# Nemotron-4-340B-Instruct [Canonical model page](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct) · [Model library](https://headlessthrones.com/models) Public catalog reference from Headless Thrones. Exact catalog ID: `nvidia-nemotron-4-340b-instruct`. Catalog source-check date: 2026-10-23. This brief contains the public catalog answers and any catalog guide, not private drafts, historical editorial revisions or independently measured rankings. The canonical HTML page may also display separately published editorial. Current catalog answers ## What to know about Nemotron-4-340B-Instruct AI-compiled from linked model documentation. This is a catalog reference, not an independent performance review. Catalog checked October 23, 2026. [Exact model](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-identity) · [Access](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-access) · [Token limits](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-context) · [Dates & knowledge](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-dates) · [License](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-license) · [Model details](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-research) · [Weight details](https://headlessthrones.com/models/nvidia-nemotron-4-340b-instruct#model-answer-repository) ### Which Nemotron-4-340B-Instruct does this page describe? Nemotron-4-340B-Instruct is a model record from **NVIDIA** in the Nemotron family. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct) A separate version identifier is not documented in this record; the model name alone does not establish which snapshot a service runs. ### How can you access Nemotron-4-340B-Instruct? The catalog documents **Open weights** access for Nemotron-4-340B-Instruct. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct) As of the catalog check, this version was listed without confirmed general availability. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct) Open weights means the model weights are distributed for use under their stated terms. It does not establish a hosted API, an open-source license, or a hardware requirement. ### What are Nemotron-4-340B-Instruct's context and output limits? The documented **context window is 4,096 tokens**. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) A separate maximum-output value is not established in this record. The context or input figure should not be used as an output allowance. Context, input and output limits describe different constraints. Do not add the figures together to infer a larger window. Check the endpoint's accounting for conversation history, system instructions, tools, media and generated tokens; a documented maximum is not a guarantee of answer quality or a measured usable capacity. ### What dates are documented for Nemotron-4-340B-Instruct? **Training-data cutoff: June 2023.** [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct) This describes the reported data boundary, not the day training finished. The source labels this “Training-data cutoff as labeled in official model card.” Retrieval or web tools can supply newer information at run time. That does not change the model's recorded training or knowledge dates, and this record does not establish that a particular endpoint includes those tools. ### What license is recorded for Nemotron-4-340B-Instruct? The recorded license label is **nvidia-open-model-license**. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct) Read the linked license and associated use terms for this exact version before redistribution, commercial deployment or fine-tuning. A label alone does not establish every permission, restriction or obligation, and it does not determine the terms of a separate hosted service. ### What distinguishes Nemotron-4-340B-Instruct? These details come from the linked publisher material for this model. Reported capabilities and training descriptions are publisher statements, not independent test results. **Checkpoint purpose**: Instruction-tuned model for text responses and synthetic-data generation. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **Training period**: Reported training period: between December 2023 and May 2024. This is not a data cutoff or public release date. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **Architecture**: Autoregressive Transformer decoder architecture. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **Alignment stages**: After the base model’s pretraining, this instruct checkpoint underwent SFT, DPO and reward-aware preference optimization. The publisher says synthetic generation supplied over 98% of its alignment data. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **BF16 deployment requirements**: The published BF16 configurations use eight H200 GPUs, sixteen H100 GPUs, or sixteen A100 GPUs with 80 GB each. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **Attention design**: The card documents grouped-query attention and rotary position embeddings, with a 4,096-token training sequence. Training sequence length is kept distinct from service allowances. [Source](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) ### What is documented about the Nemotron-4-340B-Instruct checkpoint? This evidence refers to `nvidia/Nemotron-4-340B-Instruct` at recorded revision `ac75bfbc2fb10d07fa90813707c18aebecdb9024`, checked October 23, 2026. [Repository metadata](https://huggingface.co/api/models/nvidia/Nemotron-4-340B-Instruct) Listed library: `nemo`. Check that library's version and model support before loading the weights. [Repository metadata](https://huggingface.co/api/models/nvidia/Nemotron-4-340B-Instruct) Repository access gate: `false`. This records the repository's gate setting when checked; licensing and use terms still apply. [Repository metadata](https://huggingface.co/api/models/nvidia/Nemotron-4-340B-Instruct) Read the retrieved model card for setup and qualifications. [Model card](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **Catalog qualifications:** Official publisher model repository; listed status confirms a catalog entry, not a verified hosted API service. [Source 1](https://huggingface.co/api/models/nvidia/Nemotron-4-340B-Instruct) · [Source 2](https://huggingface.co/nvidia/Nemotron-4-340B-Instruct/resolve/ac75bfbc2fb10d07fa90813707c18aebecdb9024/README.md) **Evidence still missing here:** tested hardware requirements. Missing documentation is not evidence that a feature is unavailable. Headless Thrones has not independently benchmarked this model for this reference. Evaluate it on representative work before choosing it; these facts do not rank its accuracy, reliability, speed or suitability against another model. Keep the exact version in view ## Other Nemotron models from NVIDIA. These are separate records in the same publisher family. A shared family name does not establish equal capabilities or interchangeable licenses. ### [NVIDIA-Nemotron-3.5-Bolt-E4B-BF16](https://headlessthrones.com/models/nvidia-nvidia-nemotron-3-5-bolt-e4b-bf16) Open weights ### [Nemotron-3.5-Parse](https://headlessthrones.com/models/nvidia-nemotron-3-5-parse) Open weights ### [NVIDIA-Nemotron-Labs-Dory1.0-4B-BF16](https://headlessthrones.com/models/nvidia-nvidia-nemotron-labs-dory1-0-4b-bf16) Open weights · 256,000 context tokens ### [NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16](https://headlessthrones.com/models/nvidia-nvidia-nemotron-3-5-bolt-74b-a9b-bf16) Open weights · 256,000 context tokens ### [NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16](https://headlessthrones.com/models/nvidia-nvidia-nemotron-3-5-super-vl-120b-a12b-base-bf16) Open weights ### [NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16](https://headlessthrones.com/models/nvidia-nvidia-nemotron-3-5-super-vl-120b-a12b-bf16) Open weights · 1,000,000 context tokens