Modal vs Ollama

Modal Hits $1B ARR, Raises $750M Series D at $15.75B Valuation

Modal, an AI infrastructure startup, announced it has crossed $1 billion in annualized run rate and raised a $750 million Series D round at a $15.75 billion valuation, led by Accel. The company's usage has tripled since its Series C and grown more than 15x year-over-year. Modal's Sandboxes product, launched in 2023 in response to developers using LLMs to generate code, has become a $300 million run rate product on its own, with nearly 3 billion sandboxes spun up and scaling to a million concurrent. The funding round marks Modal's transition from an infra unicorn to an infra decacorn, positioning it as a key player in the AI infrastructure space.

• Modal raised a $750M Series D at a $15.75B valuation, led by Accel.
• Modal crossed $1B in annualized run rate.
• Usage has tripled since Series C and grown over 15x year-over-year.

Runtime recap: the full keynote, VM Sandboxes, Modal Clusters, and more.

Modal announces a runtime product update with VM Sandboxes and Modal Clusters, as highlighted in a blog post.

Modal Labs closing in on $750M round at $15.75B valuation

AI inference infrastructure provider Modal Labs is nearing a $750 million funding round led by Accel at a $15.75 billion valuation, according to a source. This would more than triple its valuation from $4.65 billion in May. The round comes amid surging demand for inference services, with other startups like Baseten, Fireworks, and Fal also raising at higher valuations. Modal Labs, founded in 2021 by Erik Bernhardsson and Akshat Bubna, provides infrastructure for training and running AI models without managing servers. The company has surpassed $300 million in annualized revenue as of May. The funding talks follow a security incident in July where a customer's data was compromised, but Modal's platform was not breached.

• Modal Labs is nearing a $750 million funding round led by Accel at a $15.75 billion valuation.
• The round would more than triple Modal Labs' valuation from $4.65 billion in May.
• Modal Labs has surpassed $300 million in annualized revenue as of May.

DeepSeek Launches V4.1 Flash with Novel Encoder-Decoder Architecture

DeepSeek released DeepSeek-V4.1-Flash, a 763B-parameter mixture-of-experts model employing a novel causal encoder-decoder architecture with 8B active parameters for prefill and 16B for decode. It features native vision understanding, 1M token context, an MIT license, and extreme inference efficiency, claiming up to 1/8 KV cache footprint versus V4 Flash. Independent evals (Artificial Analysis Index 40, Vals Index #1 open-weight) show it surpasses V4 Pro at lower cost. API pricing is $0.30/1M input and $1.20/1M output tokens. DeepSeek has soft-retired V4 Pro, routing traffic to V4.1 Flash. The model supports SSD offload and local deployment, with Ollama and Baseten offering day-0 support. Technical discussions highlight the architecture's novelty and potential impact on long-context agents.

• DeepSeek launched V4.1-Flash with a causal encoder-decoder architecture, 763B total params (8B prefill/16B decode active).
• Artificial Analysis Index scores V4.1-Flash at 40, above V4 Pro and below GLM-5.3-Flash.
• API pricing: $0.30 per 1M input tokens, $1.20 per 1M output tokens, cached input $0.006 per 1M.

Ollama's transparent pricing

Ollama's Pro, Max, and Team plans now use industry-standard per-token pricing with usage included on every plan.

Developer Builds Autonomous AI Agent to Hunt Paid Bounties

A developer built an autonomous AI agent that scans hundreds of online gig/bounty listings, filters scams and human-only tasks, generates deliverables using live market data and a local LLM, and notifies a human for approval. The stack uses free tools (Python orchestration, Ollama with a local model, Chart.js, public crypto APIs, GitHub Pages, Windows Task Scheduler) resulting in $0/month infrastructure cost. In 48 hours the agent found many listings but only a handful were actionable due to geo-walls, ghost sponsors, and other filters; the author highlights the need for revenue tracking and human-in-the-loop oversight.

• Author built an autonomous AI agent that scans 232+ listings across multiple platforms to find paid work and generate deliverables.
• Stack used: Python orchestration, Ollama with qwen3:4b (local LLM), Chart.js, CoinGecko, DeFiLlama, Solana RPC, GitHub Pages, and Windows Task Scheduler.
• Total stated infrastructure cost: $0/month.