379 Integrations with Rust
View a list of Rust integrations and software that integrates with Rust below. Compare the best Rust integrations as well as features, ratings, user reviews, and pricing of software that integrates with Rust. Here are the current Rust integrations in 2026:
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1
GPT-5.4 Pro
OpenAI
GPT-5.4 Pro is an advanced AI model developed by OpenAI to deliver high-performance capabilities for professional and complex tasks. It combines improvements in reasoning, coding, and agent-based workflows into a single unified system. The model is designed to work efficiently across professional tools such as spreadsheets, presentations, documents, and development environments. GPT-5.4 Pro also includes native computer-use capabilities, enabling AI agents to interact with software, websites, and operating systems to complete tasks. With support for up to one million tokens of context, it can manage long workflows and large datasets more effectively than previous models. The model also improves tool usage, allowing it to search for and select the right tools during multi-step processes. By delivering more accurate outputs with fewer tokens, GPT-5.4 Pro helps professionals complete complex work faster and more efficiently. -
2
GPT‑5.4 Thinking
OpenAI
GPT-5.4 Thinking is an advanced reasoning-focused AI model available within ChatGPT, designed to help users complete complex professional tasks more effectively. It combines improvements in reasoning, coding, and agent-based workflows to provide more accurate and reliable outputs. The model can present an upfront outline of its reasoning process, allowing users to adjust instructions while it is generating a response. This capability helps produce results that better align with user goals without requiring multiple follow-up prompts. GPT-5.4 Thinking also improves deep web research, enabling it to locate and synthesize information from multiple sources more efficiently. With stronger context management, it can handle longer conversations and complex problem-solving tasks with greater coherence. These capabilities make GPT-5.4 Thinking well suited for professional knowledge work and advanced analytical tasks. -
3
GPT-5.4 mini
OpenAI
GPT-5.4 mini is a fast and efficient AI model designed for high-performance tasks such as coding, reasoning, and multimodal understanding. It delivers strong capabilities similar to larger models while maintaining lower latency and cost. The model is optimized for responsive applications where speed is critical, including coding assistants and real-time workflows. GPT-5.4 mini supports advanced features such as tool use, function calling, and image interpretation. It performs well on complex tasks while running significantly faster than previous mini models. The model is also suitable for subagent systems, where it handles smaller tasks within larger AI workflows. By combining speed, efficiency, and strong performance, GPT-5.4 mini enables scalable AI applications across various use cases. -
4
GPT-5.4 nano
OpenAI
GPT-5.4 nano is a lightweight and highly efficient AI model designed for fast, cost-effective task execution. It is optimized for simple and high-volume tasks such as classification, data extraction, and basic coding support. The model delivers quick responses with minimal latency, making it ideal for real-time and large-scale applications. GPT-5.4 nano improves significantly over previous nano models in both performance and efficiency. It supports essential capabilities like tool use and structured data processing. The model is commonly used as a supporting component within larger AI systems. By focusing on speed and affordability, GPT-5.4 nano enables scalable automation across various workflows. -
5
LakeSail
LakeSail
LakeSail is a unified, cloud-native data and AI platform designed to transform how organizations process, analyze, and act on large-scale data by combining all workloads into a single, high-performance system. At its core is Sail, a Rust-native distributed computation engine that serves as a drop-in replacement for Apache Spark, enabling teams to run existing SQL and Python workloads without rewriting code while eliminating JVM overhead and improving efficiency. It unifies batch processing, stream processing, ad-hoc queries, and AI workloads into one runtime, allowing data pipelines and intelligent systems to operate seamlessly on the same infrastructure. It introduces a multimodal lakehouse architecture capable of handling structured and unstructured data, including PDFs, images, and video, within a single environment, making it suitable for modern AI-driven use cases. -
6
ERNIE 5.1
Baidu
