# Atlas with IBM Granite Code 8B (Ollama): 125K Context on 4.6GB in 2026

> IBM Granite Code 8B (Ollama) offers a 125K tokens context from a 4.6GB download and is Free (self-hosted).

IBM Granite Code 8B (Ollama) is IBM's enterprise code model, a 4.6GB download that carries a 125K tokens context on the instruct tag. Inside Atlas it is the model to pick when you need a long window and a procurement story at the same time. Pricing is Free (self-hosted). The window at that size is the headline: most 8B code models cap at 8K or 16K, and Granite Code gives you an order of magnitude more. Raw coding ability trails Qwen2.5-Coder 7B, so you are buying context and provenance, not benchmark wins.

## Key takeaways

- IBM Granite Code 8B (Ollama) carries a 125K tokens context on the instruct tag from a 4.6GB download.
- Pricing is Free (self-hosted); serving takes roughly 7GB, so a long-context code model runs on an 8GB card.
- Most 8B code models cap at 8K or 16K, and Granite Code gives you an order of magnitude more.
- Pull granite-code:8b-instruct, not the base tags: the 8b-base tag renders 4K.
- Raw coding ability trails Qwen2.5-Coder 7B; you are buying context and provenance, not benchmark wins.

## Why does IBM Granite Code 8B have a 125K context at only 4.6GB?

IBM Granite Code 8B (Ollama) ships a 125K tokens window on its instruct tag from a 4.6GB download, far beyond the 8K to 16K typical of this size class. That combination is the model's entire reason to exist and the single fact that should drive an Atlas configuration decision.

For an Atlas user the practical meaning of 125K tokens is that a long agentic session survives. Atlas fans out work to subagents that can run in the foreground or in parallel background sessions, and each of those sessions accumulates tool output, file reads, and diffs. An 8K model compacts constantly under that load. IBM Granite Code 8B at 125K tokens can hold a long tool transcript intact, which keeps the agent's own reasoning coherent across a multi-step task. The download is 4.6GB and serving takes roughly 7GB, so a very long-context code model runs on an 8GB card. Be precise about the tag: the base variants show much smaller windows, and the 8b-base tag renders 4K.

## Is IBM Granite Code 8B good enough to write Atlas diffs?

IBM Granite Code 8B (Ollama) writes usable diffs, but its raw coding ability trails Qwen2.5-Coder 7B. Inside Atlas that is an honest tradeoff, not a disqualification: you are buying a 125K tokens window and IBM provenance documentation, not a benchmark win at the 8B tier.

Atlas computes a unified diff for every file edit and surfaces it for approval before writing, which changes how much the benchmark gap costs you in practice. A Granite Code patch that is slightly worse than a Qwen2.5-Coder patch is still a diff you review before it touches disk. Atlas also snapshots file changes as git patches so edits can be diffed and rolled back, so a weaker patch is recoverable. Where IBM Granite Code 8B earns its place is the tasks a short-window coder simply cannot attempt: tracing a change across a dozen files, or reasoning over a long build log that a 16K model would have to truncate before it could read the failure.

## Does IBM Granite Code 8B clear enterprise procurement?

IBM publishes Granite Code 8B (Ollama) with enterprise licensing and provenance documentation, which clears procurement in places a research release does not. For an Atlas deployment inside a regulated organization in 2026, that paperwork is often the deciding factor rather than the model's coding score.

IBM Granite Code 8B pairs well with the Atlas controls that a security review will actually ask about. Every Atlas tool call is permission-gated against allow, ask, and deny rules before it runs. Atlas drafts a plan in a read-only plan agent and asks before switching to a build agent. Atlas can build its code index with local Ollama embeddings, keeping code off third-party servers, so an enterprise-licensed model is fed by an entirely on-premise retrieval layer. That is the full story a procurement team wants: a licensed model with documented provenance, running on your hardware, retrieving from vectors your hardware produced, gated by rules you wrote, at a price of Free (self-hosted).

