> ## Documentation Index
> Fetch the complete documentation index at: https://docs.together.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Changelog

<Update label="May 15, 2026" tags={["New models"]}>
  ## New serverless models

  The following model has been added to serverless:

  * `pearl-ai/gemma-4-31b-it`: 32,000 context length, INT8 quantization. Pricing: \$0.28 input / \$0.86 output (per 1M tokens).

  See [Serverless models](/docs/serverless-models).
</Update>

<Update label="May 14, 2026" tags={["Deprecations", "Pricing"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available on serverless:

  * `deepseek-ai/DeepSeek-R1`.
  * `deepseek-ai/DeepSeek-V3.1`.
  * `Qwen/Qwen3-Coder-Next-FP8`.

  ## Upcoming pricing update

  The following model will have updated pricing, effective May 21, 2026:

  * `google/gemma-4-31b-it`: \$0.20 → \$0.39 (input), \$0.50 → \$0.97 (output) per 1M tokens.

  All usage from that date forward will be billed at the new rate.
</Update>

<Update label="May 8, 2026" tags={["New releases", "New models", "Pricing"]}>
  ## External collaborators for projects

  You can now invite users from outside your organization to collaborate on a project. Enable **Allow external collaborators** on the project's settings page, then add them like any other collaborator. The feature is currently in beta. See [roles & permissions](/docs/roles-permissions#external-collaborators-beta) for more details.

  ## New serverless models

  The following models have been added to serverless:

  * `alibaba/happyhorse-1.0-t2v`: \$0.24/sec at 1080p.
  * `ByteDance/Seedance-2.0`: \$0.16/sec at 720p.

  See [Serverless models](/docs/serverless-models).
</Update>

<Update label="May 7, 2026" tags={["New releases", "Improvements"]}>
  ## Together CLI v2.10

  The Together CLI has been updated with `tg` as the canonical command name and a refreshed command tree. Subcommands are now clearer and more consistent across fine-tuning, endpoints, evals, files, clusters, and jig.

  See [CLI reference](/reference/cli/getting-started) for details.

  ## Speech-to-text and translation: new audio formats

  The `/v1/audio/transcriptions` and `/v1/audio/translations` endpoints now accept `.ogg`, `.opus`, and `.aac` files in addition to `.wav`, `.mp3`, `.m4a`, `.webm`, and `.flac`.

  ## Speech-to-text: task field is now optional in verbose JSON responses

  The `task` field has been removed from the required fields of `AudioTranscriptionVerboseJsonResponse` and `AudioTranslationVerboseJsonResponse`. Clients that previously asserted on its presence should treat it as optional.
</Update>

<Update label="May 6, 2026" tags={["New releases"]}>
  ## Slurm-on-Kubernetes v1.0 for all new Slurm clusters

  All newly provisioned Slurm GPU clusters now run on a new Slurm-on-Kubernetes stack with significant reliability improvements. Existing clusters can be migrated in place.

  **What's new:**

  * **Self-healing worker daemons:** The Slurm worker daemon is now supervised and auto-restarts on crash, so transient failures recover without operator intervention or impact on healthy nodes.
  * **Durable job accounting:** Job history (`sacct`) is now persisted on durable, PVC-backed storage. Restarts and pod reschedules no longer wipe accounting data.
  * **Correct process tracking and cleanup:** Job processes (including daemonized children) are tracked at the kernel cgroup level and reliably cleaned up at job completion. No more orphaned processes holding GPU memory or `/dev/shm`.
  * **Zombie reaping:** A dedicated init process reaps orphaned children, preventing PID-table exhaustion from blocking new jobs.
  * **GPU state correctness:** The Slurm GPU view is rebuilt fresh on every node start, eliminating "GPU not found" failures after pod reschedules.
  * **Per-cluster GPU utilization metrics:** DCGM metrics are now exposed in your cluster's Grafana dashboards for fine-grained utilization visibility.

  See [Slurm configuration](/docs/slurm-configuration) for more details.
</Update>

<Update label="May 1, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available on serverless:

  * `MiniMaxAI/MiniMax-M2.5`.
</Update>

<Update label="April 30, 2026" tags={["Improvements"]}>
  ## Text-to-speech: pronunciation\_dict parameter

  A new `pronunciation_dict` parameter is available for TTS requests. Pass a list of `"<source>/<replacement>"` rules (e.g., `["omg/oh my god"]`) to override how the model pronounces specific tokens.

