Together AI Release Notes

Improvements

Server-side validation for fine-tuning datasets

Files uploaded for fine-tuning now go through full server-side schema validation during ingestion, with the result exposed on the file object. Poll the Files API and read processing_status (COMPLETED, INVALID_FORMAT, or FAILED) plus validation_report to detect dataset issues programmatically before launching a job, like missing role fields or malformed conversation turns.

Errors include a user-facing reason, so you can fix the dataset and re-upload without trial-and-error training runs. For example:

Line 7: messages[1] must contain a role field

Fine-tuning job metrics API

A new API endpoint, GET /fine-tunes/{id}/metrics, returns training metrics for a fine-tuning job (e.g. loss curves and other per-step values) so you can monitor progress programmatically without opening the dashboard. See the API reference and Fine tuning training metrics for details.

Slurm startup scripts for GPU Clusters

GPU clusters now support Slurm startup scripts (lifecycle hook scripts that run at node startup, job allocation, and job completion). Use them to install packages at boot, configure SSH sessions, or run per-job prolog and epilog actions across worker, login, and controller nodes. See Slurm startup scripts for details.

Evaluations: Single-pass compare mode

The compare evaluator now accepts a disable_position_bias_correction parameter. By default, the judge runs each comparison twice (A→B then B→A) and reconciles verdicts to cancel position bias. Setting disable_position_bias_correction to true runs a single pass, cutting judge cost and latency in half. See AI evaluations for details.

Billing documentation updates

Updated billing docs for multiple payment methods, separate invoice addresses, ACH payment behavior, auto-recharge limits with bank transfers, and prepaid-only access (no negative balance limits). See Payment methods & invoices, Credits, and Billing troubleshooting.

New serverless models

The following image and video models are now available on serverless:

Image

ByteDance/Seedream-5.0-lite

Video

alibaba/happyhorse-1.0-i2v (image-to-video)

alibaba/happyhorse-1.0-r2v (reference-to-video)

google/veo-3.1

google/veo-3.1-lite

New dedicated endpoint models

The following models are now available for deployment on dedicated endpoints:

Gemma 3 (1B, 27B, 27B LoRA)

Gemma 4 31B LoRA

MedGemma 27B

Molmo 7B

Llama 3.2 3B Instruct

Llama 4 Scout 17B FP8 LoRA

Qwen 2/2.5/3 variants (14B, 32B, 235B A22B Instruct 2507 FP8, Qwen2-72B)

Arcee Trinity Mini

BGE Base EN v1.5

MiniMax Speech 2.8 Turbo

Rime Mist v3 (text and omni)

Seedance 2.0 quickstart

A quickstart is now available for Seedance 2.0, ByteDance’s unified multimodal audio-video generation model. The guide covers text-to-video, image-to-video, video extension, and instruction-based editing.

GPU Clusters: External OIDC authentication and RBAC

GPU clusters now support external OpenID Connect (OIDC) authentication, allowing each team member to access the cluster’s Kubernetes API using their organization’s identity provider — Google, Okta, Auth0, Microsoft Entra ID, and others.

With OIDC enabled, access is managed through standard Kubernetes RBAC: admins bind permissions to individual user identities, and each user authenticates via their browser using SSO. This replaces shared kubeconfig credentials with per-user tokens, per-user audit trails, and clean revocation. Currently this feature is only supported for Kubernetes clusters.

OIDC must be configured at cluster creation time. See Set up OIDC authentication for the full setup guide.