DeepInfra raises $107M Series B to scale the inference cloud — read the announcement
Published on 2026.02.02 by DeepInfraReliable JSON-Only Responses with DeepInfra LLMsWhen large language models are used inside real applications, their role changes fundamentally. Instead of chatting with users, they become infrastructure components: extracting information, transforming text, driving workflows, or powering APIs. In these scenarios, natural language is no longer the desired output. What applications need is structured data — and very often, that structure is […]
Published on 2026.02.02 by DeepInfraQwen API Pricing Guide 2026: Max Performance on a BudgetIf you have been following the AI leaderboards lately, you have likely noticed a new name constantly trading blows with GPT-4o and Claude 3.5 Sonnet: Qwen. Developed by Alibaba Cloud, the Qwen model family (specifically Qwen 2.5 and Qwen 3) has exploded in popularity for one simple reason: unbeatable price-to-performance. In 2025, Qwen is widely […]
Published on 2026.02.02 by DeepInfraNVIDIA Nemotron API Pricing Guide 2026While everyone knows Llama 3 and Qwen, a quieter revolution has been happening in NVIDIA’s labs. They have been taking standard Llama models and “supercharging” them using advanced alignment techniques and pruning methods. The result is Nemotron—a family of models that frequently tops the “Helpfulness” leaderboards (like Arena Hard), often beating GPT-4o while being significantly […]
Published on 2026.02.02 by DeepInfraBest API for Kimi K2.5: Why DeepInfra Leads in Speed, TTFT, and ScalabilityKimi K2.5 is positioned as Moonshot AI’s “do-it-all” model for modern product workflows: native multimodality (text + vision/video), Instant vs. Thinking modes, and support for agentic / multi-agent (“swarm”) execution patterns. In real applications, though, model capability is only half the story. The provider’s inference stack determines the things your users actually feel: time-to-first-token (TTFT), […]
Published on 2026.01.13 by DeepInfraPricing 101: Token Math & Cost-Per-Completion ExplainedLLM pricing can feel opaque until you translate it into a few simple numbers: input tokens, output tokens, and price per million. Every request you send—system prompt, chat history, RAG context, tool-call JSON—counts as input; everything the model writes back counts as output. Once you know those two counts, the cost of a completion is […]
Published on 2026.01.13 by DeepInfraFrom Precision to Quantization: A Practical Guide to Faster, Cheaper LLMsLarge language models live and die by numbers—literally trillions of them. How finely we store those numbers (their precision) determines how much memory a model needs, how fast it runs, and sometimes how good its answers are. This article walks from the basics to the deep end: we’ll start with how computers even store a […]
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