AI Model Families
Explore leading foundation models grouped by family lineage and provider. Access every model through a unified OpenAI-compatible endpoint with transparent Algerian Dinar (DZD) billing.
Qwen
Qwen API Models for Text, Vision, Speech and Embeddings
Qwen is the most complete open model family available today, and completeness is the point. Alibaba releases not one flagship but a full spectrum — dense models small enough to serve at volume alongside sparse models in the trillion-parameter class, plus dedicated vision, speech recognition, text-to-speech, and embedding models. They share one API surface, one set of conventions, and in most cases a permissive licence, which makes moving between them a configuration change rather than a rewrite. On DEVUP AI the whole family is reachable through a single OpenAI-compatible endpoint, billed in Algerian Dinar.
OpenAI
OpenAI API Models for Reasoning, Coding and Multimodal AI
OpenAI's models cover more surface than any other family in this catalogue: reasoning and coding models across three capability tiers, image generation and editing, realtime speech, high-accuracy transcription, and text embeddings. The reasoning models share one property that shapes how they are used — deliberation is a per-request setting rather than a property of the model, so the same identifier can serve a real-time endpoint and a long analytical job. They accept text and images against context windows beyond a million tokens, support structured outputs and function calling, and are reachable on DEVUP AI through the standard OpenAI-compatible endpoint, billed in Algerian Dinar.
Claude
Claude API Models for Coding, Agents and Production Work
Claude is Anthropic's family of frontier models, built around a distinctive priority: that a model used for real work should be reliable, honest about what it does not know, and safe to give responsibility to. The family spans a capability tier for hard problems, a balanced tier for production traffic, and a fast tier for high-volume paths — all sharing one interface, extended reasoning, vision input, and tool use. On DEVUP AI they are reachable through both the standard OpenAI-compatible endpoint and Anthropic's native Messages API, which means Claude Code and the official SDKs work directly against your account, billed in Algerian Dinar.
DeepSeek
DeepSeek API Models for Reasoning, Coding and Long-Context Work
DeepSeek builds open-weight frontier models around a single engineering constraint: making very long context economically real. From Multi-head Latent Attention through to today's hybrid sparse and compressed attention stacks, every generation has attacked the two costs that make million-token inference impractical — per-token compute and key-value cache size. The result is a family that spans direct-answer chat models and deep reasoning systems with switchable effort levels, all sharing one API surface. Available on DEVUP AI through a single OpenAI-compatible endpoint.
Gemini
Gemini API Models for Multimodal and Long-Context Work
Gemini is Google's family of multimodal models, and multimodal here means what it sounds like: text, images, video, audio, and PDFs go in directly, against context windows measured in millions of tokens, with no extraction layer in front. The family spans a deep-reasoning tier, a workhorse Flash tier tuned for coding and agentic execution, and a lightweight tier for high-volume paths, all sharing one interface with thinking depth set per request. One integration note worth knowing before your first call: recent Flash models no longer accept sampling parameters. On DEVUP AI the family is reachable through the standard OpenAI-compatible endpoint, billed in Algerian Dinar.
Llama
Llama API Models with Open Weights for Production AI
Llama is Meta's family of open-weight models, and its influence is easiest to measure by what was built around it. The tooling most developers use to run, quantize, and fine-tune models locally was written for Llama first. More fine-tuned derivatives exist for this family than for any other. It spans a wider range of sizes than any competing line — from models small enough for a laptop to sparse Mixture-of-Experts systems with context windows in the millions — with native multimodal input in the current generation. On DEVUP AI the family is reachable through the standard OpenAI-compatible endpoint, billed in Algerian Dinar.
Flux
FLUX — The Image Models Built to Be Built On
FLUX is a family of image generation models from Black Forest Labs, and it became the default across the open ecosystem for a specific reason: the tooling grew around it. Adapters, fine-tunes, and workflows target FLUX first, which makes it the shortest path from an idea to a working image pipeline. The family spans a fast tier for high-volume generation through to flagship models with precise prompt adherence and reliable text rendering inside the image. On DEVUP AI it is the default engine behind the image generation endpoint, called with one API key and billed in Algerian Dinar.
