Novita AI

Novita AI

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About Novita AI

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Rated C on Competitive Edge
Rated C on Growth Potential
Rated C on Differentiation

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What believers are saying

  • July 2026 Novita launched Ling-3.0-Flash day-zero and extended free access through August 6.
  • Novita claims 200-plus models, 200ms latency, and 99.5% uptime across its platform.
  • Artifact Hosting and TiDB trial remove deployment and database setup for agent-built apps.

What critics are saying

  • Novita remains bootstrapped and unfunded, constraining GPU capex against OpenAI and Fireworks.
  • Hugging Face and Opper can swap inference providers quickly, crushing Novita pricing power.
  • DeepSeek, Kimi, and Google model-supply changes can starve Novita's catalog and traffic.

What makes Novita AI unique

  • April 2026 Hugging Face partnership puts Novita in front of 5 million developers.
  • July 2026 Opper exposes 80-plus Novita-hosted open-weight models through one API.
  • April 2026 Sandbox uses Firecracker microVMs for sub-200ms isolated agent execution.

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Novita AI
Aug 4th, 2026
What Berkeley's Agentic AI Summit 2026 means for developers building AI agents.

What Berkeley's Agentic AI Summit 2026 means for developers building AI agents. Novita AI was proud to serve as a sponsor of the Agentic AI Summit 2026 at UC Berkeley. Novita AI were glad to meet everyone who visited its booth over the two-day event to ask questions and discuss where agentic AI is headed. The summit reflects where the field is actually moving: from impressive demos toward systems that must run reliably, safely, and repeatedly at scale. For developers, however, the more important takeaway is not the event itself, but the set of problems that consistently surface once agents are put to real-world work. Caption: Novita AI at Agentic AI Summit 2026 in Berkeley Table Of Contents What is Agentic AI Summit 2026? The summit is a good signal for the current state of agentic AI: the conversation is no longer just about prompts and autonomy. It is about execution boundaries, tool use, product ergonomics, evaluation, and cost. That matters because most agent failures are not model failures alone. They are system failures. Agents need permissions, state, retries, observability, and a place to run code safely. When those pieces are missing, the demo looks good and the workflow breaks. Why Agentic AI is moving from demos to real systems. The shift is simple: teams want agents that can ship work, not just talk about work. That means builders now care about: * tool boundaries and permissions * secure execution for code and browser actions * reproducible evals * stable, OpenAI-compatible APIs * inference cost per task, not cost per query If your agent can plan well but cannot execute safely, it is not production-ready. If it can execute but you cannot trace, limit, or afford it, it still is not production-ready. Caption: Novita AI showcased its AI-native cloud platform for builders and agents 5 themes developers should watch after Berkeley's Agentic AI Summit. | Theme | Why it matters | What to do | | Agent infrastructure | Agents need state, tools, and guardrails, not just prompts | Build the runtime first, then the model loop | | Secure execution | Untrusted code and browser actions need isolation | Use a sandbox for anything with side effects | | Open interfaces | Compatibility reduces migration cost | Prefer OpenAI-compatible APIs where possible | | Observability | Agents fail in loops, not in one-off calls | Log tool calls, latency, and retries | | Cost discipline | Multi-step agents multiply inference spend | Track cost per task, not just per request | The big pattern is that agentic AI is becoming systems engineering. What students and researchers should learn now. If you are a student, focus on building one complete agent loop end to end: planning, tool use, execution, error recovery, and a measurable outcome. If you are a researcher, focus on reproducibility and failure analysis. The useful questions are not only "does the model solve the task?" but also "what breaks when the environment changes?" | Audience | Best next skill | Practical project | | Students | Tool use and evals | Build a coding agent with a sandboxed workspace | | Researchers | Reproducibility | Benchmark the same agent across different runtimes | | Builders | Reliability | Add logging, retries, and cost tracking to one workflow | Caption: The Novita AI team spoke with developers, students, and researchers at the summit How to start building AI agents on Novita AI. Novita AI fits the stack well if you want to separate the reasoning layer from the execution layer. Start with the LLM API docs. Novita AI's APIs are OpenAI-compatible, and the docs show the same base_url swap pattern at https://api.novita.ai/openai for existing ChatCompletion and Completion clients. from openai import OpenAI client = OpenAI( base_url="https://api.novita.ai/openai", api_key="<Your API Key>", Then pair that with Novita Agent Sandbox for execution. The official sandbox page positions it for coding agents, browser automation, computer use, evals, and long-running workflows, with sub-second startup and per-second pricing. That split is the key architectural idea: * use the LLM API for reasoning * use the sandbox for side effects * keep both observable * keep both cheap enough to iterate on If you are building agents for developers, students, or researchers, that is the stack that survives contact with reality. Caption: Novita AI credits, startup program materials, and booth handouts at the summit Conclusion. Berkeley's summit is a reminder that agentic AI is no longer just about capability. It is about execution quality. The teams that win will be the ones that treat agents as production systems: isolated, observable, interoperable, and affordable. If you are building now, start with the model API, add a sandbox, and measure the full task path. Faq. What is the main takeaway from Berkeley's Agentic AI Summit 2026? That agentic AI is moving from demos to systems that need reliability, permissions, and safe execution. Do I need a sandbox to build agents? If your agent writes files, runs code, or uses browser/computer actions, yes. Why use Novita AI for agent apps? Because it gives you OpenAI-compatible model access plus a separate sandbox layer for execution. What should I build first? One end-to-end agent workflow with logging, retries, and a clear success metric.

