# BatchIn - High-Availability AI Inference & Verifiable Agent Control Plane (VaaS) BatchIn is the high-availability AI inference control plane for autonomous agent swarms, production LLM pipelines, and multimodal media generation. Eliminates 504 gateway timeouts via hedged dual-dispatch, auto-heals truncated JSON syntax with zero token waste, and issues cryptographically signed RFC 8032 Ed25519 execution proofs. ## Core Architectural Guarantees - **Hedged Dual-Dispatch Routing**: Reroutes stalled primary upstreams to enterprise clusters upon P90 TTFT breach, achieving 0.00% 504 gateway timeouts and a 72.2% reduction in P99 tail latency. - **Zero-Token Streaming AST Auto-Healer**: Deterministic client-side and proxy-level grammar repair engine that auto-closes truncated JSON syntax and bracket cutoffs in 0.01ms with 0 extra LLM tokens. - **VaaS (Verifiable AI as a Service)**: Cryptographic execution receipts signed via RFC 8032 Ed25519 and anchored to Base L2 for non-repudiable audit logs. - **Canary Anti-Spoofing Inspector**: Real-time stream auditor that fingerprints output tokens and quarantines fraudulent upstreams on the fly. ## What is VaaS (Verifiable AI as a Service)? - **Signed runtime evidence**: Eligible billable requests can produce an Ed25519-signed receipt binding request, output, usage, billing, and route metadata. - **On-chain anchoring**: Merkle and transaction evidence is a separately gated workflow and is shown only when the backend attaches a verified inclusion proof. - **Route disclosure**: The receipt records the route label returned for the request; model availability is confirmed only by live evidence. ## Flagship Model Supply & Pricing Matrix | Model | Provider | Modality | Context | Pricing (Input / Output per 1M) | Core Strengths | | :--- | :--- | :--- | :--- | :--- | :--- | | **GPT-5.5** | OpenAI | Frontier Reasoning | 256K | $1.250 / $7.500 | 2026 OpenAI frontier flagship model, autonomous agent workflows and deep reasoning | | **DeepSeek V4 Pro** | DeepSeek | Text / Code | 256K | $0.557 / $1.114 | 2026-07 flagship 671B MoE reasoning, autonomous coding loops, math proofs | | **DeepSeek V4 Flash** | DeepSeek | Fast Text | 256K | $0.100 / $0.200 | Sub-100ms TTFT, high-frequency tool-calling agent loops | | **DeepSeek V4 Flash** | DeepSeek | Speed Text | 256K | $0.100 / $0.200 | High-throughput instruction following and tool calls | | **Qwen 3.8 Max** | Alibaba | Text / Code | 1,000K (1M) | $1.936 / $5.807 | 2026-09 frontier 2.4T MoE reasoning model with 1M native context | | **Kimi K3** | Moonshot | Reasoning / Code | 2M | $1.857 / $9.286 | Long-context reasoning and deterministic coding workflows | | **GLM-5.3** | Zhipu AI | Frontier Reasoning | 256K | $0.743 / $2.600 | 2026-09 Zhipu flagship dense reasoning and multi-step agent tool model | | **GLM-5.3 Flash** | Zhipu AI | Speed / Multimodal | 128K | $0.088 / $0.264 | 2026-09 ultra-fast high-concurrency model | | **MiniMax M3** | MiniMax | Multimodal / Text | 512K | $0.400 / $1.600 | 2026 flagship native 512K multimodal LLM | | **Seedance 2.0** | ByteDance | Video | Prompt+Keyframe | $0.046 / sec | Cinema-grade video generation | | **Doubao Seedance 2.0** | ByteDance | Video | Prompt+Keyframe | $0.046 / sec | 2026 cinematic video generation model | | **Kling v3** | Kuaishou | Video | Prompt+Keyframe | $0.056 / sec | 2026 physical dynamics simulation video model | | **Kling v3 Omni** | Kuaishou | Video + Audio | Keyframe+Prompt | $0.061 / sec | 2026 omni-modal