In LLaDA-2.1, we report three findings. First, the learned conditionals are not exact factorizations of a coherent joint distribution: changing only the reveal order shifts target log-likelihood by up to 0.49 nats/token, so likelihood alone mixes content difficulty with path-dependent artifacts. Second, although confidence-first (CF) dec...

Unsupervised skill discovery (USD) aims to learn diverse behaviors without reward functions, but often results in task-irrelevant or hazardous behaviors due to uniform exploration. Guided skill discovery (GSD) addresses this issue by incorporating human intent to focus exploration on meaningful regions. However, existing GSD methods typically require training additional guidance models, and rely on pre-defined rules or expert demonstration, which can be ineffective under sparse, online-collected human feedback. To overcome this, we propose COLLIE, a GSD framework that leverages dense unsuperv...

Multi-component LLM agents assemble probabilistic claims from components that each see only part of a joint problem; the composition can violate basic probability axioms even when every component is locally coherent. We formalise this locally coherent, globally incoherent failure via the compositional residual eps*, the L2 distance from the composed quote to the joint coherent polytope, computable at runtime from system output and the declared cross-component coupling constraints. A product-structure dichotomy characterises when local coherence suffices, and a Rayleigh-quotient prediction mat...

Delivers advanced reasoning with a minimal compute footprint. Command A+ offers full data sovereignty for governments and regulated industries worldwide.

A specialized translation model leverages RWS’ global language and cultural expertise and Cohere’s Command A+ model to power the new Language Weaver Pro.

Cohere and Mila announced plans for a new academic research collaboration focused on improving AI evaluation across languages and cultures, starting with French-language cultural context in Quebec.

Recent generative models have largely closed the gap on low-level artifacts - pixel fingerprints, frequency anomalies, upsampling traces - particularly in person-centric and partial-edit settings where the manipulated region is small and surrounded by photometrically authentic content. We introduce Social Gaze Consistency, a high-level semantic cue defined as the mutual coherence of gaze direction, head-eye alignment, and pupil placement between interacting individuals, and show that it constitutes a previously underutilized detection axis orthogonal to existing low-level paradigms. We instan...

Browse the new Cohere Merch Store and view the latest collection for sale, along with an archive of our merch and swag history.

Developer fine-tuned Cohere Transcribe to add diarization and timestamp support, extending open-source speech-to-text capabilities.

Cohere launches Command A+, first open-weights MoE model emphasizing efficiency and latency over peak performance.

Cohere releases Command-A-Plus-05-2026 bfloat16 model weights on Hugging Face Hub.

Cohere signs MOUs with Indra Group and Multiverse Computing to advance AI deployment with focus on sovereignty, security, and accessibility.

Cohere releases Command A+, an open-source model optimized for enterprise agent deployment with improved speed and capability.

Cohere acquires Reliant AI to strengthen sovereign AI capabilities for regulated healthcare and life sciences sectors.

PDI-Bench: Quantitative framework for auditing geometric coherence in generated video via perspective distortion and point-tracking metrics.

Value-filtered decoding selectively applies safety steering at test-time, avoiding unnecessary interventions that degrade helpfulness and coherence.

Cohere showcases AI agents for financial services compliance, efficiency, and customer trust.

Cohere outlines governance frameworks for responsible AI development and deployment.

Cohere discusses metrics and integration strategies for achieving AI-native enterprise operations.

Cohere positions LLMs as solutions for financial services knowledge work and customer service automation.

Cohere advises financial firms on scaling generative AI from pilot programs to production with risk management.

Cohere argues private AI deployment offers banks control, security, and customization advantages.

Proposes segment-level supervision for LLM-based Lean 4 theorem proving, balancing dense local signals of step-level training with coherence of whole-proof generation.

Google's leaked video model 'Omni' shows improved text coherence in generated video content.

Cohere publishes enterprise AI governance guide covering monitoring, responsibility frameworks, and innovation-risk balance.

NVIDIA GB200 NVL72 introduces a fundamentally new way to build GPU clusters by extending NVIDIA NVLink coherence across an entire rack. This design enables... NVIDIA GB200 NVL72 introduces a fundamentally new way to build GPU clusters by extending NVIDIA NVLink coherence across an entire rack. This design enables exascale performance, but it also changes the assumptions that many scheduling systems were built on. As a result, “rack-scale locality” becomes a hard constraint. When workloads cross domain boundaries, performance drops sharply… Source

Cohere outlines five-phase enterprise AI maturity framework identifying common production blockers.

