Vapi is giving its community free, unrestricted access to Cartesia's newly launched Sonic-3 TTS model through its managed API key from October 28 through November 2. Sonic-3 adds emotion and laughter tags, fine-grained speed and volume controls, and support for 27 new languages. Vapi recommends starting with the Kira and Ariana voices for low-latency, natural-sounding agents.
Modal built Modal Vibe, an open-source demo vibe coding platform on Modal Sandboxes that scales from 0 to 1,000 AI-coded apps in about five minutes. A load test creating 1,000 apps, each in its own Sandbox, took roughly 300 seconds, with the AI API as the rate-limiting step. Modal says the Team Plan can run 1,000 concurrent Sandboxes, enough for over one million sessions per month.
Modal shipped product updates including Modal Notebooks for cloud-based Python experimentation with up to 8 B200 GPUs, plus an optional idle_timeout parameter for modal.Sandbox.create(). The client also added a startup_timeout parameter to @app.function() and @app.cls() decorators and a new API pattern for imperative management of Modal resource types. Modal Notebooks have since been shut down, though existing notebooks can still be downloaded as .ipynb files.
Modal Notebooks is now generally available to all Modal customers after a limited beta last month. The collaborative notebook environment runs on a GPU-enabled Python kernel that reaches a ready state in under 5 seconds on arbitrary container images and hardware up to 256 vCPUs and 8 H100/B200 GPUs, with auto-idle shutdown, shared Volumes and Secrets, and real-time multi-cursor editing. Modal says over 5,000 accounts ran 200,000 code cells during the August beta, and upcoming features include memory snapshots, one-click export to Modal Apps, and scheduled runs.
Modal added GPU memory snapshots in alpha, cutting cold boots for GPU workloads by 10x by skipping steps like Torch compilation, enabled via the enable_gpu_snapshot option. The update also brings Modal Notebooks in beta for running Python in the browser, Service Tokens for workspace managers, and browser-generated UIs for deployed Functions.
Modal announced GPU memory snapshots in alpha, extending its existing checkpoint/restore system to capture GPU vRAM, CUDA kernels, streams and contexts so GPU workloads restore from a frozen state instead of rebuilding CUDA state after boot.
Why it matters: Modal adds GPU state to its memory snapshots, cutting cold boots for torch.compile and vLLM workloads by up to 10x and making scale-to-zero more practical.
Modal has launched multi-node training clusters in beta, letting users tap dozens of GPUs across multiple hosts by adding the @clustered decorator, with 3.2 Tbps Infiniband RDMA interconnect for near-linear scaling. The platform now offers NVIDIA B200 and H200 GPUs serverlessly at $6.25/hr and $4.54/hr respectively, claiming up to 2-4× faster LLM inference than H100s. Modal also released Client 1.0, emphasizing API stability, alongside updates including a read-only Volume method and timezone support for Cron schedules.
Vapi now lets users launch outbound call campaigns by uploading a CSV of phone numbers and custom variables, then assigning an assistant or workflow to run. Vapi handles queuing, execution and logging, with call status visible in the dashboard. Campaigns require a verified phone number, as Vapi numbers cannot be used.
Modal has launched version 1.0 of its Python SDK client, a milestone the company says brings a new level of maturity and stability to its serverless cloud compute platform, with far fewer breaking changes expected going forward. The release removes "magic" behaviors such as automatic mounting of local packages, splits core functionality across separate decorators like the new @modal.concurrent, and consolidates local file handling under the modal.Image class. Modal also plans SDKs for other languages and is exploring how the platform should serve AI-driven agent workflows.
Vapi now offers 11 built-in text-to-speech models as alternatives to ElevenLabs, including Neuphonic's Neu-hq and Neu-fast, Cartesia's Sonic lineup, Azure TTS, OpenAI TTS, Deepgram, Smallest AI's Lightning, LMNT, PlayHT, Hume's Octave and Rime AI's Mist v2. Developers can switch between them in minutes without re-coding, and Vapi says it handles over a million voice calls per day across these models.
Modal now offers Nvidia B200 and H200 GPUs to any account holder with no sales contact or quota request, priced at $6.25/hour and $4.54/hour respectively. The B200 carries 180 GB of HBM3e memory and 8 TB/s bandwidth, and in Modal's vLLM test running DeepSeek V3 in 8-bit precision, 8xB200 cut median time-to-first-token 2.5x versus 8xH200 at 1 request per second.
Narakeet converts written scripts into lifelike voiceovers, offering 600+ voices across 70+ languages and support for 140+ languages and dialects. The platform syncs narration with PowerPoint, Google Slides, and Markdown files, generates subtitles and captions, and provides a developer API with batch processing. Plans start around $5 per month, with a free tier available.