ERNIE 5.1 is Baidu’s latest large language model designed to deliver advanced reasoning, agentic AI capabilities, creative writing, and world knowledge performance while operating with significantly improved efficiency. The model builds on the foundation of ERNIE 5.0 while reducing total parameters and training costs, allowing it to achieve flagship-level intelligence at a fraction of the computational expense of comparable models. ERNIE 5.1 performs strongly across international benchmarks for reasoning, search, knowledge, and agentic tasks, ranking among the top global AI models and leading among Chinese-developed models on multiple leaderboards. The platform introduces a new fully asynchronous reinforcement learning infrastructure that improves training efficiency, scalability, and stability for complex long-horizon AI tasks. ERNIE 5.1 also features advanced creative writing capabilities. -
7
Concentrate AI
Concentrate AI
Concentrate AI is the LLM gateway for fast-growing teams, one API for every major LLM provider, with routing, spend, logs, and controls in one place. It helps teams securely access, use, and manage AI through a single API, so every request can find the smarter, faster, cheaper model for the workflow or task. Teams can access 130+ models, benchmark speed, quality, and cost, and route each workload to the best fit without wiring separate provider APIs into every environment. Support bots, coding agents, internal tools, chat, and batch jobs do not need the same model or the same route, so Concentrate lets teams pick a model slug, limit allowed providers, sort by live latency, use fallbacks, and reroute traffic when a provider slows down, errors, or hits a rate limit. It also gives engineering, finance, security, and leadership a shared view of AI usage with request-level logs, models, provider, duration, token counts, spend, error rates, alerts, and exports. -
8
Yazi
Yazi
Yazi is a blazing-fast terminal file manager written in Rust, based on async I/O. All I/O operations are asynchronous, while CPU tasks are spread across multiple threads to make the most of available resources. Its task system provides powerful async task scheduling and management, with real-time progress updates, task cancellation, and internal task priority assignment. Built for users who live in the terminal, Yazi combines speed with a modern file-management workflow: scrollable previews for various file types, visual mode for bulk selection and bulk rename, Vim-like input and select components, multi-tab collaboration, and fast navigation through tools like fzf and zoxide. Users can select multiple files individually, perform copy, cut, and other operations, and let the task system schedule the work while keeping progress visible. Incremental find shows matches in real time, including the current position and total number of matches. -
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GPT-5.6 Sol Ultrafast
OpenAI
GPT-5.6 Sol Ultrafast is a new OpenAI API service tier that runs GPT-5.6 Sol up to 14× faster than Standard processing, bringing frontier intelligence to products and workflows where every second matters. Powered by Cerebras, it can generate up to 750 output tokens per second, allowing advanced reasoning to operate at real-time speeds without requiring a smaller or more specialized model. It is designed for time-sensitive business workflows where faster responses can change what AI can realistically do. Applications include incident response, where models can analyze logs, code changes, traces, and engineer reports while an outage is unfolding; financial research and security, where changing market signals and suspicious transactions can be assessed quickly; and customer support and voice, where complex issues can be resolved without interrupting a live conversation. In commerce, it can answer product questions, check inventory, and personalize recommendations. -
10
Gemini 3.8 Flash Cyber
Google
Gemini 3.8 Flash Cyber is Google’s most capable cybersecurity model, providing frontier-level performance in vulnerability detection and automated patching with the speed needed for quick iteration. It is designed specifically for trusted defenders and is available through the Fairwind Program. On CyberGym, a standard industry benchmark for finding vulnerabilities, the model demonstrates frontier-level autonomous vulnerability discovery and surpasses both Gemini 3.5 Flash Cyber and significantly larger frontier models. Google also evaluated it on an internal benchmark covering complex codebases across 20 programming languages, where it achieved a success rate exceeding 70% in discovering a wide range of vulnerabilities. Gemini 3.8 Flash Cyber prioritizes vulnerability fixing over offensive capabilities such as exploitation, equipping defenders with expert capabilities that can help them maintain an advantage over attackers. -