PingCAP
Jul 16th, 2026
Why most ai-generated apps never ship.

Why most ai-generated apps never ship. An agent finishes writing code, and the developer inherits an infrastructure checklist. A typical AI-generated app needs: * A runtime environment, such as a container or sandbox. * A database, such as PostgreSQL or MySQL. * A domain and SSL certificate. * Environment variable configuration. * Database migration scripts. Agents do not usually handle any of this when they write code. Each item pulls the developer into a different console, and shipping one small app can require coordinating three or more platforms. For teams generating dozens of apps through agents, that overhead compounds fast. Novita Artifact Hosting: A deployment target for agent-built apps. Novita Artifact Hosting is a fully managed deployment platform for applications created by AI coding agents. The division of labor is simple: Agents write the code, and Novita runs it. One SDK call takes a sandbox directory to a live URL. Agent generates code + Dockerfile in a sandbox Agent generates code + Dockerfile in a sandbox | | One SDK call: project.deploy(sandbox_id, arti_dir) | | Docker Build | image creation | | Light Runtime | deployment goes live | | Users access the app through a domain: https://my-app.novita.space Users access the app through a domain: https://my-app.novita.space This workflow is already live and supports custom domains. But it only solves the compute side of the problem. Real applications also need data. Why ai-generated apps need MySQL compatibility and zero operations. For AI-generated web applications, the database layer has two hard requirements: MySQL compatibility and zero operations. TiDB meets both, which is why Novita chose it for its managed database layer. MySQL compatibility. The frameworks agents reach for most often, such as Next.js, Django, and Laravel, work smoothly with the MySQL ecosystem, and AI-generated code frequently defaults to a MySQL driver. Because TiDB is compatible with the MySQL protocol, AI-generated code connects and runs without rewriting SQL. Zero operations. Agent developers do not want to manage databases. They do not want to configure connection pools, tune parameters, or handle backups. TiDB's distributed architecture scales automatically, so no dedicated DBA is required. TiDB also supports hybrid transactional/analytical processing (HTAP). This means the same database that handles an app's transactions can also serve its analytical queries, without adding a separate warehouse or CDC pipeline. Adding a TiDB Cloud instance with one parameter. With Novita Artifact Hosting, enabling TiDB Cloud takes one parameter in the deploy call: deployment = project.deploy( sandbox_id="xxx", arti_dir="./workspace/my-app", database=True, # | this line migrations=[ Path("./migrations/0001_schema.sql").read_text, Path("./migrations/0002_seed.sql").read_text,], http_port=3000,) Behind the scenes, database=True triggers four automatic steps: * Novita creates or reuses a TiDB instance for the project. * Migrations run in order, creating tables, indexes, and seed data. * Novita injects DATABASE_URL into the deployment environment, and the app reads it directly from os.environ["DATABASE_URL"]. * The app deploys, connects to the database, and starts serving users. For developers, this means no database signup, no connection string setup, and no manual migration steps. Just one line: database=True. What this changes for AI coding agents. The table below compares the workflow before and after Novita Artifact Hosting with a TiDB database. Current status and what's Next. Here is where the integration stands today: * Artifact Hosting is live and supports custom domains. * TiDB Cloud is currently in trial. * Python SDK and CLI support are available. * Open-source examples are available on GitHub: ecomm-with-sql, ecomm-with-managed-db, and snake-game-static. Once the managed database capability reaches general availability, the Novita + TiDB combination can expand further: * Multi-region deployment: TiDB's multi-data-center capabilities combined with Novita's global sandbox nodes. * Data sovereignty: Users choose where their data is stored. * Agent-native workflows: Agents create projects, deploy applications, and provision databases directly through the SDK, making the entire process fully automated. Agents already write the code. With Novita handling deployment and TiDB handling data, the path from prompt to production finally has no manual steps left in the middle. Want the same zero-ops database layer for your own AI-generated apps? Spin up a TiDB Cloud cluster in minutes.

