Developers evaluating an inference platform need more than raw speed. They need a catalog that covers reasoning, code, vision, and multimodal tasks without forcing them to stitch together multiple vendors. Oxlo.ai offers 45+ open-source and proprietary models across seven categories, all behind a single API with flat per-request pricing. Because cost does not scale with token count, long-context prompts and agentic loops that might be prohibitively expensive on token-based providers become predictable workloads. Every endpoint is fully OpenAI SDK compatible, so switching existing applications requires only a base URL change.
Reasoning and Chat LLMs
The core of the Oxlo.ai catalog is a deep bench of text models built for general conversation, reasoning, and autonomous agent workflows.
For deep reasoning and complex coding, DeepSeek R1 671B MoE delivers chain-of-thought performance that handles mathematical proofs, system design, and multi-step debugging. DeepSeek V4 Flash adds a one-million-token context window with efficient MoE inference, making it ideal for analyzing entire codebases, long legal documents, or extended conversation histories without truncation. DeepSeek V3.2 focuses on coding and reasoning and is available on the free tier, so you can validate logic-intensive tasks before committing to a paid plan.
On the agentic front, GLM 5 is a 744B MoE model built for long-horizon tasks that require planning, tool selection, and memory across many turns. Qwen 3 32B offers strong multilingual reasoning and native agent workflow support, while Minimax M2.5 targets coding and tool use. Kimi K2.6 brings advanced reasoning, agentic coding, and vision together behind a 131K context window. Its siblings, Kimi K2.5 and Kimi K2 Thinking, specialize in advanced chain-of-thought reasoning for problems that benefit from explicit intermediate steps.
For general-purpose workloads, Llama 3.3 70B serves as the flagship default, and GPT-Oss 120B offers a large open-source GPT-class alternative. Mistral models round out the selection for users who need efficient European-origin weights. Use cases here range from high-volume customer support bots and internal knowledge assistants to research agents that iterate over hundreds of pages of source material.
Code Generation Models
Software engineering workloads often involve prompts that span thousands of tokens, whether you are passing an entire file tree, a lengthy diff, or detailed system prompts to a coding agent. Oxlo.ai flattens that cost structure so input length does not inflate your bill.
Qwen 3 Coder 30B is optimized for software generation and refactoring across dozens of languages. DeepSeek Coder remains a reliable choice for autocomplete and inline suggestion pipelines. For latency-sensitive environments such as IDE plugins or CI/CD review bots, Oxlo.ai Coder Fast trims overhead while preserving syntax accuracy. These models support function calling and JSON mode, so you can generate structured test cases, dependency graphs, or configuration files directly from natural language requirements.
Vision and Multimodal Models
Multimodal inference is increasingly a requirement, not a luxury. Oxlo.ai provides vision-capable models without a separate API or proprietary data format.
Gemma 3 27B handles visual question answering, chart interpretation, and UI element recognition with open weights. Kimi VL A3B integrates vision with the advanced reasoning capabilities of the Kimi family, making it suitable for document parsing from screenshots, automated accessibility auditing, and visual debugging of front-end layouts. Because the platform exposes standard chat completions with image input, you can pass base64-encoded frames or image URLs exactly as you would with the OpenAI SDK.
Image Generation and Media Models
Beyond text and vision understanding, Oxlo.ai runs generative and transcription models for full-stack creative pipelines.
For image generation, Oxlo.ai Image Pro and Oxlo.ai Image Ultra provide high-fidelity output for marketing and product design. The catalog also includes Flux.1, SDXL, and Stable Diffusion 3.5, giving teams the freedom to match a specific aesthetic or licensing requirement without managing GPU workers.
On the audio side, Whisper Large v3, Whisper Turbo, and Whisper Medium cover transcription workloads from high-accuracy legal dictation to near real-time meeting summarization. Kokoro 82M is a compact text-to-speech model that produces natural-sounding voice output for assistants and audiobook pipelines. All audio endpoints follow the standard OpenAI format, so existing Whisper or TTS client code ports without refactoring.
Embeddings and Specialized Tasks
Retrieval and perception workloads need specialized encoders and detectors that are often hosted on separate infrastructure. Oxlo.ai keeps them on the same API.
BGE-Large and E5-Large provide high-quality text embeddings for retrieval-augmented generation, semantic search, and recommendation systems. For computer-vision pipelines, YOLOv9 and YOLOv11 offer real-time object detection suitable for inventory monitoring, safety compliance, and robotics perception. Serving these from the same provider simplifies routing, authentication, and billing.
Integrating Oxlo.ai Into Your Stack
Oxlo.ai is designed as a drop-in replacement for existing OpenAI SDK implementations. The base URL is https://api.oxlo.ai/v1, and the platform supports streaming, function calling, JSON mode, multi-turn conversations, and vision input out of the box.
Below is a minimal Python example that streams a reasoning response. Changing providers is literally two lines: the base URL and the model name.
from openai import OpenAI
client = OpenAI(
base_url="https://api.oxlo.ai/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="deepseek-r1-671b",
messages=[
{"role": "system", "content": "You are a careful reasoning assistant."},
{"role": "user", "content": "Explain the tradeoffs between MoE and dense transformer architectures."}
],
stream=True
)
for chunk in response:
print(chunk.choices[0].delta.content or "", end="")
Because there are no cold starts on popular models, the first request after idle time returns at full speed. This matters for agentic systems that may issue bursts of tool calls separated by unpredictable user delays.
Pricing and Workload Fit
Model variety is only useful if the pricing model matches your traffic pattern. Oxlo.ai uses request-based pricing, which means one flat cost per API call regardless of prompt length. For long-context retrieval, agent loops with heavy tool history, or code generation with full-file context, this structure avoids the ballooning bills common on token-based platforms.
The Free plan offers $0 per month, 60 requests per day, and access to 16+ models including DeepSeek V3.2. It also includes a 7-day full-access trial so you can benchmark premium models against your own datasets. The Pro plan at $80 per month provides 1,000 requests per day across all models. Premium at $350 per month raises that to 5,000 requests per day with priority queue access. For teams that need unlimited volume, dedicated GPUs, or guaranteed infrastructure, Enterprise plans are custom and include a commitment to beat your current provider by at least 30 percent. See exact rates on the Oxlo.ai pricing page.
Conclusion
Oxlo.ai aggregates 45+ models across chat, reasoning, code, vision, image generation, audio, embeddings, and object detection into a single, OpenAI-compatible API. Flat per-request pricing removes the cost penalty for long inputs and agentic loops, while the absence of cold starts keeps latency predictable. Whether you are building a coding assistant, a multimodal agent, or a high-volume transcription pipeline, the model breadth and pricing structure make Oxlo.ai a genuinely relevant option to evaluate.