11
Grok 4.8
SpaceXSI
Grok 4.8 is an upcoming AI model from SpaceXSI expected to advance the Grok family in reasoning, coding, agentic workflows, and professional knowledge work. Elon Musk has described the model as having approximately 2.5 trillion parameters and being trained using a new C++ software stack. The model is expected to complete its initial training before entering reinforcement learning, with final capabilities and performance still subject to change. Grok 4.8 is anticipated to build on Grok 4.7’s strengths in software development, tool calling, configurable reasoning, multimodal input, and long-running agentic tasks. SpaceXSI has not yet released official benchmarks, pricing, context-window specifications, API identifiers, or a public launch date for Grok 4.8. The model is expected to target developers, researchers, enterprises, and advanced AI users who need high-capability reasoning and autonomous task execution. -
12
Open Code Review
Alibaba
Open Code Review is an AI-powered code review CLI built from Alibaba’s battle-tested internal code review agent and validated across millions of real-world tasks. It reads Git diffs, sends changed files to a configurable LLM through an agent with tool-use capabilities, and generates structured review comments with precise line-level positioning. Rather than reviewing only the visible diff, the agent can read complete files, search the codebase, inspect related changes, and cross-reference context to uncover deeper issues. Its hybrid architecture separates deterministic engineering tasks such as file filtering, task splitting, rule routing, scheduling, and line positioning from LLM reasoning for risk detection, context exploration, and issue classification. A dedicated reflection module helps intercept hallucinations and knowledge drift before comments are returned. Review depth can be adjusted from low to high depending on the required balance of speed and thoroughness. -
13
CodeSonar
CodeSecure
CodeSonar employs a unified dataflow and symbolic execution analysis that examines the computation of the complete application. By not relying on pattern matching or similar approximations, CodeSonar's static analysis engine is extraordinarily deep, finding 3-5 times more defects on average than other static analysis tools. Unlike many software development tools, such as testing tools, compilers, configuration management, etc., SAST tools can be integrated into a team's development process at any time with ease. SAST technologies like CodeSonar simply attach to your existing build environments to add analysis information to your verification process. Like a compiler, CodeSonar does a build of your code using your existing build environment, but instead of creating object code, CodeSonar creates an abstract model of your entire program. From the derived model, CodeSonar’s symbolic execution engine explores program paths, reasoning about program variables and how they relate. -
14
AtomicJar
AtomicJar
Shift testing to the left and find issues earlier, when they are easier and cheaper to fix. Enable developers to do better integration testing, shorten dev cycles and increase productivity. Shorter and more-thorough integration feedback cycles, mean more reliable products. Testcontainers Cloud makes it easy for developers to run reliable integration tests, with real dependencies defined in code, from their laptops to their team’s CI. Testcontainers is an open-source framework for providing throwaway, lightweight instances of databases, message brokers, web browsers, or just about anything that can run in a Docker container. No more need for mocks or complicated environment configurations. Define your test dependencies as code, then simply run your tests and containers will be created and then deleted. -
15
Unremot
Unremot
Unremot is a go-to place for anyone aspiring to build an AI product - with 120+ pre-built APIs, you can build and launch AI products 2X faster, at 1/3rd cost. Even, some of the most complicated AI product APIs take less than a few minutes to deploy and launch, with minimal code or even no-code. Choose an AI API that you want to integrate to your product from 120+ APIs we have on Unremot. Provide your API private key to authenticate Unremot to access the API. Use unremot unique URL to connect the product API - the whole process takes only minutes, instead of days and weeks. -
16
Succinct
Succinct