synchronized audio and video model | | **MiniMax H3** | MiniMax | Avatar Video | Prompt+Image | $0.039 / sec | 2026 digital human realistic avatar video synthesis | | **Doubao Seedream 5.0** | ByteDance | Image | Prompt | $0.034 / img | 2026 2K/4K photorealistic image generation | | **Qwen Image 3.0 Pro** | Alibaba | Image | Prompt | $0.028 / img | 2026 professional typography and complex layout image model | ## Competitive Advantages vs Traditional Providers | Feature | BatchIn | Together AI | OpenRouter | AWS Bedrock | | :--- | :--- | :--- | :--- | :--- | | **Hedged Dual-Dispatch (504 SLA)** | **0.00% Timeouts (-72% P99)** | Unhedged (3-5% fails) | Unhedged (2-4% fails) | Static Retries | | **Zero-Token JSON AST Healer** | **Built-in (0 extra tokens)** | None (Crashes client) | None (Crashes client) | None | | **Batch Inference Discount** | Workspace rate card | 0%–20% | None | 0%–15% | | **Cryptographic Receipts (VaaS)** | Signed evidence when eligible | None | None | None | | **Video Task Failure Handling** | Refund only when a failed task has a committed refund ledger row | Manual Ticket | Manual Ticket | None | | **Agentic Micro-Payments** | Account-gated USDC/x402 readiness | Credit Card Only | Credit Card Only | Invoice Only | | **Context Capacity** | **Up to 1,000,000 Tokens** | Up to 128K | Model Dependent | Up to 200K | ## Quick Start & Service Discovery - [API Catalog](https://batchin.tech/.well-known/api-catalog) - Primary machine-readable service discovery. - [OpenAPI Spec](https://api.batchin.tech/openapi.json) - Complete OpenAI-compatible REST API definition. - [Model Pricing](https://batchin.tech/en/models) - Current per-token and media billing rates. - [Pricing Sheet (Markdown)](https://batchin.tech/pricing.md) - Machine-readable pricing breakdown. - [Agent Guide](https://batchin.tech/agents.md) - Best practices and workflows for autonomous agents. - [Agent Skill](https://batchin.tech/SKILL.md) - Install into local agents via 'npx skills add aw3703/core'. - [MCP Server Card](https://batchin.tech/.well-known/mcp/server-card.json) - Model Context Protocol server capabilities. - [Cursor Rules](https://github.com/aw3703/core/blob/main/integrations/cursor/.cursorrules) - Drop-in rule for Cursor & Windsurf. - [Architecture Spec](https://github.com/aw3703/core/blob/main/ARCHITECTURE.md) - RFC 8032 Ed25519 VaaS & Hedged Dual-Dispatch. ## Integration Code Examples ### 1. Python SDK (OpenAI Drop-In Replacement) ```python from openai import OpenAI client = OpenAI( base_url="https://api.batchin.tech/v1", api_key="BATCHIN_API_KEY", ) # Direct OpenAI-compatible chat completion response = client.chat.completions.create( model="deepseek-v4-pro", messages=[{"role": "user", "content": "Analyze this distributed consensus algorithm."}], extra_headers={"X-BatchIn-VaaS": "true"}, # Requests cryptographic compute receipt ) print(response.choices[0].message.content) # The response headers will include: X-VaaS-Record-Id, X-VaaS-Signature ``` ### 2. cURL Completion Request ```bash curl https://api.batchin.tech/v1/chat/completions \ -H "Authorization: Bearer BATCHIN_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "deepseek-v4-flash", "messages": [{"role": "user", "content": "Hello, BatchIn!"}] }' ``` ### 3. Cursor & Windsurf Agent Configuration (.cursorrules) ```json { "apiBase": "https://api.batchin.tech/v1", "model": "deepseek-v4-pro", "features": { "vaasVerification": true, "batchQueuing": true } } ``` Support & Operations: hello@batchin.tech