--- title: Interfaze thumbnail: >- https://cdn-uploads.huggingface.co/production/uploads/62fb53b572a7ab50b4b06fca/II4KdeJkepE_NOg9HNnq_.jpeg short_description: The AI model built for deterministic developer tasks --- ![Extraction](https://interfaze.ai/banner.png) # The AI model built for deterministic developer tasks Interfaze is an AI model built on a new architecture that merges specialized DNN/CNN models with LLMs for developer tasks that require deterministic output and high consistency like OCR, scraping, classification, web search and more. [Try now](https://interfaze.ai/dashboard) or [Read paper](https://www.arxiv.org/abs/2602.04101) - OCR, web scraping, web search, classification and more - OpenAI chat completion API compatible - High accuracy structured output consistency - Built-in code execution and sandboxing - Custom web engine for scraping and web research capabilities - Auto reasoning when needed - Controllable guardrails - Fully managed and scalable - Globally distributed fallback system with high uptime ### Model Comparison | Benchmark | interfaze-beta | GPT-4.1 | Claude Sonnet 4 | Gemini 2.5 Flash | Claude Sonnet 4 (Thinking) | Claude Opus 4 (Thinking) | GPT-5-Minimal | Gemini-2.5-Pro | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | MMLU-Pro | 83.6 | 80.6 | 83.7 | 80.9 | 83.7 | 86 | 80.6 | 86.2 | | MMLU | 91.38 | 90.2 | - | - | 88.8 | 89 | - | 89.2 | | MMMU | 77.33 | 74.8 | - | 79.7 | 74.4 | 76.5 | - | 82 | | AIME-2025 | 90 | 34.7 | 38 | 60.3 | 74.3 | 73.3 | 31.7 | 87.7 | | GPQA-Diamond | 81.31 | 66.3 | 68.3 | 68.3 | 77.7 | 79.6 | 67.3 | 84.4 | | LiveCodeBench | 57.77 | 45.7 | 44.9 | 49.5 | 65.5 | 63.6 | 55.8 | 75.9 | | ChartQA | 90.88 | - | - | - | - | - | - | - | | AI2D | 91.51 | 85.9 | - | - | - | - | - | 89.5 | | Common-Voice-v16 | 90.8 | - | - | - | - | - | - | - | \*Results for Non-Interfaze models are sourced from model providers, leaderboards, and evaluation providers such as Artificial Analysis. ### Works like any other LLM OpenAI API compatible, works with every AI SDK out of the box ``` import OpenAI from "openai"; const interfaze = new OpenAI({ baseURL: "https://api.interfaze.ai/v1", apiKey: "" }); const completion = await interfaze.chat.completions.create({ model: "interfaze-beta", messages: [\ {\ role: "user",\ content: "Get the company description of JigsawStack from their linkedin page",\ },\ ], }); console.log(completion.choices[0].message.content); ``` ### OCR & Document Extraction [vision docs ->](https://interfaze.ai/docs/vision) ``` prompt = "Get the person information from the following ID." schema = z.object({ first_name: z.string(), last_name: z.string(), dob: z.string(), expiry: z.string(), }); ``` ![Extraction](https://interfaze.ai/examples/extraction_example.png) ### Smart Web Scraping [web docs ->](https://interfaze.ai/docs/web) ``` prompt = "Extract the information from Yoeven D Khemlani's linkedin page based on the schema." schema = z.object({ first_name: z.string(), last_name: z.string(), about: z.string(), current_company: z.string(), current_position: z.string(), }); ``` ![scraping](https://interfaze.ai/examples/scraper_example.png) ### Translation [translation docs ->](https://interfaze.ai/docs/translation) ``` prompt = "The UK drinks about 100–160 million cups of tea every day, and 98% of tea drinkers add milk to their tea." schema = z.object({ zh: z.string(), hi: z.string(), es: z.string(), fr: z.string(), de: z.string(), it: z.string(), ja: z.string(), ko: z.string(), }); ``` ``` zh: 英国每天饮用约100–160百万杯茶，有98%的茶饮者在茶中加入牛奶。 