Opper
Jul 13th, 2026
Opper AI partners with Novita to bring 80+ open-weight models to the gateway.

Opper AI partners with Novita to bring 80+ open-weight models to the gateway. Stockholm, Sweden, July 2026. Opper AI and Novita are partnering to bring Novita's open-weight inference to the Opper AI gateway. Builders can now reach more than 80 Novita-hosted models through the Opper API, from DeepSeek V4 and Kimi K2.6 to GLM-5, MiniMax M3, Llama 4, and Qwen, making Novita one of the broadest single-provider catalogues on the gateway. Why this matters. One of the broadest open-weight catalogues anywhere. Novita serves models from close to twenty different makers through Opper: DeepSeek V4 Pro and Flash with 1M-token context windows, Moonshot's Kimi family up to K2.6 and the code-tuned K2.7, Z.ai's GLM-5, MiniMax M3 with a 1M-token window, Meta's Llama 3 and Llama 4, the Qwen lineup, Google's Gemma 4, OpenAI's GPT-OSS, Baidu's ERNIE 4.5, NVIDIA Nemotron, and a long tail of specialist checkpoints down to dedicated OCR models. When your agent needs one specific open-weight checkpoint, this is the route where it's most likely already live. New releases, production-ready fast. Open-weight releases move quickly, and Novita has made a name for being among the first providers to serve them with stable, production-grade inference. The current frontier of open models, Kimi K2.6, GLM-5, DeepSeek V4, and MiniMax M3, is already callable through Opper today, at price points that are consistently among the most competitive on the gateway. Per Novita's published figures, its model APIs run at around 200ms latency with 99.5% uptime, up to 50% cheaper than the large cloud providers. Clear data handling, US-hosted. Novita is hosted in the United States and does not train on customer data. The platform is SOC 2 Type II audited and a GDPR DPA is offered under standard contractual clauses; operationally, Novita keeps abuse-monitoring logs. For teams that want the breadth of the catalogue with a well-understood, audited posture behind it, that's a clean foundation to build on. More than a router: the AI control plane. Routing to Novita is just the entry point. Every call through Opper runs on its AI control plane: intelligent routing across models, full observability into every call, token, and session, real-time PII masking and content filtering, budget caps, and audit trails. Pin Novita for a task or set it as a fallback for rate limits and outages, and because Novita is OpenAI-compatible, getting there is a model string, not a migration. "We're glad to welcome Novita to Opper. They bring one of the broadest open-weight catalogues anywhere, from DeepSeek and Kimi to GLM, MiniMax, and Llama, and they're consistently among the first to get new releases production-ready. That gives our developers a deep bench of models they can reach the moment they need them." - Göran Sandahl, Co-founder and CEO, Opper AI "Developers come to Novita because new open models show up fast and just work in production. Opper puts that catalogue in front of a large community of builders through one API, with routing, observability, and governance handled, so teams can adopt new models the day they land." - Junyu Huang, COO, Novita Models live today. The catalog below is fetched live from Opper's model API and filtered to Novita-hosted models. Availability, context windows, and pricing stay in sync with what's actually callable through Opper. All Novita routes are hosted in the United States. | Model | Region | Context | Input / 1M | Output / 1M | | novita/Sao10K/L3-8B-Stheno-v3.2 | US | 8K | $0.05 | $0.05 | | novita/baichuan/baichuan-m2-32b | US | 131K | $0.07 | $0.07 | | novita/baidu/cobuddy | US | 131K | $0.28 | $1.13 | | novita/baidu/ernie-4.5-21B-a3b | US | 120K | $0.07 | $0.28 | | novita/baidu/ernie-4.5-21B-a3b-thinking | US | 131K | $0.07 | $0.28 | | novita/baidu/ernie-4.5-300b-a47b-paddle | US | 123K | $0.28 | $1.10 | | novita/baidu/ernie-4.5-vl-28b-a3b | US | 30K | $0.14 | $0.56 | | novita/baidu/ernie-4.5-vl-28b-a3b-thinking | US | 131K | $0.39 | $0.39 | | novita/baidu/ernie-4.5-vl-424b-a47b | US | 123K | $0.42 | $1.25 | | novita/deepseek-ocr | US | 128K | $0.03 | $0.03 | | novita/deepseek-ocr-2 | US | 128K | $0.03 | $0.03 | | novita/deepseek-v3.1 | US | 131K | $0.27 | $1.00 | | novita/deepseek-v3.2 | US | 164K | $0.27 | $0.40 | | novita/deepseek-v4-flash | US | 1.0M | $0.14 | $0.28 | | novita/deepseek-v4-pro | US | 1.0M | $1.74 | $3.48 | | novita/deepseek/deepseek-prover-v2-671b | US | 160K | $0.70 | $2.50 | | novita/deepseek/deepseek-r1 | US | 64K | $4.00 | $4.00 | | novita/deepseek/deepseek-r1-0528 | US | 164K | $0.70 | $2.50 | | novita/deepseek/deepseek-r1-0528-qwen3-8b | US | 128K | $0.06 | $0.09 | | novita/deepseek/deepseek-r1-distill-llama-70b | US | 8K | $0.80 | $0.80 | | novita/deepseek/deepseek-r1-distill-qwen-14b | US | 33K | $0.15 | $0.15 | | novita/deepseek/deepseek-r1-distill-qwen-32b | US | 64K | $0.30 | $0.30 | | novita/deepseek/deepseek-r1-turbo | US | 64K | $0.70 | $2.50 | | novita/deepseek/deepseek-r1/community | US | 64K | $4.00 | $4.00 | | novita/deepseek/deepseek-v3-0324 | US | 164K | $0.27 | $1.12 | | novita/deepseek/deepseek-v3-turbo | US | 64K | $0.40 | $1.30 | | novita/deepseek/deepseek-v3.1-terminus | US | 131K | $0.27 | $1.00 | | novita/deepseek/deepseek-v3.2-exp | US | 164K | $0.27 | $0.41 | | novita/deepseek/deepseek-v3/community | US | 64K | $0.89 | $0.89 | | novita/deepseek/deepseek_v3 | US | 64K | $0.89 | $0.89 | | novita/elephant | US | 262K | $0.10 | $0.30 | | novita/glm-4.7 | US | 205K | $0.60 | $2.20 | | novita/glm-4.7-flash | US | 200K | $0.07 | $0.40 | | novita/glm-5 | US | 205K | $1.00 | $3.20 | | novita/google/gemma-3-12b-it | US | 131K | $0.05 | $0.10 | | novita/google/gemma-3-27b-it | US | 98K | $0.12 | $0.20 | | novita/google/gemma-4-26b-a4b-it | US | 262K | $0.13 | $0.40 | | novita/google/gemma-4-31b-it | US | 262K | $0.14 | $0.40 | | novita/gryphe/mythomax-l2-13b | US | 4K | $0.09 | $0.09 | | novita/inclusionai/ling-2.6-1t | US | 262K | $0.30 | $2.50 | USD per 1M tokens. Pricing and availability subject to change. Get started. Paste this into your coding agent (Claude Code, Cursor, Codex, and more) and it will set up Opper and route to Novita for you: Use curl to download, read and follow: https://skills.opper.ai Then set up Opper to use Novita as the provider, e.g. novita/deepseek-v4-flash. Prefer a direct call? Opper is drop-in compatible with the OpenAI, Anthropic, and Google SDKs, so one API key and the model string are all you need: 1import OpenAI from "openai"; 2 3const client = new OpenAI({ 4 apiKey: process.env.OPPER_API_KEY, 5 baseURL: "https://api.opper.ai/v3/compat", 6}); 7 8const completion = await client.chat.completions.create({ 9 model: "novita/deepseek-v4-flash", 10 messages: [{role: "user", content: "Hello"}], 11}); 12console.log(completion.choices[0].message.content); About Novita Novita is an AI cloud platform headquartered in San Francisco, serving 200+ open-weight and multimodal models across text, image, audio, and video through an OpenAI-compatible API, alongside dedicated and serverless GPU infrastructure and agent sandboxes. Novita is SOC 2 Type II audited and does not train on customer data. About Opper AI Opper AI is the European AI gateway and control plane for agents: one EU-hosted, GDPR-compliant API across 300+ models, with smart routing, automatic fallbacks, built-in evaluations and observability, real-time guardrails, and full OpenAI SDK compatibility.