  ## Together Deployments: custom metric autoscaling

  Deployments can now autoscale on any Prometheus metric exposed by your worker's `/metrics` endpoint. Set `metric = "CustomMetric"` and provide a `custom_metric_name` (e.g., `vllm:num_requests_running`) along with a `target` to scale on application-specific signals.
</Update>

<Update label="April 28, 2026" tags={["Improvements"]}>
  ## Fine-tuning: new supported models

  The following models are now available for fine-tuning:

  * `Qwen/Qwen3.6-35B-A3B`.
  * `google/gemma-4-31B-it`.
  * `google/gemma-4-26B-A4B-it`.
</Update>

<Update label="April 24, 2026" tags={["New models", "Pricing"]}>
  ## DeepSeek-V4-Pro on serverless

  `deepseek-ai/DeepSeek-V4-Pro` has been added to serverless.

  * Context length: 512,000.
  * Pricing: \$2.10 input / \$4.40 output / \$0.20 cached input (per 1M tokens).
  * Quantization: FP4.
  * Function calling and structured outputs supported.

  ## New serverless models

  The following models have been added:

  * `deepcogito/cogito-v2-1-671b`.
  * `google/veo-3.1-test-debug`.
  * `vidu/vidu-q3`.
  * `vidu/vidu-q3-turbo`.
  * `Wan-AI/wan2.7-i2v`.
  * `Wan-AI/wan2.7-r2v`.

  ## Pricing update: no-packing fine-tuning jobs

  We rolled out a pricing update for no-packing fine-tuning jobs. When the no-packing option is chosen, the number of training dataset tokens is now calculated as `len(dataset) * max_seq_length` to account for the compute used by packing-free jobs.

  * `max_seq_length` is configurable in both the SDK and UI.
  * Price prediction reflects these changes, so if no-packing is chosen you can control the cost of the job by adjusting the sequence length.
</Update>

<Update label="April 22, 2026" tags={["Improvements", "New models"]}>
  ## Dynamic rate limits and prepaid billing

  * Build Tiers 1–5, Scale, and Enterprise tier labels have been retired. Dynamic rate limits are now live for all users.
  * Billing has moved to a fully prepaid model.
  * Model-specific tier gates have been removed. The platform-wide \$5 credit purchase is the only gate.

  ## New serverless models

  The following models have been added:

  * `moonshotai/Kimi-K2.6`.
</Update>

<Update label="April 15, 2026" tags={["Pricing"]}>
  ## Pricing update

  The following model has updated pricing, effective April 15, 2026:

  * **`google/gemma-3n-E4B-it`:** \$0.02 → \$0.06 (input), \$0.04 → \$0.12 (output) per 1M tokens.
</Update>

<Update label="April 14, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `Qwen/Qwen3-VL-8B-Instruct`.
  * `Qwen/Qwen3-235B-A22B-Thinking-2507`.
  * `mistralai/Mixtral-8x7B-Instruct-v0.1`.
</Update>

<Update label="April 11, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `MiniMaxAI/MiniMax-M2.7`.
</Update>

<Update label="April 8, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `google/gemma-4-31B-it`.
  * `zai-org/GLM-5.1`.
</Update>

<Update label="April 2, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `zai-org/GLM-4.5-Air-FP8`.
  * `zai-org/GLM-4.7`.
  * `Qwen/Qwen3-Next-80B-A3B-Instruct`.
</Update>

<Update label="March 31, 2026" tags={["Deprecations"]}>
  ## Model deprecation

  The following model has been deprecated and is no longer available:

  * `meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8`.
</Update>

<Update label="March 10, 2026" tags={["Pricing"]}>
  ## Cached input token pricing

  Cached input token pricing is now available:

  * `MiniMaxAI/MiniMax-M2.5`: \$0.06 per 1M cached input tokens (80% off standard input price).
</Update>

<Update label="March 7, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `Qwen/Qwen3.5-9B`.
</Update>

<Update label="March 6, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `mixedbread-ai/Mxbai-Rerank-Large-V2`.
  * `moonshotai/Kimi-K2-Thinking`.
  * `meta-llama/Llama-3.2-3B-Instruct-Turbo`.
  * `moonshotai/Kimi-K2-Instruct-0905`.
</Update>