GLM
GLM API Models for Agentic Coding and Complex Engineering
GLM is Z.ai's family of open-weight models, and it is aimed squarely at engineering: repository-scale coding, terminal automation, and long-horizon agent execution rather than chat. The family makes an argument worth noticing — that beyond a certain scale, capability comes from post-training on verifiable, executable environments rather than from a larger foundation, and its recent releases demonstrate that on identical base weights. Models here hold a million-token context through hybrid attention designs built specifically to make that window affordable, with reasoning depth selectable per request. On DEVUP AI the family is reachable through the standard OpenAI-compatible endpoint, billed in Algerian Dinar.
Kimi
Kimi API Models for Long-Context and Agentic Work
Kimi is Moonshot AI's family of open-weight frontier models, and it is built for a specific shape of work: tasks measured in hours rather than turns. Sustained engineering sessions across large repositories, terminal orchestration, multi-step research, and document-heavy knowledge work. The flagship is the first open model in the trillion-parameter class, with native vision and a million-token context, yet it activates only a small fraction of its parameters on any given token. Unlike most frontier systems, the architecture is published rather than described. On DEVUP AI the family is reachable through the standard OpenAI-compatible endpoint, billed in Algerian Dinar.
Gemma
Open Models From the Research Behind Gemini
Gemma is Google's family of open-weight models, built from the same research and technology as Gemini. That lineage is the point: capability developed for a frontier model, released in sizes you can actually run and inspect. The family spans a wide range, from models small enough for a single consumer GPU to mid-size models that handle serious production work — all sharing one interface, so moving between them is a configuration change rather than a rewrite. On DEVUP AI they are reachable through the standard OpenAI-compatible endpoint with one API key, billed in Algerian Dinar.
Nemotron
Open Weights, Open Data, Open Recipes
NVIDIA's open models open more than most: the weights, the training data, and the recipes that produced them. Major portions of both the pre-training and post-training corpora are published as datasets you can inspect, alongside the end-to-end training procedure — which makes these the rare models you can reproduce rather than only consume. They are built for agents specifically, with a hybrid architecture interleaving Mamba-2 and mixture-of-experts layers to raise throughput on high-volume workloads. On DEVUP AI they are reachable through the standard OpenAI-compatible endpoint, billed in Algerian Dinar.
Bria
Image Models You Can Deploy Without a Legal Question
Bria builds image models trained exclusively on licensed, rights-cleared data — and licenses the foundation model with commercial liability coverage attached. For a company putting generated imagery into a product, an advertisement, or a publication, that provenance answers a question most image models leave open. The family also takes a distinctive technical approach: structured JSON prompts instead of free-form text, which separates lighting from composition from camera settings so that changing one does not disturb the others. The same input reproduces the same output, making edits auditable rather than probabilistic. On DEVUP AI they run through the standard images endpoint, billed in Algerian Dinar.
Mistral
Mistral — Open Models for Text and Speech
Five Mistral models on DEVUP AI: three instruction-tuned text models from Nemo up to Small 3.2 with 128K context, and two Voxtral speech recognition models priced per minute. European open-weight models through one OpenAI-compatible API key, billed in Algerian Dinar.
Wan-AI
Open Video Generation, Built for Production Use
Wan-AI is Alibaba Tongyi Lab's family of video generation models, and it became the open-weight reference for turning text into moving pictures. The line covers text-to-video, image-to-video, reference-driven generation, and video editing, with recent generations unifying what previously required separate models for each task. Clips run to seconds rather than frames, with audio generated alongside the picture in the newest releases and reference inputs spanning images, audio, video, and documents. On DEVUP AI they run through the video generation endpoint — one API key, one request, billed in Algerian Dinar.
