Open-Source Inference, Instant Intelligence.
Blazing-fast inference for Llama, Qwen, Mistral and more. Full-stack RAG pipelines with hybrid search and grounded citations. Deploy in seconds.
from tensoras import Tensoras
# One line to instant intelligence
client = Tensoras()
response = client.chat.completions.create(
model="llama-3.3-70b",
messages=[{"role": "user", "content": "Hello!"}]
)Trusted by teams building with
Deployment
Deploy anywhere, your way
Choose the deployment model that matches your compliance, latency, and cost requirements.
Cloud API
Start in seconds with our global edge network. No infrastructure to manage.
- Pay-per-token pricing
- Auto-scaling to zero
- Global edge PoPs
- 99.9% uptime SLA
- OpenAI-compatible endpoint
Dedicated Cluster
Reserved GPU capacity with guaranteed throughput and single-tenant isolation.
- Reserved A100 / H100 GPUs
- Custom model fine-tuning
- Single-tenant isolation
- Private networking (VPC)
- Dedicated support engineer
Self-Hosted
Run the Tensoras engine in your own cloud or on-prem with Docker & Kubernetes.
- Docker & Helm charts
- Air-gapped deployments
- Full data sovereignty
- Bring your own GPUs
- Community + Enterprise support
Capabilities
Everything you need for production AI
From low-latency inference to knowledge-grounded retrieval, Tensoras covers the full stack.
Instant Answers
Sub-200ms time-to-first-token with speculative decoding and continuous batching. Stream responses the moment they start generating.
Agents That Never Stall
Built for agentic loops with tool-use, function calling, and structured JSON output. Keep chains of thought flowing without timeouts.
Code at Speed of Thought
Optimized serving for code models with fill-in-the-middle, multi-file context, and inline completions. Perfect for AI-assisted development.
RAG Pipelines in Minutes
Ingest from 15+ data sources, auto-chunk with smart strategies, embed with state-of-the-art models, and retrieve with hybrid search.
Hybrid Search Built-In
Combine dense vector similarity with BM25 keyword search and reciprocal rank fusion. No external search engine required.
Citations & Grounding
Every RAG response comes with source citations, chunk references, and confidence scores. Verify claims with a single click.
Intelligent Routing
Automatically route prompts to the optimal model based on complexity. Save up to 30% on costs with zero code changes — just use model: "auto".
MCP Tool Integration
Connect external tools via the Model Context Protocol. Your models can call APIs, query databases, and access live data through standardized MCP servers.
Code Execution
Built-in Python sandbox for data analysis, charts, and computation. gVisor-secured, scales to zero.
Audio APIs
Speech-to-text with Whisper Large v3 (98+ languages) and text-to-speech with Kokoro. OpenAI-compatible endpoints, per-minute pricing.
Realtime API
Bidirectional WebSocket for real-time voice conversations. Server-side VAD, streaming STT and TTS, OpenAI-compatible protocol.
Image Generation
Generate images from text with FLUX.1 Schnell. Multiple sizes, quality options, and base64 or URL output. Scales to zero when idle.
Structured Outputs
Guarantee valid JSON with JSON Schema enforcement. Perfect for extracting data, building pipelines, and ensuring type-safe responses every time.
Embeddings & Reranking
Generate embeddings with BGE Large and rerank results with cross-encoder models. Full OpenAI-compatible endpoints for vector search pipelines.
Content Moderation
Configurable guardrail policies with category thresholds, topic deny-lists, and real-time content filtering. Block or warn on harmful content automatically.
Batch Processing
Submit large workloads as batch jobs with automatic retries and progress tracking. Process thousands of requests at reduced cost with the Batches API.
Fine-tuning
Fine-tune open-source models on your data with LoRA. Track training runs, manage checkpoints, and deploy custom models to production.
Webhooks
Get notified about async events with 14 webhook event types. Track batch completions, ingestion jobs, fine-tuning progress, and more in real time.
Security & IP Allowlisting
Restrict API access by IP range, configure per-org guardrail policies, audit every request, and manage API key scopes for fine-grained access control.
Performance
Benchmarked against the fastest
Output tokens per second on standard chat workloads. Higher is better.
Measured on standard chat completion workload, 256 input / 512 output tokens
tokens / secRAG Pipeline
From raw data to grounded answers
A fully managed pipeline that ingests, embeds, indexes, retrieves, and generates -- with citations on every response.
Data Sources
S3, Postgres, Confluence, Notion, Kafka
Ingestion
Parse, clean, smart chunking
Embeddings
BGE, E5, Cohere, OpenAI
Vector Store
Built-in hybrid index
Retrieval
Semantic + BM25 + RRF
LLM
Tensoras inference
Citations
Grounded, verifiable output
Supported data sources
Developer
For production workloads with pay-as-you-go
- 5% usage discount
- All models (70B+, vision, code)
- 25 RAG knowledge bases
- 25 GB vector storage
- 100 GB document storage
- SSO authentication
- Hybrid search + reranking
- Streaming & function calling
- Code execution (120s max)
- Email + Discord support
- 99.9% uptime SLA
Testimonials
Loved by engineers
“We migrated from our DIY vLLM setup to Tensoras and cut our P95 latency by 60%. The OpenAI-compatible API made the switch trivial.”
Sarah Chen
Head of AI, Dataflow Labs