<Update label="February 25, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `black-forest-labs/FLUX.1-dev`.
  * `black-forest-labs/FLUX.1-dev-lora`.
  * `black-forest-labs/FLUX.1-kontext-dev`.
  * `Qwen/Qwen3-VL-32B-Instruct`.
  * `mistralai/Ministral-3-14B-Instruct-2512`.
  * `Qwen/Qwen3-Next-80B-A3B-Thinking`.
  * `Alibaba-NLP/gte-modernbert-base`.
  * `BAAI/bge-base-en-v1.5`.
  * `meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo`.
  * `meta-llama/Llama-Guard-3-11B-Vision-Turbo`.
  * `meta-llama/LlamaGuard-2-8b`.
  * `marin-community/marin-8b-instruct`.
  * `nvidia/NVIDIA-Nemotron-Nano-9B-v2`.
</Update>

<Update label="February 16, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `Qwen/Qwen3.5-397B-A17B`.
</Update>

<Update label="February 15, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `MiniMaxAI/MiniMax-M2.5`.
</Update>

<Update label="February 13, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `zai-org/GLM-5`.
</Update>

<Update label="February 12, 2026" tags={["New releases"]}>
  ## Dedicated Container Inference launch

  Together AI has officially launched [Dedicated Container Inference](https://www.together.ai/dedicated-container-inference) (DCI), formerly known as BYOC. DCI lets you containerize, deploy, and scale custom models on Together AI.

  * [Blog post](https://www.together.ai/blog/dedicated-container-inference).
  * [Documentation](/docs/dedicated-container-inference).
  * [Getting started](/docs/containers-quickstart#example-guides).
</Update>

<Update label="February 6, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `togethercomputer/m2-bert-80M-32k-retrieval`.
  * `Salesforce/Llama-Rank-V1`.
  * `togethercomputer/Refuel-Llm-V2`.
  * `togethercomputer/Refuel-Llm-V2-Small`.
  * `Qwen/Qwen3-235B-A22B-fp8-tput`.
  * `qwen-qwen2-5-14b-instruct-lora`.
  * `meta-llama/Llama-4-Scout-17B-16E-Instruct`.
  * `Qwen/Qwen2.5-72B-Instruct-Turbo`.
  * `meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo`.
  * `BAAI/bge-large-en-v1.5`.
</Update>

<Update label="February 4, 2026" tags={["New releases"]}>
  ## Python SDK v2.0 general availability

  Together AI is releasing the **Python SDK v2.0**, a new, type-safe, OpenAPI-driven client designed to be faster, easier to maintain, and ready for everything we're building next.

  * **Install:** `pip install together` or `uv add together`.
  * **Migration guide:** A detailed [Python SDK Migration Guide](/docs/pythonv2-migration-guide) covers API-by-API changes, type updates, and troubleshooting tips.
  * **Code and docs:** Access the [Together Python v2 repo](https://github.com/togethercomputer/together-py) and [reference docs](/reference/chat-completions-1) with code examples.
  * **Main goal:** Replace the legacy v1 Python SDK with a modern, strongly-typed, OpenAPI-generated client that matches the API surface more closely and stays in lock-step with new features.
  * **Net new:** All new features will be built in version 2 moving forward. This first version already includes beta APIs for our Instant Clusters.
</Update>

<Update label="February 3, 2026" tags={["New models", "Deprecations"]}>
  ## New serverless models

  The following models have been added:

  * `Qwen/Qwen3-Coder-Next-FP8`.

  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `deepseek-ai/DeepSeek-R1-0528-tput`.
</Update>

<Update label="January 29, 2026" tags={["Deprecations"]}>
  ## Model redirects

  The following models are now being automatically redirected to their upgraded versions. See our [Model Lifecycle Policy](/docs/deprecations#model-lifecycle-policy) for details.

  | Original model                       | Redirects to                              |
  | :----------------------------------- | :---------------------------------------- |
  | `mistralai/Mistral-7B-Instruct-v0.3` | `mistralai/Ministral-3-14B-Instruct-2512` |
  | `zai-org/GLM-4.6`                    | `zai-org/GLM-4.7`                         |

  These are same-lineage upgrades with compatible behavior. If you need the original version, deploy it as a [dedicated endpoint](/docs/dedicated-endpoints).
</Update>

<Update label="January 27, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `moonshotai/Kimi-K2.5`.
</Update>

<Update label="January 23, 2026" tags={["Deprecations"]}>
  ## Model redirect

  The following model is now being automatically redirected to its upgraded version. See our [Model Lifecycle Policy](/docs/deprecations#model-lifecycle-policy) for details.

  | Original model     | Redirects to    |
  | :----------------- | :-------------- |
  | `DeepSeek-V3-0324` | `DeepSeek-V3.1` |

  This is a same-lineage upgrade with compatible behavior. If you need the original version, deploy it as a [dedicated endpoint](/docs/dedicated-endpoints).
</Update>

<Update label="January 21, 2026" tags={["Improvements", "Deprecations"]}>
  ## Prompt caching now enabled by default for dedicated endpoints

  Prompt caching is now **automatically enabled** for all newly created dedicated endpoints. This change improves performance and reduces costs by default.

