IBM Granite 4.1 8B is the step up from Micro: a dense 8B model at $0.05/$0.10 per Mtok with a 131,072 token context where max output equals the full window. Symmetric-ish pricing and full-window output make it a surprisingly practical worker model inside Atlas. OpenRouter and W&B Inference both list Granite 4.1 8B at $0.05/$0.10 per Mtok. Output is only 2x input, where most models charge 4x to 10x, so verbose generations do not spike the bill. The limit is scale: 8B dense is a worker, not an architect.
Why does IBM Granite 4.1 8B charge only 2x for output tokens?
IBM Granite 4.1 8B prices output at only 2x input, $0.05 to $0.10 per Mtok, where most models charge 4x to 10x. For an agent like Atlas that generates code continuously, a 2x output multiplier means verbose generations do not spike the bill the way they do elsewhere.
Output pricing is where most coding agent budgets go wrong. A model that charges 8x for output turns every long generation into a surprise. Granite 4.1 8B's $0.05/$0.10 per Mtok structure means the cost of writing code is roughly twice the cost of reading it, which is a ratio you can actually plan against. Inside Atlas that changes what you allow the model to do. Atlas computes a unified diff for every file edit and surfaces it for approval before writing, so a model that emits a large diff cheaply is one whose output you review rather than ration. Both OpenRouter and W&B Inference list Granite 4.1 8B at $0.05/$0.10 per Mtok, so the price is consistent across the two routes.
Can IBM Granite 4.1 8B emit a full file rewrite in one call?
Yes. IBM Granite 4.1 8B has max output equal to its full 131,072 token context, so it can emit a very large file rewrite in a single call without truncation. That property is rare, and it is the strongest technical argument for Granite 4.1 8B in a coding agent.
Most models cap output far below their context, which forces an agent to chunk a rewrite across multiple turns and hope the pieces reconcile. Granite 4.1 8B does not have that problem: the 131,072 token context and the 131,072 token max output are the same number. Because output runs to the full 131,072 tokens, Atlas's unified-diff review is the safety net. Read the diff before accepting a large rewrite. Atlas snapshots file changes as git patches so edits can be diffed and rolled back, so a large single-shot rewrite that goes wrong is a `git` operation away from being undone, not a manual repair job.
Why do enterprises choose Granite 4.1 8B over Qwen or Llama at the same size?
IBM Granite 4.1 8B is Apache 2.0 licensed with IBM's published data-provenance documentation, which is the whole reason enterprises pick Granite over a comparable Qwen or Llama at the same size. At $0.05/$0.10 per Mtok the price is not the differentiator. Provenance is.
An 8B open-weights model is a commodity in 2026. What is not commodity is a paper trail describing what trained it. IBM publishes that for Granite 4.1 8B alongside an Apache 2.0 license, and for teams whose legal function has an opinion about their coding assistant, that documentation is the deciding factor. Atlas complements the same posture from the infrastructure side. Atlas can build its code index with local Ollama embeddings, keeping code off third-party servers, and every Atlas tool call is permission-gated against allow, ask, and deny rules before it runs. Provenance on the model, containment on the agent.
What are the limits of IBM Granite 4.1 8B in Atlas?
IBM Granite 4.1 8B is a dense 8B model, and 8B dense is a worker, not an architect. Granite 4.1 8B will not hold the cross-file invariants that a 120B MoE handles on a real refactor, regardless of how large its 131,072 token output window is.
Granite 4.1 8B's honest limits are two. First, capacity: a large output ceiling lets it write a lot, but writing a lot is not the same as holding a mental model of a codebase. A multi-file refactor with real invariants belongs on a larger model, and Atlas lets you switch the active model and provider on the fly with favorites and recents, so keeping Granite 4.1 8B as `"small_model"` under a frontier build model is a reasonable middle ground. Second, distribution: Granite 4.1 8B is not carried by the big first-party inference providers in the registry, so you reach it through an aggregator like OpenRouter or W&B Inference rather than direct.
How do you set up Atlas with IBM Granite 4.1 8B?
Setting up Atlas on IBM Granite 4.1 8B takes three steps: export OPENROUTER_API_KEY, run `atlas models openrouter`, and pin the `ibm-granite/granite-4.1-8b` row in atlas.json. The model resolves at $0.05/$0.10 per Mtok with a 131,072 token context.
Because IBM Granite 4.1 8B is reached through an aggregator, the auth step is OpenRouter's, not IBM's. Export OPENROUTER_API_KEY, or run `atlas login` and pick OpenRouter, then run `atlas models openrouter` and find the `ibm-granite/granite-4.1-8b` row to confirm the model resolved. Pin `"model": "openrouter/ibm-granite/granite-4.1-8b"` in atlas.json, or use it as `"small_model"` under a frontier build model, depending on which role you want it in. W&B Inference carries the same listing at the same $0.05/$0.10 per Mtok if you prefer that route.