Cohere and Aleph Alpha merge to form AI company positioned on sovereign/on-premise deployment.

Learning to Defer framework extended to hierarchical multi-label medical imaging with coherence constraints preventing taxonomic contradictions.

Motivated by sensing modalities in modern autonomous systems that involve hardware-constrained spatial sampling over large arrays with limited coherence time, we develop a novel framework for rapid super-resolution multi-signal direction-of-arrival (DoA) estimation based on Hankel-structured sensing and data matrix decomposition of arbitrary rank, under both the $L_2$ and $L_1$-norm formulation. The resulting $L_2$-norm estimator is shown to be maximum-likelihood optimal in white Gaussian noise. The $L_1$-norm estimator is shown to be maximum-likelihood optimal in independent, identically dis...

AI Council framework mitigates artificial consensus in multi-LLM policy simulation via architectural heterogeneity and coherence validation across value perspectives.

Differentiable physics-informed approach for phase retrieval in coherent transition radiation spectroscopy diagnostics.

Dependency-driven multi-stage prompt pipeline for coherent RPG world and narrative generation using LLMs.

Cohere publishes guidance on enterprise AI security: deployment best practices, vulnerability classes, and secure configuration for production systems.

Talker-T2AV decouples semantic and low-level modeling in autoregressive audio-video generation for improved talking head synthesis coherence.

Canadian AI startup Cohere is taking over Germany-based Aleph Alpha with support from Lidl’s owner, Schwarz Group. With the blessing of their governments, the companies intend to offer a sovereign alternative to enterprises in an AI landscape dominated by American players.

Cohere preparing new MoE model with vLLM optimization support, signaling open-weights or community-accessible release.

Gated context projectors improve cross-stage coherence in autonomous driving VQA by reducing perception-planning inconsistencies by 42.6%.

User reports Image Gen 2 demonstrates advanced reasoning in color composition, generating cinematic palettes and tonal coherence across panels.

Cohere explains MoE models' efficiency gains with speculative decoding via expert routing correlation and bandwidth optimization.

Notion integrates Cohere Rerank to improve workspace search and retrieval accuracy.

Cohere publishes practical guide for implementing agentic RAG systems in enterprise settings.

Ensemble deploys Cohere's custom LLM to add agentic AI automation to healthcare RCM platform.

Cohere explores how rerankers and embeddings improve search and retrieval for AI applications.

Cohere provides FAQ guide addressing common enterprise RAG search and retrieval questions.

Cohere releases Rerank 3 model with improved search precision and enterprise retrieval performance.

Cohere discusses emerging multimodal AI search capabilities for information discovery.

Cohere explains enterprise AI search capabilities for data integration and workflow automation.

Cohere Labs releases Tiny Aya, open-weight multilingual model optimized for on-device inference across 200+ languages.

Cohere launches Transcribe speech-to-text API with accuracy/speed claims for audio data search and automation.

Cohere conceptual overview defining enterprise AI, its business applications, and role in driving automation and growth.

Cohere marketing guide covering generative AI use cases and integration strategies for campaigns.

Cohere educational overview of AI infrastructure components: hardware, software, networking layers for AI stack construction.

Cohere publishes enterprise deployment guidance covering cost, security, and scaling challenges for AI model operations.

Cohere releases Command R7B, compact generative model optimized for speed/efficiency on commodity GPUs and edge devices.

Cohere and NVIDIA partner on NVIDIA-native sovereign AI model for secure, locally-run enterprise deployment.

Cohere appoints chess champion Magnus Carlsen as brand ambassador for company reputation and strategy messaging.

Cohere C-suite guide on enterprise AI advantages: productivity, competitive advantage, and 2026 adoption strategies.

Cohere analysis of AI adoption in financial services: productivity gains, operational efficiency, and implementation pathways.

Cohere webinar on AI applications in financial services; generic promotional content.

Cohere and SAP expand partnership to deploy sovereign AI solutions for European enterprises through SAP Sovereign Cloud.

Cohere, OpenAI, and AI21 Labs have developed a preliminary set of best practices applicable to any organization developing or deploying large language models.

We find that, just as a large transformer model trained on language can generate coherent text, the same exact model trained on pixel sequences can generate coherent image completions and samples. By establishing a correlation between sample quality and image classification accuracy, we show that our best generative model also contains features competitive with top convolutional nets in the unsupervised setting.

We’ve trained a large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization—all without task-specific training.