What is the effective context window for NVIDIA Nemotron 3 Super 120B A12B in Atlas?

NVIDIA Nemotron 3 Super 120B A12B provides a 262,144 token context window on NVIDIA NIM, which also supports a 262,144 max output. On Vercel, Nebius, and Cloudflare Workers AI, the context window is 256,000 tokens. This large capacity allows Atlas to process extensive code and complex reasoning.

How much does NVIDIA Nemotron 3 Super 120B A12B cost to use with Atlas?

Pricing for NVIDIA Nemotron 3 Super 120B A12B varies significantly by provider. Input tokens start at $0.15 per Mtok on Vercel AI Gateway, while NVIDIA NIM charges $0.20 per Mtok. Output tokens are generally 3x to 4x more expensive, for example, $0.65 per Mtok on Vercel AI Gateway.

Why is the price of NVIDIA Nemotron 3 Super 120B A12B so different across providers?

The input price for NVIDIA Nemotron 3 Super 120B A12B varies by as much as 3.3x across hosts, from $0.15 per Mtok on Vercel AI Gateway to $0.50 per Mtok on Cloudflare Workers AI. This wide spread means the same model is a different product depending on the provider you select for Atlas, offering opportunities for cost optimization.

Is NVIDIA Nemotron 3 Super 120B A12B good for long reasoning tasks in Atlas?

Yes, NVIDIA Nemotron 3 Super 120B A12B is reasoning-capable and well-suited for long reasoning tasks within Atlas, especially when served on NVIDIA NIM. Its 262,144 token context window and matching max output allow for extensive reasoning traces and large diffs to fit within a single call, enhancing Atlas's ability to draft comprehensive plans.

When should I avoid using Cloudflare Workers AI for NVIDIA Nemotron 3 Super 120B A12B?

You should generally avoid Cloudflare Workers AI for NVIDIA Nemotron 3 Super 120B A12B because it is the most expensive option at $0.50/$1.50 per Mtok, and it offers no larger context window than the cheaper providers. There is no upside to choosing this route for Atlas.

How does Atlas leverage the capabilities of NVIDIA Nemotron 3 Super 120B A12B?

Atlas leverages NVIDIA Nemotron 3 Super 120B A12B's reasoning power and large context window for tasks like searching code with Axis, the hybrid semantic and keyword retrieval system, indexing code by AST declarations, drafting plans in a read-only agent, and processing unified diffs. Its ability to handle extensive context helps Atlas perform complex coding tasks and manage git operations effectively.

Can I switch between NVIDIA Nemotron 3 Super 120B A12B and other models in Atlas?

Yes, Atlas allows you to switch the active model and provider on the fly. You can add NVIDIA Nemotron 3 Super 120B A12B to your favorites in the `/models` dialog, enabling `model.cycle_recent` to flip between it and a frontier model mid-session as your task requirements change.

Atlas with NVIDIA Nemotron 3 Super 120B A12B in 2026

NVIDIA Nemotron 3 Super 120B A12B is an excellent choice for Atlas in 2026, providing robust reasoning capabilities at a highly competitive price point, starting at just $0.15 per million input tokens. Its substantial 262,144 token context window on NVIDIA NIM allows Atlas to handle complex codebases and extensive reasoning traces effectively, making it a sweet spot for developers seeking both power and cost efficiency.

What is NVIDIA Nemotron 3 Super 120B A12B best at inside Atlas?

NVIDIA Nemotron 3 Super 120B A12B excels within Atlas for complex reasoning tasks and deep code analysis, leveraging its 120B total parameters with 12B active per token. This model is a sweet spot for developers in 2026 who need robust AI assistance without the prohibitive costs of larger, less efficient models.

Atlas, the terminal-native AI coding agent, benefits significantly from NVIDIA Nemotron 3 Super 120B A12B's reasoning capabilities. This model is adept at processing the extensive context Atlas provides, whether it is searching code with Axis, the hybrid semantic and keyword retrieval system, or analyzing unified diffs for approval before writing. Its ability to handle a 262,144 token context window on NVIDIA NIM means Atlas can feed it entire codebases indexed by AST declarations using tree-sitter, enabling more informed and accurate plan drafting in the read-only plan agent. The model's reasoning power ensures that Atlas can effectively fan out work to subagents and manage complex git operations, from reading branches and status to staging and creating commits on your behalf.

How does NVIDIA Nemotron 3 Super 120B A12B pricing vary across providers?

The input price for NVIDIA Nemotron 3 Super 120B A12B varies by a significant 3.3x across different hosts, starting as low as $0.15 per million input tokens on Vercel AI Gateway. This wide spread means the same model becomes a distinct product depending on where you point Atlas in 2026, offering substantial cost optimization opportunities.