  **What's changing:**

  * The `disable_prompt_cache` field (API), `--no-prompt-cache` flag (CLI), and related SDK parameters are now **deprecated**.
  * Prompt caching will always be enabled. The field is accepted but ignored after deprecation.

  **Timeline:**

  * **Now:** Field is deprecated; setting it has no effect (prompt caching is always on).
  * **February 2026:** Field will be removed.

  **Action required:**

  * `--no-prompt-cache` in CLI commands has no effect. You can remove it.
  * `disable_prompt_cache` from API requests has no effect. You can remove it.
  * SDK calls that set this parameter have no effect. You can remove it.

  No changes are required for existing endpoints. This only affects endpoint creation.
</Update>

<Update label="January 9, 2026" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `zai-org/GLM-4.7`.
</Update>

<Update label="January 5, 2026" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `Qwen/Qwen2.5-VL-72B-Instruct`.
</Update>

<Update label="December 23, 2025" tags={["Deprecations"]}>
  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `deepseek-ai/DeepSeek-R1-Distill-Llama-70B`.
  * `meta-llama/Meta-Llama-3-70B-Instruct-Turbo`.
  * `black-forest-labs/FLUX.1-schnell-free`.
  * `meta-llama/Meta-Llama-Guard-3-8B`.
</Update>

<Update label="December 17, 2025" tags={["Deprecations"]}>
  ## Model redirects now active

  The following models are now being automatically redirected to their upgraded versions. See our [Model Lifecycle Policy](/docs/deprecations#model-lifecycle-policy) for details.

  | Original model | Redirects to       |
  | :------------- | :----------------- |
  | `Kimi-K2`      | `Kimi-K2-0905`     |
  | `DeepSeek-V3`  | `DeepSeek-V3-0324` |
  | `DeepSeek-R1`  | `DeepSeek-R1-0528` |

  These are same-lineage upgrades with compatible behavior. If you need the original version, deploy it as a [dedicated endpoint](/docs/dedicated-endpoints).
</Update>

<Update label="December 12, 2025" tags={["New releases"]}>
  ## Python SDK v2.0 release candidate

  Together AI is releasing the **Python SDK v2.0 Release Candidate**, a new, OpenAPI-generated, strongly-typed client that replaces the legacy v1.0 package and brings the SDK into lock-step with the latest platform features.

  * **Install:** `pip install together==2.0.0a9`.
  * **RC period:** The v2.0 RC window starts today and will run for approximately one month. During this time we'll iterate quickly based on developer feedback and may make a few small, well-documented breaking changes before GA.
  * **Type-safe, modern client:** Stronger typing across parameters and responses, keyword-only arguments, explicit `NOT_GIVEN` handling for optional fields, and rich `together.types.*` definitions for chat messages, eval parameters, and more.
  * **Redesigned error model:** Replaces `TogetherException` with a new `TogetherError` hierarchy, including `APIStatusError` and specific HTTP status code errors such as `BadRequestError (400)`, `AuthenticationError (401)`, `RateLimitError (429)`, and `InternalServerError (5xx)`, plus transport (`APIConnectionError`, `APITimeoutError`) and validation (`APIResponseValidationError`) errors.
  * **New Jobs API:** Adds first-class support for the Jobs API (`client.jobs.*`) so you can create, list, and inspect asynchronous jobs directly from the SDK without custom HTTP wrappers.
  * **New Hardware API:** Adds the Hardware API (`client.hardware.*`) to discover available hardware, filter by model compatibility, and compute effective hourly pricing from `cents_per_minute`.
  * **Raw response and streaming helpers:** New `.with_raw_response` and `.with_streaming_response` helpers make it easier to debug, inspect headers and status codes, and stream completions via context managers with automatic cleanup.
  * **Code Interpreter sessions:** Adds session management for the Code Interpreter (`client.code_interpreter.sessions.*`), enabling multi-step, stateful code-execution workflows that were not possible in the legacy SDK.
  * **High compatibility for core APIs:** Most core usage patterns, including `chat.completions`, `completions`, `embeddings`, `images.generate`, audio transcription/translation/speech, `rerank`, `fine_tuning.create/list/retrieve/cancel`, and `models.list`, are designed to be drop-in compatible between v1 and v2.
  * **Targeted breaking changes:** Some APIs (Files, Batches, Endpoints, Evals, Code Interpreter, select fine-tuning helpers) have updated method names, parameters, or response shapes; these are fully documented in the Python SDK Migration Guide and Breaking Changes notes.
  * **Migration resources:** A dedicated Python SDK Migration Guide is available with API-by-API before/after examples, a feature parity matrix, and troubleshooting tips to help teams smoothly transition from v1 to v2 during the RC period.
</Update>

