How much does GPT-OSS 20B (hosted) cost to use with Atlas?

The cost for GPT-OSS 20B (hosted) varies by provider. DeepInfra offers the most competitive pricing at $0.03 per Mtok for input and $0.14 per Mtok for output. Other providers range from $0.05/$0.20 (Together AI, Databricks) to $0.20/$0.30 (Cloudflare Workers AI). Running it locally via LM Studio costs $0.00 per Mtok.

Is GPT-OSS 20B (hosted) suitable for complex code generation in Atlas?

GPT-OSS 20B (hosted) is a 20B parameter model best suited for helper roles, subagents, and summarization within Atlas. It provides reasoning capabilities but is not designed as an architect-grade model for complex, large-scale code generation. For such tasks, Atlas users should select a more powerful model for the main slot.

Can I use GPT-OSS 20B (hosted) for private, local development with Atlas?

Yes, GPT-OSS 20B (hosted) can be run entirely locally using LM Studio at no cost. This setup provides the full 131,072 token context window and a 32,768 max output, ensuring privacy as no code leaves your machine, especially when combined with local Ollama embeddings for Atlas's indexing.

What are the performance benefits of using GPT-OSS 20B (hosted) on Groq?

When served on Groq's LPU hardware, GPT-OSS 20B (hosted) is available at $0.075 per Mtok for input and $0.30 per Mtok for output. This configuration provides a 65,536 max output and delivers near-instant time-to-first-token, making it an excellent choice for rapid, interactive tasks within Atlas where speed is paramount.

How does Atlas use GPT-OSS 20B (hosted) for code search?

Atlas can leverage GPT-OSS 20B (hosted) to enhance its Axis, the hybrid semantic and keyword code search. While Atlas indexes code by AST declarations using tree-sitter and can use local Ollama embeddings, GPT-OSS 20B can assist in understanding and processing search queries or summarizing search results, benefiting from its reasoning capabilities and large 131,072 token context window.

Why is the provider choice important for GPT-OSS 20B (hosted)?

Provider choice is crucial due to significant pricing and context window variations. DeepInfra offers the lowest input cost at $0.03 per Mtok with a 131,072 token window. In contrast, Cloudflare charges $0.20 per Mtok for input, nearly 7 times more, and provides a slightly smaller 128,000 token window for the same model weights. Selecting the right provider can drastically impact operational costs for Atlas users.

Atlas with GPT-OSS 20B (hosted) in 2026

GPT-OSS 20B (hosted) is an excellent choice for Atlas's `small_model` slot in 2026, providing reasoning capabilities at a highly competitive price point. Starting at just $0.03 per Mtok on DeepInfra, it offers a substantial 131,072 token context window, making it suitable for tasks like summarization, subagent operations, and general assistance within Atlas.

What is GPT-OSS 20B (hosted) best for in Atlas?

GPT-OSS 20B (hosted) excels as the default for Atlas's `small_model` slot, offering robust reasoning capabilities at an economical price point of $0.03 per Mtok on DeepInfra. This 20B parameter model is specifically designed to handle tasks where a thinking model is required without the overhead of a larger, more expensive architect-grade solution.

In 2026, Atlas developers will find GPT-OSS 20B (hosted) to be an ideal companion for enhancing their coding workflow. It is particularly well-suited for driving subagents, generating concise summaries, and handling various helper functions within Atlas. Its Apache license and open weights make it a flexible choice. Atlas leverages this model for tasks that benefit from a reasoning-enabled agent, ensuring that even the 'cheap slot' can contribute intelligently to problem-solving. For instance, when Atlas drafts a plan in its read-only plan agent, GPT-OSS 20B can efficiently process and summarize information, asking for approval before switching to a build agent. Atlas's ability to fan out work to subagents, which can run in the foreground or in parallel background sessions, is significantly bolstered by the cost-effective reasoning of GPT-OSS 20B.

What are the cost and context window tradeoffs for GPT-OSS 20B (hosted)?

GPT-OSS 20B (hosted) offers a substantial 131,072 token context window across most providers, with DeepInfra providing the most cost-effective access at $0.03 per Mtok for input. However, pricing varies significantly, with Cloudflare Workers AI charging nearly 7 times more for input tokens at $0.20 per Mtok for the same weights but a slightly smaller 128,000 token window.

Developers evaluating GPT-OSS 20B (hosted) for Atlas in 2026 must consider the significant pricing differences across providers. While DeepInfra offers an attractive $0.03 per Mtok for input and $0.14 per Mtok for output, other providers like Together AI and Databricks charge $0.05/$0.20 per Mtok. Fireworks and Groq are priced at $0.07/$0.30 and $0.075/$0.30 respectively. Hugging Face charges $0.10/$0.50. The most notable tradeoff is with Cloudflare Workers AI, which charges $0.20 per Mtok for input and $0.30 per Mtok for output, representing a nearly 7x increase in input cost compared to DeepInfra, alongside a slightly reduced context window of 128,000 tokens. This highlights that host choice is critical for managing operational costs, even for a model of this size. The 131,072 token context window is consistent across DeepInfra, Together AI, Databricks, Fireworks, Groq, and LM Studio, providing ample space for complex code analysis and summarization tasks within Atlas.

When should I choose a different model over GPT-OSS 20B (hosted)?