hi: यूके हर दिन लगभग 100–160 मिलियन कप चाय पीता है, और 98% चाय पीने वाले अपनी चाय में दूध मिलाते हैं। es: El Reino Unido bebe alrededor de 100–160 millones de tazas de té cada día, y el 98 % de los consumidores de té añade leche a su té. fr: Le Royaume-Uni boit environ 100–160 millions de tasses de thé chaque jour, et 98 % des buveurs de thé ajoutent du lait à leur thé. de: Das Vereinigte Königreich trinkt etwa 100–160 Millionen Tassen Tee pro Tag, und 98 % der Teetrinker fügen ihrem Tee Milch hinzu. it: Il Regno Unito beve circa 100–160 milioni di tazze di tè ogni giorno e il 98% degli amanti del tè aggiunge latte al proprio tè. ja: イギリスでは毎日約100～160百万杯の紅茶が飲まれており、紅茶を飲む人の98%が紅茶に牛乳を加えます。 ko: 영국에서는 매일 약 1억 ~ 1억 6천만 잔의 차를 마시며, 차를 마시는 사람의 98%가 차에 우유를 넣습니다. ``` ### Speech-to-text (STT) and diarization [stt docs ->](https://interfaze.ai/docs/speech-to-text) ``` prompt = "Transcribe https://jigsawstack.com/preview/stt-example.wav" schema = z.object({ text: z.string(), speakers: z.object({ id: z.string(), start: z.number(), end: z.number() }) }); ``` ``` { "text": " The little tales they tell are false The door was barred, locked and bolted as well Ripe pears are fit for a queen's table A big wet stain was on the round carpet The kite dipped and swayed but stayed aloft The pleasant hours fly by much too soon The room was crowded with a mild wob The room was crowded with a wild mob This strong arm shall shield your honour She blushed when he gave her a white orchid The beetle droned in the hot June sun", "speakers": [\ {\ "start":0,\ "end":4.78,\ "id": "SPEAKER_00"\ },\ {\ "start":4.78,\ "end":9.48,\ "id": "SPEAKER_00"\ },\ {\ "start":9.48,\ "end":13.06,\ "id": "SPEAKER_00"\ },\ {\ "start":13.06,\ "end":17.24,\ "id": "SPEAKER_00"\ },\ {\ "start":17.24,\ "end":21.78,\ "id": "SPEAKER_00"\ },\ {\ "start":21.78,\ "end":26.3,\ "id": "SPEAKER_00"\ },\ {\ "start":26.3,\ "end":30.76,\ "id": "SPEAKER_00"\ },\ {\ "start":30.76,\ "end":35.08,\ "id": "SPEAKER_00"\ },\ {\ "start":35.08,\ "end":39.24,\ "id": "SPEAKER_00"\ },\ {\ "start":39.24,\ "end":43.94,\ "id": "SPEAKER_00"\ },\ {\ "start":43.94,\ "end":48.5,\ "id": "SPEAKER_00"\ }\ ] } ``` ### Configurable guardrails and NSFW checks [guardrails docs ->](https://interfaze.ai/docs/guard-rails) Fully configurable guardrails for text and images ``` S1: Violent Crimes S2: Non-Violent Crimes S3: Sex-Related Crimes S4: Child Sexual Exploitation S5: Defamation S6: Specialized Advice S7: Privacy S8: Intellectual Property S9: Indiscriminate Weapons S10: Hate S11: Suicide & Self-Harm S12: Sexual Content S12_IMAGE: Sexual Content (Image) S13: Elections S14: Code Interpreter Abuse ``` ### Architecture [read paper ->](https://www.arxiv.org/abs/2602.04101) This architecture combines a suite of small specialized models supported with custom tools and infrastructure while automatically routing to the best model for the task that prioritizes accuracy and speed. ![How it works](https://interfaze.ai/examples/howitworks.png) ### Specs - Context window: 1m tokens - Max output tokens: 32k tokens - Input modalities: Text, Images, Audio, File, Video - Reasoning: Available ### Research references - [Interfaze: The Future of AI is built on Task-Specific Small Models](https://www.arxiv.org/abs/2602.04101) - [Agentic Context Engineering](https://www.arxiv.org/pdf/2510.04618) - [Small Language Models are the Future of Agentic AI](https://arxiv.org/pdf/2506.02153) - [The Sparsely-Gated Mixture-of-Experts Layer](https://arxiv.org/pdf/1701.06538) - [DeepSeekMoE](https://arxiv.org/pdf/2401.06066) - [Confronting LLMs with Traditional ML](https://arxiv.org/pdf/2310.14607) ### Who are we? We are a small team of ML, Software and Infrastructure engineers engrossed in the fact that a small model can do a lot more when specialized. Allowing us to make AI available in every dev workflow.