<Update label="December 8, 2025" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `mistralai/Ministral-3-14B-Instruct-2512`.
</Update>

<Update label="November 10, 2025" tags={["New models"]}>
  ## New serverless models

  The following models have been added:

  * `zai-org/GLM-4.6`.
  * `moonshotai/Kimi-K2-Thinking`.
</Update>

<Update label="November 3, 2025" tags={["New releases", "New models"]}>
  ## Real-time text-to-speech and speech-to-text

  Together AI expands audio capabilities with real-time streaming for both TTS and STT, new models, and speaker diarization.

  * **Real-time text-to-speech:** WebSocket API for lowest-latency interactive applications.
  * **New TTS models:** Orpheus 3B (`canopylabs/orpheus-3b-0.1-ft`) and Kokoro 82M (`hexgrad/Kokoro-82M`), supporting REST, streaming, and WebSocket endpoints.
  * **Real-time speech-to-text:** WebSocket streaming transcription with Whisper for live audio applications.
  * **Voxtral model:** New Mistral AI speech recognition model (`mistralai/Voxtral-Mini-3B-2507`) for audio transcriptions.
  * **Speaker diarization:** Identify and label different speakers in audio transcriptions with a free `diarize` flag.
  * **TTS WebSocket endpoint:** `/v1/audio/speech/websocket`.
  * **STT WebSocket endpoint:** `/v1/realtime`.

  See the [Text-to-speech guide](/docs/inference/text-to-speech/overview) and [Speech-to-text guide](/docs/inference/transcription/overview).
</Update>

<Update label="October 31, 2025" tags={["Deprecations"]}>
  ## Image model deprecations

  The following image models have been deprecated and are no longer available:

  * `black-forest-labs/FLUX.1-pro` (calls to FLUX.1-pro will now redirect to FLUX.1.1-pro).
  * `black-forest-labs/FLUX.1-Canny-pro`.
</Update>

<Update label="October 21, 2025" tags={["New releases", "New models"]}>
  ## Video generation API and 40+ new image and video models

  Together AI expands into multimedia generation with comprehensive video and image capabilities. [Read more](https://www.together.ai/blog/40-new-image-and-video-models).

  * **New video generation API:** Create high-quality videos with models like OpenAI Sora 2, Google Veo 3.0, and Minimax Hailuo.
  * **40+ image and video models:** Including Google Imagen 4.0 Ultra, Gemini Flash Image 2.5 (Nano Banana), ByteDance SeeDream, and specialized editing tools.
  * **Unified platform:** Combine text, image, and video generation through the same APIs, authentication, and billing.
  * **Production-ready:** Serverless endpoints with transparent per-model pricing and enterprise-grade infrastructure.
  * **Video endpoints:** `/videos/create` and `/videos/retrieve`.
  * **Image endpoint:** `/images/generations`.
</Update>

<Update label="September 15, 2025" tags={["Improvements"]}>
  ## Improved Batch Inference API

  * **Streamlined UI:** Create and track batch jobs in an intuitive interface. No complex API calls required.
  * **Universal model access:** The Batch Inference API now supports all serverless models and private deployments, so you can run batch workloads on exactly the models you need.
  * **Massive scale jump:** Rate limits are up from 10M to 30B enqueued tokens per model per user, a 3,000x increase. Need more? We'll work with you to customize.
  * **Lower cost:** For most serverless models, the Batch Inference API runs at 50% the cost of our real-time API, making it the most economical way to process high-throughput workloads.
</Update>

<Update label="September 13, 2025" tags={["New models"]}>
  ## Qwen3-Next-80B models

  New Qwen3-Next-80B models are now available for both thinking and instruction tasks.

