batchlane
github.com/gojiplus/batchlane- Category
- Developer Tools
- Rank
- No. 1944Tools index
Previous survey · No. 1958 ·
- Pricing
- Open Source
- Type
- TOOL
- Use case
- Models: Train & Run
- GitHub
- 3 stars
- Latest release
- v0.2.0
- Date
About
batchlane is a Python library that submits asynchronous LLM batch jobs through a single interface across eight providers, including Anthropic, Gemini AI Studio, OpenAI, Groq, Mistral, Fireworks, Together, and DeepInfra. It splits a job to fit each provider's batch size limits, submits the resulting batches, waits for completion, and rejoins results in the original input order; only the Anthropic adapter has been verified against a live API.
At a glance
batchlane submits asynchronous model jobs through a shared Python interface and matches responses back to input rows. It is worth evaluating when you have many independent requests and can wait for a provider batch.
Good fit
Developers classifying or summarizing datasets offline who want the same job shape across providers.
Consider something else when
Use direct requests for interactive output or a provider client when you need features the adapter does not cover.
Start here
Dry-run a small synthetic JSONL file, then submit it with the documented live-verified adapter. Check row order, failure markers and what happens when you resume the same job.
Cost and requirements
MIT-licensed, Python 3.12 or newer, with credentials and billing for the selected provider.
Limits to know
The author reports live end-to-end testing only for Anthropic. Other adapters have mocked contract tests. Requests and downloaded results are buffered in memory.
Sources checked 2026-11-05. Source-based assessment.
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