Releasesby Ibise2b@2.56.0
Update11 days agoUnverifiedAdded Oct 17, 2026
Minor Changes 6a74c39: Require Node.js 22.19.0 or newer and depend on undici@^8 only (undici 7 is dropped). undici 8 respects the server's HTTP/2 SETTINGS_MAX_CONCURRENT_STREAMS and opens more connections when one is saturated.
Topics: Streaming, Developer tools
More E2B releases
Every E2B releasee2b@2.55.0
Minor Changes b52cd30: Add mode: 'full' | 'filesystem' (exported as the SnapshotMode type) to createSnapshot / create_snapshot. With 'filesystem', only the filesystem is persisted: the snapshot is smaller and faster to take, and sandboxes created from it cold-boot (start fresh from disk) instead of restoring memory.
e2b@2.52.0
Minor Changes 2de0cc3: Cap sandbox fork count at 20. e2b sandbox fork --count, JavaScript Sandbox.fork({ count }), and Python Sandbox.fork(count=...) reject a count outside 1–20 before the API call. Counts from 21 through 100 used to reach the API. Omitting count still leaves the field off the request so the API default applies.
e2b@2.51.0
Minor Changes 5c0f6eb : Remove SDK-side defaults from API request payloads so the API defaults apply when options are omitted. Sandbox create/fork/connect no longer preset a 5-minute timeout, fork no longer presets count: 1 , create no longer presets allow_internet_access , pause no longer presets keeping memory, and template builds no longer preset...
e2b@2.50.0
Minor Changes 5b015ad : Removed the V1 template build operations and schemas from the generated API clients. The API no longer serves them (runtime 87968fc1e1fa ); control planes carrying that change answer 410 Gone . Template builds go through the Template SDK.
e2b@2.49.0
Minor Changes f842aa8 : Expose a configurable minimum free-disk target with minFreeDiskMb in JavaScript, min_free_disk_mb in Python, and --min-free-disk-mb in template create . Omission uses the team default, while explicit zero requests no minimum growth. Growth is best effort and never shrinks an existing filesystem.
Also shipped on Oct 13, 2026
E2B in October 2026What's included:
- Three training methods: Supervised fine-tuning (SFT) , direct preference optimization (DPO) , and reinforcement learning with group relative policy optimization (GRPO) . Each method trains a low-rank adapter (LoRA) or the full model weights. Custom loss functions : Train with any objective you compute in PyTorch from the model's log-probabilities.
The AI.AGG function is generally available (GA)
The AI.AGG function is generally available (GA). You can use this function to semantically aggregate unstructured input data based on natural language instructions.
BigQuery generative AI functions now support the gemini-4-argon model
BigQuery generative AI functions now support the gemini-4-argon model. This model is generally available .
Gemini 4 Argon in CodeMender (Preview)
CodeMender now supports Gemini 4 Argon. To use it, pass --model gemini-4-argon to cm find , cm verify , or cm fix . Gemini 3.8 Flash remains the default model. For more information, see Specifying the model .
Gemini 4 Argon and Gemini 4 Argon Cyber Permissive
Gemini 4 Argon ( gemini-4-argon ) is available in General Availability (GA) . Gemini 4 Argon is Google's frontier model that excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science.
On-demand state repartitioning is now generally available
On-demand state repartitioning is now generally available. You can resize the number of shuffle partitions for a stateful Structured Streaming query or Lakeflow pipeline without losing checkpoint state. See On-demand state repartitioning for stateful streaming queries .