  * Model ID: `Qwen/Qwen3-Next-80B-A3B-Thinking`.
  * Model ID: `Qwen/Qwen3-Next-80B-A3B-Instruct`.
</Update>

<Update label="September 10, 2025" tags={["Improvements"]}>
  ## Fine-tuning: new large models supported

  Enhanced fine-tuning capabilities with expanded model support. [Read more](https://www.together.ai/blog/fine-tuning-updates-sept-2025).

  * `openai/gpt-oss-120b`.
  * `deepseek-ai/DeepSeek-V3.1`.
  * `deepseek-ai/DeepSeek-V3.1-Base`.
  * `deepseek-ai/DeepSeek-R1-0528`.
  * `deepseek-ai/DeepSeek-R1`.
  * `deepseek-ai/DeepSeek-V3-0324`.
  * `deepseek-ai/DeepSeek-V3`.
  * `deepseek-ai/DeepSeek-V3-Base`.
  * `Qwen/Qwen3-Coder-480B-A35B-Instruct`.
  * `Qwen/Qwen3-235B-A22B` (context length 32,768 for SFT and 16,384 for DPO).
  * `Qwen/Qwen3-235B-A22B-Instruct-2507` (context length 32,768 for SFT and 16,384 for DPO).
  * `meta-llama/Llama-4-Maverick-17B-128E`.
  * `meta-llama/Llama-4-Maverick-17B-128E-Instruct`.
  * `meta-llama/Llama-4-Scout-17B-16E`.
  * `meta-llama/Llama-4-Scout-17B-16E-Instruct`.

  ## Fine-tuning: increased maximum context lengths

  ### DeepSeek models

  * DeepSeek-R1-Distill-Llama-70B: SFT 8,192 → 24,576; DPO 8,192 → 8,192.
  * DeepSeek-R1-Distill-Qwen-14B: SFT 8,192 → 65,536; DPO 8,192 → 12,288.
  * DeepSeek-R1-Distill-Qwen-1.5B: SFT 8,192 → 131,072; DPO 8,192 → 16,384.

  ### Google Gemma models

  * gemma-3-1b-it: SFT 16,384 → 32,768; DPO 16,384 → 12,288.
  * gemma-3-1b-pt: SFT 16,384 → 32,768; DPO 16,384 → 12,288.
  * gemma-3-4b-it: SFT 16,384 → 131,072; DPO 16,384 → 12,288.
  * gemma-3-4b-pt: SFT 16,384 → 131,072; DPO 16,384 → 12,288.
  * gemma-3-12b-pt: SFT 16,384 → 65,536; DPO 16,384 → 8,192.
  * gemma-3-27b-it: SFT 12,288 → 49,152; DPO 12,288 → 8,192.
  * gemma-3-27b-pt: SFT 12,288 → 49,152; DPO 12,288 → 8,192.

  ### Qwen models

  * Qwen3-0.6B / Qwen3-0.6B-Base: SFT 8,192 → 32,768; DPO 8,192 → 24,576.
  * Qwen3-1.7B / Qwen3-1.7B-Base: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen3-4B / Qwen3-4B-Base: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen3-8B / Qwen3-8B-Base: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen3-14B / Qwen3-14B-Base: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen3-32B: SFT 8,192 → 24,576; DPO 8,192 → 4,096.
  * Qwen2.5-72B-Instruct: SFT 8,192 → 24,576; DPO 8,192 → 8,192.
  * Qwen2.5-32B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 12,288.
  * Qwen2.5-32B: SFT 8,192 → 49,152; DPO 8,192 → 12,288.
  * Qwen2.5-14B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2.5-14B: SFT 8,192 → 65,536; DPO 8,192 → 16,384.
  * Qwen2.5-7B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2.5-7B: SFT 8,192 → 131,072; DPO 8,192 → 16,384.
  * Qwen2.5-3B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2.5-3B: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2.5-1.5B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2.5-1.5B: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2-72B-Instruct / Qwen2-72B: SFT 8,192 → 32,768; DPO 8,192 → 8,192.
  * Qwen2-7B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2-7B: SFT 8,192 → 131,072; DPO 8,192 → 16,384.
  * Qwen2-1.5B-Instruct: SFT 8,192 → 32,768; DPO 8,192 → 16,384.
  * Qwen2-1.5B: SFT 8,192 → 131,072; DPO 8,192 → 16,384.

