Grok Code Fast 1 vs Llama 3.2 1B Instruct
Grok Code Fast 1 (2025) and Llama 3.2 1B Instruct (2024) are agentic coding models from xAI and AI at Meta. Grok Code Fast 1 ships a 262K-token context window, while Llama 3.2 1B Instruct ships a 128K-token context window. On pricing, Llama 3.2 1B Instruct costs $0.03/1M input tokens versus $0.2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3.2 1B Instruct is ~641% cheaper at $0.03/1M; pay for Grok Code Fast 1 only for coding workflow support.
Specs
| Released | 2025-08-27 | 2024-09-25 |
| Context window | 262K | 128K |
| Parameters | 314B | 1.23B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Grok Code Fast 1 | Llama 3.2 1B Instruct | |
|---|---|---|
| Input price | $0.2/1M tokens | $0.03/1M tokens |
| Output price | $1.5/1M tokens | $0.2/1M tokens |
| Providers |
Capabilities
| Grok Code Fast 1 | Llama 3.2 1B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: Grok Code Fast 1 and tool use: Grok Code Fast 1. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Grok Code Fast 1 lists $0.2/1M input and $1.5/1M output tokens, while Llama 3.2 1B Instruct lists $0.03/1M input and $0.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 1B Instruct lower by about $0.51 per million blended tokens. Availability is 1 providers versus 5, so concentration risk also matters.
Choose Grok Code Fast 1 when coding workflow support and larger context windows are central to the workload. Choose Llama 3.2 1B Instruct when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, Grok Code Fast 1 or Llama 3.2 1B Instruct?
Grok Code Fast 1 supports 262K tokens, while Llama 3.2 1B Instruct supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Grok Code Fast 1 or Llama 3.2 1B Instruct?
Llama 3.2 1B Instruct is cheaper on tracked token pricing. Grok Code Fast 1 costs $0.2/1M input and $1.5/1M output tokens. Llama 3.2 1B Instruct costs $0.03/1M input and $0.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Grok Code Fast 1 or Llama 3.2 1B Instruct open source?
Grok Code Fast 1 is listed under Proprietary. Llama 3.2 1B Instruct is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for function calling, Grok Code Fast 1 or Llama 3.2 1B Instruct?
Grok Code Fast 1 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Grok Code Fast 1 or Llama 3.2 1B Instruct?
Grok Code Fast 1 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Grok Code Fast 1 and Llama 3.2 1B Instruct?
Grok Code Fast 1 is available on OpenRouter. Llama 3.2 1B Instruct is available on OpenRouter, Fireworks AI, NVIDIA NIM, Bitdeer AI, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.