Developers using Atlas in 2026 must carefully consider the provider for NVIDIA Nemotron 3 Super 120B A12B due to its highly variable pricing. Vercel AI Gateway offers the most economical input rate at $0.15 per Mtok, with output at $0.65 per Mtok. NVIDIA NIM follows at $0.20/$0.80 per Mtok, Baseten at $0.30/$0.75 per Mtok, and Nebius at $0.30/$0.90 per Mtok. Cloudflare Workers AI is the most expensive option at $0.50/$1.50 per Mtok, offering no additional context window size over the cheaper alternatives. This pricing disparity underscores the importance of configuring Atlas to use the most cost-effective provider for your specific workload, easily achieved by switching the active model and provider on the fly.

What are the context window capabilities of NVIDIA Nemotron 3 Super 120B A12B?

NVIDIA Nemotron 3 Super 120B A12B offers a substantial context window of 262,144 tokens when served on NVIDIA NIM, with an equally impressive 262,144 max output. For other providers like Vercel, Nebius, and Cloudflare Workers AI, the context window is 256,000 tokens. This large capacity is crucial for Atlas's deep code understanding in 2026.

The generous context window of NVIDIA Nemotron 3 Super 120B A12B is a key advantage for Atlas users. On NVIDIA NIM, the model can process and generate up to 262,144 tokens, allowing for extensive reasoning traces and the inclusion of large unified diffs within a single call. This capability ensures Atlas can maintain a comprehensive understanding of complex tasks, from indexing code by AST declarations to drafting detailed plans. While Vercel, Nebius, and Cloudflare Workers AI provide a slightly smaller but still significant 256,000 token context, the NVIDIA NIM offering stands out for its symmetrical input and output capacity, which is particularly beneficial for iterative problem-solving and detailed code generation within Atlas.

What are the tradeoffs when using NVIDIA Nemotron 3 Super 120B A12B with Atlas?

While NVIDIA Nemotron 3 Super 120B A12B offers excellent input pricing, its output tokens are priced 3x to 4x higher on every host, meaning a chatty thinking budget is what actually costs you money in 2026. For instance, Vercel AI Gateway charges $0.15 for input but $0.65 for output per Mtok.

The primary tradeoff with NVIDIA Nemotron 3 Super 120B A12B, despite its competitive input pricing, lies in the cost of output tokens. Reasoning traces, which are fundamental to Atlas's planning and execution, consume output tokens. With output priced significantly higher than input across all providers,for example, $0.65 per Mtok on Vercel AI Gateway compared to $0.15 input,developers must be mindful of the verbosity of the model's responses. Additionally, Cloudflare Workers AI's listing is both the most expensive at $0.50/$1.50 per Mtok and offers no larger context window than the cheapest options, presenting no upside for that route. For tasks requiring extremely long, detailed outputs or when cost is paramount, developers might need to balance the model's reasoning capabilities against the potential for higher output costs.

When should you consider a different model for Atlas?

While NVIDIA Nemotron 3 Super 120B A12B is a sweet spot for many Atlas workflows in 2026, developers should consider alternative models when output token costs become a dominant factor or when specific frontier model capabilities are required. Its output pricing, ranging from $0.65 to $1.50 per Mtok, can accumulate quickly.

Developers should consider switching from NVIDIA Nemotron 3 Super 120B A12B in Atlas if their primary concern shifts from reasoning capability at a good input price to minimizing overall token expenditure, especially for very chatty tasks. The model's output token pricing, which is 3x to 4x its input cost, can make extensive, verbose interactions expensive. If a task requires minimal reasoning but maximum output efficiency, or if a frontier model offers a unique capability not present in Nemotron 3 Super, then leveraging Atlas's ability to switch the active model and provider on the fly becomes essential. For instance, if a task demands current performance that only the latest, most expensive models can provide, even with a higher per-token cost, that might justify the switch.

Setup

01Export your API key: For the cheapest listing, set `export AI_GATEWAY_API_KEY="your_vercel_key"`. For the largest output window, set `export NVIDIA_API_KEY="your_nvidia_key"`.
02Verify model availability: Run `atlas models vercel` or `atlas models nvidia` and confirm the `nemotron-3-super` row and its context window details.
03Pin the model in `atlas.json`: Add `"model": "vercel/nvidia/nemotron-3-super-120b-a12b"` to your `atlas.json` configuration to default to the $0.15/$0.65 per Mtok Vercel listing.
04Add to favorites: Use the `/models` dialog within Atlas to add NVIDIA Nemotron 3 Super 120B A12B to your favorites, enabling `model.cycle_recent` to quickly switch between it and other models mid-session.