  ### Meta Llama models

  * Llama-3.3-70B-Instruct-Reference: SFT 8,192 → 24,576; DPO 8,192 → 8,192.
  * Llama-3.2-3B-Instruct: SFT 8,192 → 131,072; DPO 8,192 → 24,576.
  * Llama-3.2-1B-Instruct: SFT 8,192 → 131,072; DPO 8,192 → 24,576.
  * Meta-Llama-3.1-8B-Instruct-Reference: SFT 8,192 → 131,072; DPO 8,192 → 16,384.
  * Meta-Llama-3.1-8B-Reference: SFT 8,192 → 131,072; DPO 8,192 → 16,384.
  * Meta-Llama-3.1-70B-Instruct-Reference: SFT 8,192 → 24,576; DPO 8,192 → 8,192.
  * Meta-Llama-3.1-70B-Reference: SFT 8,192 → 24,576; DPO 8,192 → 8,192.

  ### Mistral models

  * mistralai/Mistral-7B-v0.1: SFT 8,192 → 32,768; DPO 8,192 → 32,768.
  * teknium/OpenHermes-2p5-Mistral-7B: SFT 8,192 → 32,768; DPO 8,192 → 32,768.

  ## Fine-tuning: Hugging Face integrations

  * Fine-tune any \< 100B parameter CausalLM from Hugging Face Hub.
  * Support for DPO variants such as LN-DPO, DPO+NLL, and SimPO.
  * Support fine-tuning with maximum batch size.
  * Public `fine-tunes/models/limits` and `fine-tunes/models/supported` endpoints.
  * Automatic filtering of sequences with no trainable tokens (e.g., if a sequence prompt is longer than the model's context length, the completion is pushed outside the window).
</Update>

<Update label="September 9, 2025" tags={["New releases"]}>
  ## Together Instant Clusters general availability

  Self-service NVIDIA GPU clusters with API-first provisioning. [Read more](https://www.together.ai/blog/together-instant-clusters-ga).

  * New API endpoints for cluster management:
    * `/v1/gpu_cluster`: Create and manage GPU clusters.
    * `/v1/shared_volume`: High-performance shared storage.
    * `/v1/regions`: Available data center locations.
  * Support for NVIDIA Blackwell (HGX B200) and Hopper (H100, H200) GPUs.
  * Scale from single-node (8 GPUs) to hundreds of interconnected GPUs.
  * Pre-configured with Kubernetes, Slurm, and networking components.
</Update>

<Update label="September 8, 2025" tags={["Improvements"]}>
  ## Serverless LoRA and dedicated endpoint support for evaluations

  You can now run evaluations:

  * Using [Serverless LoRA](/docs/lora-inference#serverless-lora-inference) models, including supported LoRA fine-tuned models.
  * Using [dedicated endpoints](/docs/dedicated-endpoints), including fine-tuned models deployed via dedicated endpoints.
</Update>

<Update label="September 5, 2025" tags={["New models"]}>
  ## Kimi-K2-Instruct-0905

  Upgraded version of Moonshot's 1 trillion parameter MoE model with enhanced performance. [Read more](https://www.together.ai/models/kimi-k2-0905).

  * Model ID: `moonshot-ai/Kimi-K2-Instruct-0905`.
</Update>

<Update label="August 27, 2025" tags={["New models", "Deprecations"]}>
  ## DeepSeek-V3.1

  Upgraded version of DeepSeek-R1-0528 and DeepSeek-V3-0324. [Read more](https://www.together.ai/blog/deepseek-v3-1-hybrid-thinking-model-now-available-on-together-ai).

  * **Dual modes:** Fast mode for quick responses; thinking mode for complex reasoning.
  * **671B total parameters**, with 37B active parameters.
  * Model ID: `deepseek-ai/DeepSeek-V3.1`.

