nvidia.nemotron-nano-3-30b

bedrock_converse · Chat model

nvidia.nemotron-nano-3-30b is listed here as a chat model from bedrock_converse. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Provider and model identifiers are kept in their original form for accuracy.

bedrock_converse-nvidia-nemotron-nano-3-30b

Input

$0.0600 / 1M tokens

Output

$0.2400 / 1M tokens

Cached input

$0.0060 / 1M tokens

Context window

8.2K

Catalog generated: Jul 13, 2026

Compare this model Open a side-by-side table using this route and a close match from the current catalog. Estimate cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill.

Quick read

Best for

Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.

Things to verify

Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.

Pricing

Item	Price
Input	$0.0600 / 1M tokens
Output	$0.2400 / 1M tokens
Cached input	$0.0060 / 1M tokens
Embedding	$0.0600 / 1M tokens

Limits

Context window

8.2K

Max input tokens

262.1K

Max output tokens

8.2K

Max tokens

8.2K

Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification. API vs subscription Learn when API pricing matters compared with ChatGPT, Claude Code, Cursor, or Copilot subscriptions. Cache and batch pricing Understand cached input, cache write, batch, priority, and flex pricing rows shown on this page.

Capabilities

Capability	Supported
Vision	-
Function calling	Supported
Parallel function calling	-
Tool choice	Supported
Prompt caching	-
Reasoning	-
Response schema	-
System messages	Supported
Audio input	-
Audio output	-
Web search	-
PDF input	-
Video input	-

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer

Benchmark	Score	Metric	Scope	Checked	Source
MT-Bench	8.22	total	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
IFEval	79.9	Prompt-Strict Acc	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
IFEval	86.1	Instruction-Strict Acc	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
MMLU	78.7	0-shot	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
GSM8K	92.3	0-shot	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
HumanEval	73.2	0-shot	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
MBPP	75.4	0-shot	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
Arena Hard	54.2	Arena Hard	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
AlpacaEval 2.0 LC	41.5	Length Controlled	Base model: Nemotron (Nemotron-4-340B-Instruct)	2026-05-31	Link
AIME 2025	76.25%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link
MATH-500	97.75%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link
GPQA	64.48%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link
LCB	70.79%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link
BFCL	66.98%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link
IFEval Prompt	84.70%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link
IFEval Instruction	89.81%	Reasoning On	Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2)	2026-05-31	Link

Sources

Source links	Row source LiteLLM repository LiteLLM model cost map
Pricing data	LiteLLM model cost map
Synced at	2026-05-28
Catalog generated	2026-07-13T14:21:55.110Z