DeepInfra raises $107M Series B to scale the inference cloud — read the announcement
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Published on 2026.07.21 by DeepInfraWe Benchmarked NVIDIA Vera, the CPU for Agents. Here's What We MeasuredDeepInfra runs AI agents in production, so when NVIDIA built a CPU for agents, we measured it ourselves with our own harness, our own agent, and a methodology we locked before the hardware arrived.
Published on 2026.07.16 by Aray SultanbekovaDeepInfra Now Serves NVIDIA Nemotron 3 Embed: Frontier Retrieval for RAG and AgentsDeepInfra now serves NVIDIA Nemotron 3 Embed, the industry's leading open embedding model for enterprise search and agentic retrieval, available today in both 8B and 1B sizes.
Published on 2026.07.14 by DeepInfraIntroducing the Flex Service Tier: Cheaper Inference When You Can WaitRun latency-tolerant work at 0.8× real-time — best-effort, sheddable, same OpenAI-compatible API.
Published on 2026.07.08 by Aray SultanbekovaFrontier-Level Agents on Open Models: LangChain Deep Agents + NVIDIA Nemotron 3 Ultra, Live on DeepInfraOpen models have reached frontier-level agent performance. Starting today, you can point LangChain Deep Agents at NVIDIA Nemotron 3 Ultra running on DeepInfra and get top-tier agent accuracy at roughly 10x lower cost than leading closed models.
Published on 2026.07.01 by DeepInfraBest SaaS Tools and API Providers for MiMo-V2.5As LLM architectures grow increasingly complex, the introduction of the MiMo-V2.5 series represents a significant step forward in multimodal capabilities and massive context handling. Integrating a model with a 1M-token context window and native multimodal support (image, video, audio, text) introduces substantial infrastructure considerations. For developers and enterprise architects, the priorities are clear: managing inference […]
Published on 2026.07.01 by DeepInfraMiMo-V2.5 Model Documentation and Integration GuideMiMo-V2.5 is a native omnimodal model developed by XiaomiMiMo, designed to process and understand text, image, video, and audio through a unified architecture rather than relying on “bolted-on” components for each modality. Built on a 310-billion-parameter Sparse Mixture of Experts (MoE) architecture — with only 15 billion parameters activated during inference — MiMo-V2.5 offers a […]
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