  ## Model deprecations

  The following models have been deprecated and are no longer available:

  * `meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo`.
  * `black-forest-labs/FLUX.1-canny`.
  * `meta-llama/Llama-3-8b-chat-hf`.
  * `black-forest-labs/FLUX.1-redux`.
  * `black-forest-labs/FLUX.1-depth`.
  * `deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B`.
  * `NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO`.
  * `meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo`.
  * `meta-llama-llama-3-3-70b-instruct-lora`.
  * `Qwen/Qwen2.5-14B`.
  * `meta-llama/Llama-Vision-Free`.
  * `Qwen/Qwen2-72B-Instruct`.
  * `google/gemma-2-27b-it`.
  * `meta-llama/Meta-Llama-3-8B-Instruct`.
  * `perplexity-ai/r1-1776`.
  * `nvidia/Llama-3.1-Nemotron-70B-Instruct-HF`.
  * `Qwen/Qwen2-VL-72B-Instruct`.
</Update>

<Update label="August 19, 2025" tags={["Improvements"]}>
  ## GPT-OSS fine-tuning support

  Fine-tune OpenAI's open-source models to create domain-specific variants. [Read more](https://www.together.ai/blog/fine-tune-gpt-oss-models-into-domain-experts-together-ai).

  * Supported models: `gpt-oss-20B` and `gpt-oss-120B`.
  * Supports 16K context SFT and 8K context DPO.
</Update>

<Update label="August 5, 2025" tags={["New models"]}>
  ## OpenAI GPT-OSS models

  OpenAI's first open-weight models are now accessible through Together AI. [Read more](https://www.together.ai/blog/announcing-the-availability-of-openais-open-models-on-together-ai).

  * Model IDs: `openai/gpt-oss-20b`, `openai/gpt-oss-120b`.
</Update>

<Update label="July 29, 2025" tags={["New models"]}>
  ## VirtueGuard

  Enterprise-grade guard model for safety monitoring with **8ms response time**. [Read more](https://www.together.ai/blog/virtueguard).

  * Real-time content filtering and bias detection.
  * Prompt injection protection.
  * Model ID: `VirtueAI/VirtueGuard-Text-Lite`.
</Update>

<Update label="July 28, 2025" tags={["New releases"]}>
  ## Together Evaluations framework

  Benchmarking platform using LLM-as-a-judge methodology for model performance assessment. [Read more](https://www.together.ai/blog/introducing-together-evaluations).

  * Create custom LLM-as-a-judge evaluation suites for your domain.
  * Supports `compare`, `classify`, and `score` functionality.
  * Compare models, prompts, and LLM configs; score and classify LLM outputs.
</Update>

<Update label="July 25, 2025" tags={["New models"]}>
  ## Qwen3-Coder-480B

  Agentic coding model with top SWE-Bench Verified performance. [Read more](https://www.together.ai/blog/qwen-3-coder).

  * **480B total parameters**, with 35B active (MoE architecture).
  * **256K context length** for entire codebase handling.
  * **Leading SWE-Bench scores** on software engineering benchmarks.
  * Model ID: `Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8`.
</Update>

<Update label="July 17, 2025" tags={["New releases"]}>
  ## NVIDIA HGX B200 hardware support

  Record-breaking serverless inference speed for DeepSeek-R1-0528 using NVIDIA's Blackwell architecture. [Read more](https://www.together.ai/blog/fastest-inference-for-deepseek-r1-0528-with-nvidia-hgx-b200).

  * Dramatically improved throughput and lower latency.
  * Same API endpoints and pricing.
  * Model ID: `deepseek-ai/DeepSeek-R1`.
</Update>

<Update label="July 14, 2025" tags={["New models"]}>
  ## Kimi-K2-Instruct

  Moonshot AI's 1 trillion parameter MoE model with frontier-level performance. [Read more](https://www.together.ai/blog/kimi-k2-leading-open-source-model-now-available-on-together-ai).

  * Excels at tool use and multi-step tasks, with strong multilingual support.
  * Strong agentic and function calling capabilities.
  * Model ID: `moonshotai/Kimi-K2-Instruct`.
</Update>

<Update label="July 10, 2025" tags={["New releases"]}>
  ## Whisper speech-to-text APIs

  High-performance audio transcription that's 15x faster than OpenAI, with support for files over 1 GB. [Read more](https://www.together.ai/blog/speech-to-text-whisper-apis).

  * Multiple audio formats with timestamp generation.
  * Speaker diarization and language detection.
  * Use the `/audio/transcriptions` and `/audio/translations` endpoints.
  * Model ID: `openai/whisper-large-v3`.
</Update>

<Update label="July 8, 2025" tags={["New releases"]}>
  ## SOC 2 Type II compliance certification

  Achieved enterprise-grade security compliance through an independent audit of security controls. [Read more](https://www.together.ai/blog/soc-2-compliance).

  * Simplified vendor approval and procurement.
  * Reduced due diligence requirements.
  * Support for regulated industries.
</Update>