Modal launched Modal Batch, a batch-processing interface backed by a rebuilt durable queue that can queue 1 million inputs at once, up from 2,000, and guarantees execution up to 7 days after a job is launched, up from 1 day. A new native handler, .spawn_map, spawns thousands of containers over a set of inputs without users managing async logic, and Harvey reports a 10x speed-up in its document-processing pipeline after fanning inputs across 1,000 containers. Suno uses it to run GPU-accelerated preprocessing on thousands of GPUs, and Achira relies on its retry mechanism for quantum mechanical datasets.
Modal upgraded its serverless Dict key-value store: new Dicts now have unlimited storage instead of the previous 10GiB cap, and item expiry changed to 7 days since last write or read. A new skip_if_exists flag on .put() enables distributed locking and "exactly once" semantics, and Dicts now offer data durability. The changes apply only to newly created Dicts.
Vapi has rolled out direct integration with GoHighLevel Calendars, embedding its voice agents into the GHL scheduling flow. Agents can now check real-time availability on connected GHL calendars, create contacts from caller details, and book appointments tied to the correct contact. Setup mirrors connecting Google Calendar in Vapi, with four new tools: Create Event, Check Availability, Create Contact, and Contact Get.
Modal released alpha versions of its official SDKs for JavaScript and Go, letting developers call deployed Modal Functions and create isolated sandboxes from Node, Next.js, or Go services without writing Python. The SDKs cannot deploy functions, which still require Python, and only support JSON-like or bytes data types for now. Modal says it can run 10,000 sandboxes in either language without issues.
Lemon Slice built Lemon Slice Live, a product for real-time video conversations with AI characters, using Modal and Daily's low-latency primitives to reach an end-to-end video response latency of 3-6 seconds. The pipeline runs a Pipecat server and a 1B parameter video model on separate Modal containers that communicate via Modal's Tunnel and are co-located with region selection, with Deepgram, Grok and ElevenLabs handling speech-to-text, LLM response and text-to-speech. Earlier, two Python Modal Functions let Lemon Slice scale to 10,000 requests per hour without managing an ECS cluster, job queue or load balancer.
Vapi now supports SMS, letting its voice AI agents send and receive text messages during calls. Agents can reply to incoming texts live, switch from voice to text mid-conversation, and run fully text-based flows; SMS is currently available for Twilio only.
Vapi released the Vapi MCP Server, letting AI agent tools trigger real-time voice flows and outbound calls via function calling. It supports Claude Desktop integration and remote access over SSE, so users can ask Claude to place calls or schedule follow-ups in plain language. The server is available via @vapi-ai/mcp-server, locally or through a hosted SSE endpoint.
Modal now lets each Function queue up to 1 million inputs, up from 2k, with higher .spawn() rate limits and FunctionCall results retained for 7 days. The update also adds ephemeral apps via app.run() inside containers, Git commit info for apps in the CLI and dashboard, and a new TensorRT-LLM example serving LLMs at under 400 ms latency.
Modal cut GPU, CPU and memory prices by up to 65%, and Team plan users can now run up to 50 GPUs concurrently. The Modal SDK is now on conda-forge starting with version 0.73.46, and a version 1.0 client release is planned. Modal also published an LTX-Video image-to-video example and launched a new logo.
Modal shipped a refreshed logs dashboard with time-range input filtering, live container profiling for debugging stuck containers or inputs, and Debug Shells that run commands like vim, ps, and strace inside running containers. Region selection is now available on all plans, priced with a multiplier on base prices, and the client adds OIDC authentication for cloud bucket mounts via the new oidc_auth_role_arn field.
Modal introduced memory snapshot restore for its serverless GPU container runtime, which it says makes cold starts about 2.5x faster than standard container startup. A Stable Diffusion inference Function that normally takes around 13 seconds now restores in 3.5 seconds, and a simple import torch program drops from roughly 5 seconds to about 1.05 seconds at p50 and 0.69 seconds at p0. Snapshots are built on gVisor's checkpoint/restore and are created on demand, with automatic fallback to a standard container startup when a restore fails; GPU state is not yet saved, so it must be rebuilt after restore.
Why it matters: Modal explains how gVisor-based memory snapshots cut serverless cold starts, with concrete restore timings for a Stable Diffusion Function and a torch import example.
Modal now offers NVIDIA L40S GPUs at $1.95/hr, with 48GB of memory, up to 40% faster performance on memory-bound tasks and over 100% speedup on compute-bound jobs versus its A10 GPUs. The platform also added Proxy Auth tokens for gating web endpoints, a Filesystem API for Sandboxes, and disk snapshotting that lets users branch new Sandbox instances from snapshots to eliminate cold starts. Modal additionally announced completion of its SOC 2 Type 2 certification.
