SenseNova-U1 8B MoT by SenseNova — 32K Context
8B-parameter end-to-end unified multimodal model based on NEO-Unify architecture. Native unified text and image understanding + generation without separate visual encoder or VAE. Supports visual Q&A, text-to-image generation, image editing, and interleaved text-image generation. Context length up to 32K tokens. Available in both 8B dense MoT and A3B MoE variants. Optimized for infographic generation and complex visual reasoning.
At a glance
Modalities
Context window
32,000
Pricing
input / output per 1M
Reasoning
Capabilities
Streaming
Real-time token-by-token response streaming
Function calling
Connect the model to external tools and systems
Structured outputs
Return responses in JSON schema format
Image generation
Generate images from text descriptions
Details
| Release date | 2026-05-01 |
| Model ID | sensenova-u1-8b-mot |
| Provider | SenseNova |
What You Need to Know About SenseNova-U1 8B MoT
Complete Overview of SenseNova-U1 8B MoT by SenseNova
Get detailed information about SenseNova-U1 8B MoT, including its context window of 32000 tokens, pricing per million tokens, supported input and output modalities, and benchmark scores. This model from SenseNova offers specific capabilities for natural language processing, code generation, and complex reasoning tasks that set it apart from alternatives.
Pricing and Cost Analysis for SenseNova-U1 8B MoT
Compare input and output token pricing for SenseNova-U1 8B MoT against other models in its class. Understanding LLM pricing is essential for budgeting your AI applications at scale. We break down the cost per million tokens for both input and output so you can estimate the total cost of your workloads and compare value across providers.
Benchmarks and Performance Metrics for SenseNova-U1 8B MoT
Review benchmark performance data for SenseNova-U1 8B MoT across key evaluation metrics. Compare its reasoning, coding, and language understanding capabilities against competing models to determine if it is the right fit for your specific requirements, whether that involves complex analysis, creative generation, or efficient inference at scale.