Frequently asked questions

What is the effective context window for NVIDIA Nemotron 3 Super 120B A12B in Atlas?: NVIDIA Nemotron 3 Super 120B A12B provides a 262,144 token context window on NVIDIA NIM, which also supports a 262,144 max output. On Vercel, Nebius, and Cloudflare Workers AI, the context window is 256,000 tokens. This large capacity allows Atlas to process extensive code and complex reasoning.
How much does NVIDIA Nemotron 3 Super 120B A12B cost to use with Atlas?: Pricing for NVIDIA Nemotron 3 Super 120B A12B varies significantly by provider. Input tokens start at $0.15 per Mtok on Vercel AI Gateway, while NVIDIA NIM charges $0.20 per Mtok. Output tokens are generally 3x to 4x more expensive, for example, $0.65 per Mtok on Vercel AI Gateway.
Why is the price of NVIDIA Nemotron 3 Super 120B A12B so different across providers?: The input price for NVIDIA Nemotron 3 Super 120B A12B varies by as much as 3.3x across hosts, from $0.15 per Mtok on Vercel AI Gateway to $0.50 per Mtok on Cloudflare Workers AI. This wide spread means the same model is a different product depending on the provider you select for Atlas, offering opportunities for cost optimization.
Is NVIDIA Nemotron 3 Super 120B A12B good for long reasoning tasks in Atlas?: Yes, NVIDIA Nemotron 3 Super 120B A12B is reasoning-capable and well-suited for long reasoning tasks within Atlas, especially when served on NVIDIA NIM. Its 262,144 token context window and matching max output allow for extensive reasoning traces and large diffs to fit within a single call, enhancing Atlas's ability to draft comprehensive plans.
When should I avoid using Cloudflare Workers AI for NVIDIA Nemotron 3 Super 120B A12B?: You should generally avoid Cloudflare Workers AI for NVIDIA Nemotron 3 Super 120B A12B because it is the most expensive option at $0.50/$1.50 per Mtok, and it offers no larger context window than the cheaper providers. There is no upside to choosing this route for Atlas.
How does Atlas leverage the capabilities of NVIDIA Nemotron 3 Super 120B A12B?: Atlas leverages NVIDIA Nemotron 3 Super 120B A12B's reasoning power and large context window for tasks like searching code with Axis, the hybrid semantic and keyword retrieval system, indexing code by AST declarations, drafting plans in a read-only agent, and processing unified diffs. Its ability to handle extensive context helps Atlas perform complex coding tasks and manage git operations effectively.
Can I switch between NVIDIA Nemotron 3 Super 120B A12B and other models in Atlas?: Yes, Atlas allows you to switch the active model and provider on the fly. You can add NVIDIA Nemotron 3 Super 120B A12B to your favorites in the `/models` dialog, enabling `model.cycle_recent` to flip between it and a frontier model mid-session as your task requirements change.

Try SeaShell in your terminal

The terminal-native AI coding agent. Free core, single binary.

Install SeaShell

Related guides

Atlas for Fiber in 2026

Atlas is a terminal-native AI coding agent for Fiber in 2026. It knows fasthttp reuses buffers, tests handlers with app.Test(), and diffs every edit first.

Atlas for React Native: Terminal-Native AI Coding Across the Native Boundary in 2026

Atlas is a terminal-native AI coding agent for React Native in 2026. Work across the New Architecture, native modules, and platform-specific files with diff-first review.

Atlas vs Mistral Vibe for Code: Terminal AI Coding Agents in 2026

Compare Atlas and Mistral Vibe for Code in 2026. Atlas offers terminal-native TUI, permission-gated tools, and local embeddings. Mistral Vibe provides a four-model stack and EU data sovereignty.

Atlas for Axum in 2026

Atlas is a terminal-native AI coding agent for Axum in 2026. It decodes tower trait-bound errors, adds IntoResponse types, and runs cargo nextest run.

Atlas for Angular in 2026

Adopt Atlas, the terminal-native AI coding agent, for your Angular projects in 2026. Enhance development with intelligent code search, secure local embeddings, and granular control over AI actions.

Atlas vs Cosine: Choosing Your AI Coding Agent in 2026

Compare Atlas and Cosine AI coding agents for 2026. Atlas offers terminal-native TUI, explicit change review, and BYO model keys. Cosine features its Lumen models and a 30.08% SWE-bench record.

Atlas for Nim: A Terminal-Native AI Coding Agent for Nimble Packages and Macros in 2026

Atlas is a terminal-native AI coding agent for Nim in 2026. It reads .nimble requires and asterisk-exported symbols, adds std/unittest suites, runs nimble test, formats with nph.

Atlas vs GitHub Copilot: Terminal AI Coding Agents in 2026

Atlas vs GitHub Copilot in 2026: Compare terminal-native AI coding agents. Atlas offers deep planning and diff review, while GitHub Copilot excels in inline autocomplete and GitHub integration.

Browse this resource hub