Setup
- 01Export OPENROUTER_API_KEY (or run `atlas login` and pick OpenRouter).
- 02Run `atlas models openrouter` and find the `ibm-granite/granite-4.1-8b` row.
- 03Pin `"model": "openrouter/ibm-granite/granite-4.1-8b"` in atlas.json, or use it as `"small_model"` under a frontier build model.
- 04Because output runs to the full 131,072 tokens, Atlas's unified-diff review is the safety net. Read the diff before accepting a large rewrite.
- 05W&B Inference lists Granite 4.1 8B at the same $0.05/$0.10 per Mtok if you prefer that route over OpenRouter.
Frequently asked questions
- how much does ibm granite 4.1 8b cost per million tokens
- IBM Granite 4.1 8B is $0.05/$0.10 per Mtok on both OpenRouter and W&B Inference. Output is only 2x input, where most models charge 4x to 10x, so verbose generations do not spike the bill.
- what is the max output of granite 4.1 8b
- Granite 4.1 8B has max output equal to its full 131,072 token context on OpenRouter and W&B Inference, so it can emit a very large file rewrite in a single call without truncation.
- granite 4.1 8b vs granite 4.0 h micro
- Granite 4.1 8B is the step up from Micro: a dense 8B model at $0.05/$0.10 per Mtok with a 131,072 token context where max output equals the full window. Granite 4.0 H Micro is cheaper but is a micro model built for titles and summaries.
- how do I run atlas on ibm granite 4.1 8b
- Export OPENROUTER_API_KEY or run `atlas login` and pick OpenRouter, run `atlas models openrouter` and find the `ibm-granite/granite-4.1-8b` row, then pin `"model": "openrouter/ibm-granite/granite-4.1-8b"` in atlas.json.
- is granite 4.1 8b good enough for refactoring
- For scoped work, yes. For a real refactor, no. 8B dense is a worker, not an architect, and Granite 4.1 8B will not hold the cross-file invariants that a 120B MoE handles.
- why do enterprises use ibm granite instead of llama
- Granite 4.1 8B is Apache 2.0 licensed with IBM's published data-provenance documentation, which is the whole reason enterprises pick Granite over a comparable Qwen or Llama at the same size.
- which providers host ibm granite 4.1 8b
- OpenRouter and W&B Inference, both at $0.05/$0.10 per Mtok. Granite 4.1 8B is not carried by the big first-party inference providers in the registry, so you reach it through an aggregator rather than direct.
Try Atlas in your terminal
The terminal-native AI coding agent. Free core, single binary.
Install AtlasRelated guides
Atlas vs Ellipsis: Terminal AI Coding Agents in 2026
Compare Atlas, a terminal-native AI coding agent with free core and local embeddings, against Ellipsis, a cloud platform with usage-based pricing and live session tracing for 2026.
Atlas for OCaml: A Terminal-Native AI Coding Agent for dune and opam Projects in 2026
Atlas is a terminal-native AI coding agent for OCaml in 2026. It reads dune stanzas and .mli signatures, runs dune runtest behind a prompt, and finishes with ocamlformat.
Atlas for Astro: Islands, Content Collections, and Zero JS by Default in 2026
Atlas is a terminal-native AI coding agent for Astro in 2026. It reads astro.config.mjs, src/pages, and content collection schemas, drops needless client:load directives, and runs astro check.
Run Atlas Headless in CI with Atlas (2026 Workflow)
How to run Atlas headless in CI in 2026: atlas run sends one prompt and exits when the session goes idle, with --format json, --command, and --continue for pipeline steps.
Atlas for Zig: A Terminal-Native AI Coding Agent for build.zig Projects in 2026
Atlas is a terminal-native AI coding agent for Zig in 2026. It reads build.zig and comptime blocks, tracks your allocators, runs zig build test behind a prompt, and runs zig fmt.
Atlas vs Gemini CLI: A Developer's Guide to Terminal AI Agents in 2026
Atlas vs Gemini CLI in 2026: Compare terminal AI coding agents. Atlas offers permission-gated tool calls and diff-based approvals. Gemini CLI provides a million-plus token context and a free tier.
Atlas for SQL in 2026
Atlas is a terminal-native AI coding agent for SQL in 2026. Run it in a repo with your migrations or .sql files, optimize a query, and review the diff before applying.
Atlas vs Augment Code: Choosing a Terminal AI Coding Agent in 2026
In 2026, Atlas offers a free, terminal-native AI agent with local embeddings and robust safety. Augment Code's Cosmos platform provides shared memory for teams at $100/month.