While GPT-OSS 20B (hosted) is an excellent helper model, its 20 billion parameters mean it is not designed to be an architect-grade solution for complex, high-level coding tasks. For primary agent roles requiring deep architectural understanding or extensive code generation, a more powerful model should be selected for Atlas's main slot.

GPT-OSS 20B (hosted) is best utilized for its intended purpose: supporting Atlas as a 'small_model' for specific, focused tasks. If your primary need is for a model to act as the central coding architect, capable of generating large, intricate codebases or making high-level design decisions, then GPT-OSS 20B will fall short. Its 20B parameter count positions it as a capable reasoning assistant, but not a standalone coding powerhouse. Atlas allows you to switch the active model and provider on the fly, making it easy to pair GPT-OSS 20B in the `small_model` slot with a more robust, dedicated coding model in the main slot. This strategy ensures you leverage the cost-effectiveness and reasoning of GPT-OSS 20B for summarization and subagent work, while reserving a more powerful model for core development tasks where Atlas drafts a plan, computes unified diffs, and stages commits on your behalf.

Can GPT-OSS 20B (hosted) run locally with Atlas?

Yes, GPT-OSS 20B (hosted) can run entirely locally within LM Studio at zero cost, offering the same 131,072 token context window as its hosted counterparts. This local option provides a 32,768 token maximum output, making it a drop-in swap for the hosted versions and ideal for privacy-conscious developers in 2026.

For developers prioritizing data privacy or seeking to eliminate API costs, GPT-OSS 20B offers a fully local deployment option through LM Studio. Running the model locally at $0.00 per Mtok means no code leaves your machine, especially when paired with local Ollama embeddings for Atlas's code indexing. Atlas indexes code by AST declarations using tree-sitter, not blind line windows, and can build its code index with local Ollama embeddings, keeping code off third-party servers. This local setup provides the identical 131,072 token context window, ensuring consistent performance for tasks like code search with Axis, the hybrid semantic and keyword retrieval fused by reciprocal rank fusion. The local version also supports a substantial 32,768 token maximum output, making it a powerful and private choice for Atlas users.

Setup

01For hosted access via DeepInfra, export your API key: `export DEEPINFRA_API_KEY='your_api_key_here'`.
02Confirm Atlas recognizes the model by running: `atlas models deepinfra` (or `atlas models lmstudio` for local).
03Configure Atlas to use GPT-OSS 20B for small model tasks by setting in `atlas.json`: `"small_model": "deepinfra/openai/gpt-oss-20b"`.
04To run locally, install LM Studio and ensure it's running on port 1234 with GPT-OSS 20B loaded.
05For a fully local setup, update `atlas.json` to: `"small_model": "lmstudio/openai/gpt-oss-20b"`.
06Pair the local LM Studio setup with local Ollama embeddings to keep all code processing on your machine.

Frequently asked questions

What is the context window size for GPT-OSS 20B (hosted) in Atlas?: GPT-OSS 20B (hosted) provides a 131,072 token context window when accessed via providers like DeepInfra, Together AI, Databricks, Fireworks, Groq, and LM Studio. Cloudflare Workers AI offers a slightly smaller 128,000 token window for this model.
How much does GPT-OSS 20B (hosted) cost to use with Atlas?: The cost for GPT-OSS 20B (hosted) varies by provider. DeepInfra offers the most competitive pricing at $0.03 per Mtok for input and $0.14 per Mtok for output. Other providers range from $0.05/$0.20 (Together AI, Databricks) to $0.20/$0.30 (Cloudflare Workers AI). Running it locally via LM Studio costs $0.00 per Mtok.
Is GPT-OSS 20B (hosted) suitable for complex code generation in Atlas?: GPT-OSS 20B (hosted) is a 20B parameter model best suited for helper roles, subagents, and summarization within Atlas. It provides reasoning capabilities but is not designed as an architect-grade model for complex, large-scale code generation. For such tasks, Atlas users should select a more powerful model for the main slot.
Can I use GPT-OSS 20B (hosted) for private, local development with Atlas?: Yes, GPT-OSS 20B (hosted) can be run entirely locally using LM Studio at no cost. This setup provides the full 131,072 token context window and a 32,768 max output, ensuring privacy as no code leaves your machine, especially when combined with local Ollama embeddings for Atlas's indexing.
What are the performance benefits of using GPT-OSS 20B (hosted) on Groq?: When served on Groq's LPU hardware, GPT-OSS 20B (hosted) is available at $0.075 per Mtok for input and $0.30 per Mtok for output. This configuration provides a 65,536 max output and delivers near-instant time-to-first-token, making it an excellent choice for rapid, interactive tasks within Atlas where speed is paramount.
How does Atlas use GPT-OSS 20B (hosted) for code search?: Atlas can leverage GPT-OSS 20B (hosted) to enhance its Axis, the hybrid semantic and keyword code search. While Atlas indexes code by AST declarations using tree-sitter and can use local Ollama embeddings, GPT-OSS 20B can assist in understanding and processing search queries or summarizing search results, benefiting from its reasoning capabilities and large 131,072 token context window.
Why is the provider choice important for GPT-OSS 20B (hosted)?: Provider choice is crucial due to significant pricing and context window variations. DeepInfra offers the lowest input cost at $0.03 per Mtok with a 131,072 token window. In contrast, Cloudflare charges $0.20 per Mtok for input, nearly 7 times more, and provides a slightly smaller 128,000 token window for the same model weights. Selecting the right provider can drastically impact operational costs for Atlas users.

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