Making zero-knowledge proofs accessible to any developer. Write ZKPs with Rust using SP1, a performant, open-source zkVM and generate proofs in 1-click on Succinct’s decentralized prover network. With SP1, developers can write Rust, reusing existing libraries for reduced development time and better maintainability. Instead of requiring specialized expertise writing circuits for months, write your verifiable program in hours. SP1’s state-of-the-art performance is a result of its next-generation “precompile-centric” architecture. SP1 shows general-purpose Rust code can match the performance of specialized circuit-based approaches. -
17
CodeGemma
Google
CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time. -
18
Daft
Daft
Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. -
19
Grok 4 Fast
SpaceXSI
Grok 4 Fast is the latest AI model from xAI, engineered to deliver rapid and efficient query processing. It improves upon earlier versions with faster response times, lower latency, and higher accuracy across a variety of topics. With enhanced natural language understanding, the model excels in both casual conversation and complex problem-solving. A key feature is its real-time data analysis capability, ensuring users receive up-to-date insights when needed. Grok 4 Fast is accessible across multiple platforms, including Grok, X, and mobile apps for iOS and Android. By combining speed, reliability, and scalability, it offers an ideal solution for anyone seeking instant, intelligent answers. -
20
GPT-5.4
OpenAI
GPT-5.4 is an advanced artificial intelligence model developed by OpenAI to support complex professional and technical work. The model combines improvements in reasoning, coding, and agent-based workflows into a single system designed for real-world productivity tasks. GPT-5.4 can generate, analyze, and edit documents, spreadsheets, presentations, and other work outputs with greater accuracy and efficiency. It also features improved tool integration, enabling the model to interact with software environments and external tools to complete multi-step workflows. With enhanced context capabilities supporting up to one million tokens, GPT-5.4 can process and reason over very large amounts of information. The model also improves factual accuracy and reduces errors compared to earlier versions. By combining strong reasoning, coding ability, and tool use, GPT-5.4 helps users complete complex tasks faster and with fewer iterations. -
21
Claude Fable 5.5
Anthropic
Claude Fable 5.5 is not currently an announced or released Anthropic model as of September 30, 2026. Anthropic's current model documentation lists Claude Fable 5.1 as the latest Fable model alongside Claude Opus 5.5 and Claude Sonnet 5.5. Fable 5.1 remains Anthropic's premium model for demanding reasoning and long-horizon agentic workloads, with a 1-million-token context window and maximum output of 128,000 tokens. It uses adaptive thinking that is always enabled and defaults to a high reasoning effort level. Fable 5.1 is priced at $10 per million input tokens and $50 per million output tokens, with cache reads priced at $0.25 per million tokens. Anthropic has released Opus 5.5 and Sonnet 5.5, but there is currently no official model documentation, pricing, release date, benchmark data, or API identifier for Claude Fable 5.5. -
22
Gemini 4 Carbon
Google
Gemini 4 Carbon is a reportedly experimental artificial intelligence model developed by Google DeepMind as part of the Gemini 4 family of advanced reasoning models. The model has reportedly been tested internally for software engineering and AI-assisted coding workflows. Internal testing has included Google's Jetski coding platform, where Carbon has been evaluated for its ability to support complex programming tasks. The model is believed to build on Google's ongoing development of advanced reasoning and autonomous AI capabilities. Its potential applications include code generation, software debugging, technical problem-solving, and AI-assisted development workflows. Google has not publicly confirmed Carbon's architecture, context window, model specifications, release date, or commercial availability. -
23
OpenAI o3-mini-high
OpenAI
The o3-mini-high model from OpenAI advances AI reasoning by refining deep problem-solving in coding, mathematics, and complex tasks. It features adaptive thinking time with adjustable reasoning modes (low, medium, high) to optimize performance based on task complexity. Outperforming the o1 series by 200 Elo points on Codeforces, it delivers high efficiency at a lower cost while maintaining speed and accuracy. As part of the o3 family, it pushes AI problem-solving boundaries while remaining accessible, offering a free tier and expanded limits for Plus subscribers. -
24
ERNIE 4.5 Turbo
Baidu
