Grok Code Fast 1 vs Llama 4 Scout

Grok Code Fast 1 and Llama 4 Scout are both large language models tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Grok Code Fast 1

<cite index="2-1">Released in late August 2025, the xAI Grok Code Fast 1 model is a coding-focused AI model that excels at common, high-volume coding task and is designed especially for agentic coding workflows.</cite> <cite index="1-6,1-7,1-8">Built from scratch with a brand-new model architecture, it was trained on a pre-training corpus rich with programming-related content, and curated high-quality datasets that reflect real-world pull requests and coding tasks.</cite> <cite index="1-23">The model is particularly adept at TypeScript, Python, Java, Rust, C++, and Go.</cite> <cite index="1-13">The model is generally available via the xAI API, priced at $0.20 / 1M input tokens, $1.50 / 1M output tokens, and $0.02 / 1M cached input tokens.</cite>

Llama 4 Scout

Scout carries a 10M token context window, meaning you can feed it an entire codebase or a stack of legal documents in a single pass without chunking pipelines or retrieval hacks. Maverick trades raw context depth for stronger multimodal reasoning, handling interleaved image and text inputs through native early-fusion architecture rather than a bolted-on vision adapter. Both models ship as open weights, downloadable from Hugging Face after license acceptance, with no API bill required if you run them yourself. The ceiling appears at inference: the Mixture-of-Experts architecture demands hardware that most teams do not have sitting idle, and running Scout's full 10M context window in practice requires significant GPU memory that a standard cloud instance will not cover.

Attribute	Grok Code Fast 1	Llama 4 Scout
Pricing	Paid	Free
Price	$30/month	—
Free trial	0 days	No
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	<cite index="30-1">Available through xAI API and integrated with launch partners including GitHub Copilot, Cursor, Cline, Roo Code, Kilo Code, opencode, and Windsurf</cite>	Linux, macOS, Windows (via HuggingFace, llama.com, Ollama, container environments)
Languages	<cite index="1-23">TypeScript, Python, Java, Rust, C++, and Go</cite>	Arabic, English, French, German, Hindi, Indonesian, Italian, Portuguese, Spanish, Tagalog, Thai, Vietnamese
Released	2025-08-28	2025-04-05
Pros	<cite index="2-25,2-26">Massive throughput of approximately 90-100 tokens per second, delivering dozens of tool calls and edits before you finish reading its initial plan in IDE integrations</cite> <cite index="1-13">Economical pricing at $0.20/1M input tokens and $1.50/1M output tokens</cite> <cite index="2-27,2-28,2-29">Visible reasoning traces that provide real-time, summarized view of its reasoning process, helping developers catch logic errors early</cite> <cite index="1-22">Prompt caching optimizations regularly achieving cache hit rates above 90% when used with launch partners</cite>	10M token context window on Scout, so you can pass an entire large codebase or document corpus in a single inference call without building a retrieval pipeline to chunk and re-rank content. Native early-fusion multimodality on Maverick, meaning image and text inputs are processed in the same model pass, so you avoid stitching together a separate vision encoder and a language model with a custom integration layer. Open weights downloadable at no cost after license acceptance, so your inference bill is your hardware cost alone — no per-token API charges accumulating against a usage cap. MoE architecture activates only a subset of parameters per inference pass, which means lower per-token compute cost compared to a dense model at equivalent parameter count, giving your GPU budget more headroom. Self-hosted deployment option, so sensitive document content or regulated data never leaves your infrastructure — which closes the door on the data-residency objections that block most SaaS LLM integrations in enterprise procurement.
Cons	<cite index="6-31,6-34">Potential gaps in training on specific frameworks; poor performance on Tailwind CSS v3 tasks, suggesting possible smaller model size limitations</cite> <cite index="6-36">Its reasoning model nature makes it unsuitable for interactive workflows requiring fast responses despite fast token throughput</cite>	Running Scout's 10M context window at the hardware level requires GPU memory that exceeds a standard single-node cloud instance — teams hitting this wall either partition across multiple nodes with custom serving infrastructure or drop to a shorter effective context, which eliminates the primary reason to choose Scout over smaller models. The Llama 4 Community License is not a standard open-source license; it contains commercial use restrictions that legal review at larger enterprises frequently flags, and teams operating at scale or in regulated industries have switched to models carrying Apache 2.0 or MIT licenses specifically to avoid that procurement friction. Neither Scout nor Maverick ships with a managed inference API from Meta directly — teams that need guaranteed uptime, autoscaling, and SLA-backed hosting must either build that layer themselves or pay a third-party host, at which point the cost advantage of open weights shrinks against a managed provider like Anthropic or OpenAI.

Bottom line

Grok Code Fast 1 is paid while Llama 4 Scout is free; Llama 4 Scout is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Grok Code Fast 1 and Llama 4 Scout?

Grok Code Fast 1 is Paid, while Llama 4 Scout is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Grok Code Fast 1 better than Llama 4 Scout?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.