## Which Granite Code tag should you pull for Atlas?

Pull the instruct tag specifically: ollama pull granite-code:8b-instruct (4.6GB). IBM Granite Code 8B's base variants show much smaller windows, and the 8b-base tag renders 4K, so pulling the wrong tag costs you the 125K tokens context that was the reason to choose the model.

The plain 8b tag is the same 4.6GB size, but the instruct tag is what you want for Atlas, which is a conversational tool-calling agent rather than a completion engine. Register granite-code:8b-instruct in the atlas.json ollama models map with limit.context 125000 and limit.output 8192, then set model to ollama/granite-code:8b-instruct and verify with atlas models ollama. One memory caveat that trips people: grow Ollama's num_ctx toward the full window incrementally, because the roughly 7GB figure covers weights, not a 125K KV cache. Asking for the whole window on day one on an 8GB card will not end well.

## When should you pick a different model than IBM Granite Code 8B?

Choose something else when peak code quality at 8B is the goal, because IBM Granite Code 8B (Ollama) trails Qwen2.5-Coder 7B on raw coding ability. Atlas lets you switch the active model and provider on the fly with favorites and recents, so the choice is per task, not per project.

IBM Granite Code 8B is the right answer for long transcripts, enterprise licensing, and provenance documentation. It is the wrong answer if you have no procurement constraint, no long-context need, and simply want the strongest small coder you can serve on an 8GB card. A workable split is to keep granite-code:8b-instruct as the favorite for long, cross-file sessions where the 125K tokens window is doing real work, and switch to a stronger coder for tight, single-file patches. Both are Free (self-hosted), so running two tags costs disk, not money.

## Setup

1. Pull the instruct tag specifically: ollama pull granite-code:8b-instruct (4.6GB). The plain 8b tag is the same size.
2. Register granite-code:8b-instruct in the atlas.json ollama models map with limit.context 125000 and limit.output 8192.
3. Grow Ollama's num_ctx toward the full window incrementally; the 7GB figure covers weights, not a 125K KV cache.
4. Set model to ollama/granite-code:8b-instruct and verify with atlas models ollama.
5. Run the codebase index with Ollama embeddings so an enterprise-licensed model is fed by an entirely on-premise retrieval layer.

## FAQ

### how to run atlas on ibm granite code 8b

Run ollama pull granite-code:8b-instruct (4.6GB), register it in the atlas.json ollama models map with limit.context 125000 and limit.output 8192, set model to ollama/granite-code:8b-instruct, and verify with atlas models ollama.

### what is granite code 8b's context window

IBM Granite Code 8B (Ollama) has a 125K tokens context on the instruct tag. The base variants show much smaller windows, and the 8b-base tag renders 4K, so pull the instruct tag.

### granite-code 8b vs qwen2.5-coder 7b for coding

IBM Granite Code 8B's raw coding ability trails Qwen2.5-Coder 7B. Granite Code's advantages are its 125K tokens context and IBM's enterprise licensing with provenance documentation, not benchmark wins.

### how much vram do i need for granite code 8b

IBM Granite Code 8B is a 4.6GB download and takes roughly 7GB to serve, so it fits an 8GB card. That figure covers weights, not a 125K KV cache, so raise num_ctx incrementally.

### is ibm granite code free to use

IBM Granite Code 8B (Ollama) is Free (self-hosted). IBM publishes it with enterprise licensing and provenance documentation, which clears procurement in places a research release does not.

### why does granite-code:8b-base only show 4k context

The base variants of IBM Granite Code 8B show much smaller windows, and the 8b-base tag renders 4K. Pull granite-code:8b-instruct if you want the 125K tokens context.

### can granite code 8b run fully offline with atlas

Yes. Serve granite-code:8b-instruct through Ollama and run the codebase index with Ollama embeddings, since Atlas can build its code index with local Ollama embeddings, keeping code off third-party servers.

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