ERNIE 4.5 Turbo, unveiled by Baidu at the 2025 Baidu Create conference, is a cutting-edge AI model designed to handle a variety of data inputs, including text, images, audio, and video. It offers powerful multimodal processing capabilities that enable it to perform complex tasks across industries such as customer support automation, content creation, and data analysis. With enhanced reasoning abilities and reduced hallucinations, ERNIE 4.5 Turbo ensures that businesses can achieve higher accuracy and reliability in AI-driven processes. Additionally, this model is priced at just 1% of GPT-4.5’s cost, making it a highly cost-effective alternative for enterprises looking for top-tier AI performance. -
25
ERNIE X1.1
Baidu
ERNIE X1.1 is Baidu’s upgraded reasoning model that delivers major improvements over its predecessor. It achieves 34.8% higher factual accuracy, 12.5% better instruction following, and 9.6% stronger agentic capabilities compared to ERNIE X1. In benchmark testing, it surpasses DeepSeek R1-0528 and performs on par with GPT-5 and Gemini 2.5 Pro. Built on the foundation of ERNIE 4.5, it has been enhanced with extensive mid-training and post-training, including reinforcement learning. The model is available through ERNIE Bot, the Wenxiaoyan app, and Baidu’s Qianfan MaaS platform via API. These upgrades are designed to reduce hallucinations, improve reliability, and strengthen real-world AI task performance. -
26
ERNIE 5.0
Baidu
ERNIE 5.0 is a next-generation conversational AI platform developed by Baidu, designed to deliver natural, human-like interactions across multiple domains. Built on Baidu’s Enhanced Representation through Knowledge Integration (ERNIE) framework, it fuses advanced natural language processing (NLP) with deep contextual understanding. The model supports multimodal capabilities, allowing it to process and generate text, images, and voice seamlessly. ERNIE 5.0’s refined contextual awareness enables it to handle complex conversations with greater precision and nuance. Its applications span customer service, content generation, and enterprise automation, enhancing both user engagement and productivity. With its robust architecture, ERNIE 5.0 represents a major step forward in Baidu’s pursuit of intelligent, knowledge-driven AI systems. -
27
OpenTelemetry
OpenTelemetry
High-quality, ubiquitous, and portable telemetry to enable effective observability. OpenTelemetry is a collection of tools, APIs, and SDKs. Use it to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior. OpenTelemetry is generally available across several languages and is suitable for use. Create and collect telemetry data from your services and software, then forward them to a variety of analysis tools. OpenTelemetry integrates with popular libraries and frameworks such as Spring, ASP.NET Core, Express, Quarkus, and more! Installation and integration can be as simple as a few lines of code. 100% Free and Open Source, OpenTelemetry is adopted and supported by industry leaders in the observability space. -
28
OpenAI Bel
OpenAI
OpenAI Bel is the reported codename of an unreleased artificial intelligence foundation model associated with OpenAI. Unofficial reports describe it as a large-scale pretraining project intended to support future generations of AI models. The project has been linked in speculative reporting to OpenAI's Astra model family and potential successors to GPT-6. Some sources claim that Bel contains more than 10 trillion parameters, although this figure has not been independently verified. OpenAI has not published official technical specifications, benchmark results, or documentation confirming the project's capabilities. Bel is not currently available as a publicly documented model through ChatGPT or the OpenAI API. -
29
Amazon CodeWhisperer
Amazon
Build apps faster with ML-powered coding companion. Accelerate application development with automatic code recommendations based on the code and comments in your IDE. Empower developers to use artificial intelligence (AI) responsibly to create syntactically correct and secure applications. Generate entire functions and logical code blocks without having to search and customize code snippets from the web. Stay focused and never leave the IDE, with real-time customized code recommendations for all your Java, Python, and JavaScript projects. Amazon CodeWhisperer is a machine learning (ML)–powered service that helps improve developer productivity by generating code recommendations based on their comments in natural language and code in the integrated development environment (IDE). Accelerate frontend and backend development by empowering developers with automatic code recommendations. Save time and effort by using CodeWhisperer to generate code to build and train your ML models.