Modal announced the general availability of Sandboxes, its primitive for safely running untrusted code from LLMs, users, or third-party sources in an isolated environment separate from other Modal resources. Sandboxes offer a simple exec API, runtime-configurable environments via the Image API, and filesystem snapshots for persistence. Modal also upstreamed support into SWE-bench, where a --modal flag lets the Verified benchmark's 500 tasks run in about 7 minutes, and cited Quora's Poe, Codegen, and Relevance AI as customers.
Modal shipped a product update round led by a major upgrade to its beta memory snapshotting feature, which it says can cut cold start times by half for models like Stable Diffusion. The platform also added OpenID Connect support for short-lived identity tokens, eStargz image compression for faster builds from registries like ECR and Docker Hub, and is expanding async job queues toward a 1 million input limit, up from 2k.
Modal now offers NVIDIA L40S GPUs to all users at $1.95/hr, positioned as a faster, larger-memory alternative to its most popular inference accelerator, the A10. The L40S doubles GPU RAM to 48GB, letting models like Flux.1-schnell run in 16bit precision on a single GPU, and delivers roughly 40% speedup on memory-bound jobs and over 100% on compute-bound 16bit Tensor Core jobs.
Modal shipped static IP proxies that route outbound traffic through workspace-exclusive IPs, plus a native Slack integration for real-time app alerts and a live usage dashboard tracking resources across all workspace apps. The update also adds GPU fallbacks for functions, expanding the pool of resources a function can be scheduled on, and client changes including `modal shell` container IDs and memory snapshotting for parametrized functions.
Modal has added native dynamic batching support, letting inference functions group requests via a single @modal.batched() decorator with max_batch_size and wait_ms parameters. On OpenAI's Whisper large v3 running on an A10G, a max_batch_size of 64 raised throughput from ~1.2 to ~3.3 requests per second per container and cut inference cost by 65%.
Modal shipped app rollbacks that let users revert a deployed app to a previous version from the dashboard or CLI, plus a @batched decorator that accumulates requests into dynamically sized batches to trade latency for throughput and GPU utilization. Sandbox objects can now forward TCP ports to the internet and exec additional processes, and logs can be exported to an OpenTelemetry provider. CPU cores and higher-end GPUs also got cheaper.
Cursor has implemented a shadow workspace that lets its AI apply edits in a hidden Electron window and read back lint results without touching the user's editing session. The post outlines the design goals of LSP availability, independence, privacy, concurrency and speed, and explains why copying a TextModel or running separate language servers failed. It also sketches a future kernel-level folder proxy for runnability, noting that macOS and Windows lack a viable FUSE path and that Rust LSP support is currently unavailable.
Modal's monthly product update adds a Datadog integration that forwards application and audit logs with a single click, plus cloud region selection for functions to meet regulatory, egress cost, or database-locality needs. The company also reworked its function call system for higher throughput with significantly lower overhead, targeting low-latency real-time production workloads, and overhauled the app details page with time-interval zoom, container status, and image file system views.
Modal's monthly product update adds writable mounts for AWS S3 and Cloudflare R2 buckets, a @web_server decorator for hosting non-ASGI/WSGI web servers on a specified port, and Okta single sign-on for enterprise plan users. A volume viewer in the web dashboard lets users explore volume file systems, and the latest client adds multi-file app composition via .include, partitioned queues, and stdin support for Sandboxes.
Modal now supports WebSocket connections, letting functions on its platform maintain persistent, bidirectional links between client and server instead of per-request HTTP connections. Each WebSocket connection counts as a single input, so functions not bound by CPU/GPU should allow concurrent inputs or Modal spins up a new container per connection. Modal auto-scales WebSocket handlers, targeting real-time streaming, progress updates on long-running tasks, and hosting frameworks like ComfyUI, Streamlit and Gradio.
Modal has added WebSocket support to its functions, enabling out-of-the-box hosting of frameworks like Streamlit, plus interactive commands via `modal container exec` for inspecting and debugging active containers. H100 GPUs are now available on Modal, and the client update adds `@build` lifecycle hooks, automatic background commits for Volumes, and expanded CLI commands including get, put and rm.
Modal has made NVIDIA H100 GPUs available to all users, priced at $7.65 per hour per GPU. NVIDIA benchmarks show the H100 delivers up to 4x training speedups and up to 30x inference speedups versus the A100, with 80 GB of on-chip DRAM and up to 8 GPUs linked via NVLink at 3.6 TB/s. Users enable it by setting "H100" as the GPU type in the Modal decorator.