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Grok 4.1 vs Llama 3.2 1B

Grok 4.1 (2025) and Llama 3.2 1B (2024) are compact production models from xAI and AI at Meta. Grok 4.1 ships a 2M-token context window, while Llama 3.2 1B ships a 128K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Grok 4.1 fits 16x more tokens; pick it for long-context work and Llama 3.2 1B for tighter calls.

Specs

Released2025-11-172024-09-25
Context window2M128K
Parameters1.23B
Architecture-decoder only
LicenseProprietaryOpen Source
Knowledge cutoff-2023-12

Pricing and availability

Grok 4.1Llama 3.2 1B
Input price-$0.1/1M tokens
Output price-$0.1/1M tokens
Providers-

Capabilities

Grok 4.1Llama 3.2 1B
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 multimodal input: Grok 4.1. Both models share the core language-model surface, 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.

Pricing coverage is uneven: Grok 4.1 has no token price sourced yet and Llama 3.2 1B has $0.1/1M input tokens. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Grok 4.1 when long-context analysis and larger context windows are central to the workload. Choose Llama 3.2 1B when provider fit 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. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, Grok 4.1 or Llama 3.2 1B?

Grok 4.1 supports 2M tokens, while Llama 3.2 1B supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Grok 4.1 or Llama 3.2 1B open source?

Grok 4.1 is listed under Proprietary. Llama 3.2 1B 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 multimodal input, Grok 4.1 or Llama 3.2 1B?

Grok 4.1 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Grok 4.1 and Llama 3.2 1B?

Grok 4.1 is available on the tracked providers still being sourced. Llama 3.2 1B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Grok 4.1 over Llama 3.2 1B?

Grok 4.1 fits 16x more tokens; pick it for long-context work and Llama 3.2 1B for tighter calls. If your workload also depends on long-context analysis, start with Grok 4.1; if it depends on provider fit, run the same evaluation with Llama 3.2 1B.

Continue comparing

Last reviewed: 2026-04-18. Data sourced from public model cards and provider documentation.