PR Newswire
Apr 28th, 2026
Novita AI launches Sandbox to secure autonomous AI agents with sub-200ms isolation

Novita AI has launched Sandbox, a secure infrastructure platform for autonomous AI systems including OpenClaw and Hermes Agent. The platform addresses security risks as AI systems evolve from copilots to autonomous agents that execute code and interact with live environments. Sandbox uses Firecracker microVMs to isolate each agent task with dedicated kernels, isolated memory and ephemeral filesystems, preventing credential leakage and cross-agent interference. The system maintains sub-200 millisecond startup times whilst scaling to thousands of parallel microVMs. The platform supports stateful execution, allowing environments to pause and resume with full runtime state restored in approximately one second. Sandbox is available through managed NovitaClaw deployments, OpenClaw skills and Hermes-compatible runtimes. Novita AI positions the launch as creating a new category: Secure Agent Infrastructure for production-scale autonomous systems.

Chinook Observer
Apr 21st, 2026
Novita AI ranked as the best performing & reliable inference layer.

Novita AI ranked as the best performing & reliable inference layer. PR Newswire Today at 8:07am PDT 120+ LLMs through a single API, with day-0 model availability, OpenAI and Anthropic compatibility, and top-ranked performance validated by Artificial Analysis. SAN FRANCISCO, April 21, 2026 /PRNewswire/ - As demand for open-source AI infrastructure grows, Novita AI is establishing itself as the inference provider for developers and engineering teams that need fast and affordable inference for production AI. The platform covers more than 120 large language models through a single OpenAI-compatible and Anthropic-compatible API, makes every new model available on release day, and ranked #1 for scientific reasoning accuracy across all major inference providers, according to independent benchmarking by Artificial Analysis. Novita AI is trusted by leading teams across the AI ecosystem, including Hugging Face, Quora, OpenRouter, Vercel, Kilo Code, and Genspark. "Open-source AI moves at a pace that most infrastructure hasn't kept up with," said Junyu Huang, COO of Novita AI. "We built Novita to close that gap. When a new model ships, developers can be in production with it the same day, on infrastructure they can actually rely on." Artificial Analysis provides comparison and analysis of AI models and API hosting providers, with independent benchmarks across key performance metrics including quality, price, and output speed. In its GPT-OSS 120B assessment covering all major inference providers, Novita AI ranked as follows (April 2026): GPQA Diamond (scientific reasoning): #1 among all providers, scoring 79.0% across 16 runs AIME 2025 (advanced mathematics): 93.3% across 32 runs, at the level of the top providers IFBench (instruction following): #5, scoring 68.9%, within 0.8 points of the top provider New models ship constantly. Novita AI makes each one available through its API on release day, without exception. For engineering teams running evaluation pipelines or production systems that depend on current models, access is never the bottleneck. Novita AI hosts more than 120 LLMs across every major model family, including Qwen, DeepSeek, LLaMA, Mistral, Gemma, GLM, Phi, and more. All models share the same API format, authentication, and SDK. Teams on the OpenAI or Anthropic SDK can switch to Novita by changing the base URL. Novita's API works out of the box with Claude Code, OpenClaw, Codex CLI, and OpenCode. Novita AI delivers fast inference with the full feature set production AI teams depend on, with no tiered restrictions or add-ons. Tool calling: compliant with OpenAI and Anthropic function-calling specifications, supporting multi-turn agent workflows Structured outputs: JSON responses that conform to a specified schema, no parsing wrappers needed Prompt caching: lower latency and token costs for RAG pipelines and agent sessions with repeated context Novita AI is an AI and agent cloud platform helping developers and startups build, deploy, and scale models and agentic applications with high performance, reliability, and cost efficiency. The platform delivers fast inference across 120+ LLMs and multimodal models through a single API, alongside GPU Instances, Bare Metal, and Agent Sandbox infrastructure built for production AI. SOURCE Novita AI This is a paid placement. For further inquiries, please contact PR Newswire directly.

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