Lesson 87 of 1570
Grok-Code — coding benchmarks and reality
xAI's code-specialist model ships strong benchmarks. Here is how it actually feels in a real IDE.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1A coding model with attitude
- 2What it does well
- 3Grok-Code
- 4SWE-bench
Concept cluster
Terms to connect while reading
Section 1
A coding model with attitude
Grok-Code is xAI's specialist fine-tune aimed at developer workflows. Reported SWE-bench scores land in the top tier, and the pricing is aggressive — roughly half of Sonnet for comparable coding tasks.
Section 2
What it does well
- Multi-file edits with explicit diffs
- Refactors that touch imports and types coherently
- Shell + test-runner tool use
- Explaining legacy code in plain English
Compare the options
| Tool | Grok-Code | Claude Sonnet 4.6 | GPT-5.5 |
|---|---|---|---|
| SWE-bench (reported) | High | High | High |
| Price per M output | $ | $$ | $$$ |
| IDE integrations | Growing | Mature (Claude Code) | Mature (Codex) |
| Refusal tendency | Low | Medium | Medium |
OpenAI-compatible — drop into any existing Codex-style harness.
client = OpenAI(api_key=os.environ["XAI_API_KEY"], base_url="https://api.x.ai/v1")
resp = client.chat.completions.create(model="grok-code", messages=msgs)Key terms in this lesson
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