Llama 3.2 1B vs o4-mini
Llama 3.2 1B (2024) and o4-mini (2025) are frontier reasoning models from AI at Meta and OpenAI. Llama 3.2 1B ships a 128K-token context window, while o4-mini ships a not-yet-sourced context window. On pricing, Llama 3.2 1B costs $0.1/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Llama 3.2 1B is ~400% cheaper at $0.1/1M; pay for o4-mini only for coding workflow support.
Specs
| Released | 2024-09-25 | 2025-04-16 |
| Context window | 128K | — |
| Parameters | 1.23B | — |
| Architecture | decoder only | decoder only |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2023-12 | 2025-08 |
Pricing and availability
| Llama 3.2 1B | o4-mini | |
|---|---|---|
| Input price | $0.1/1M tokens | $0.5/1M tokens |
| Output price | $0.1/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Llama 3.2 1B | o4-mini | |
|---|---|---|
| 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 vision: o4-mini, multimodal input: o4-mini, reasoning mode: o4-mini, function calling: o4-mini, tool use: o4-mini, structured outputs: o4-mini, and code execution: o4-mini. 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.
For cost, Llama 3.2 1B lists $0.1/1M input and $0.1/1M output tokens, while o4-mini lists $0.5/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 1B lower by about $0.85 per million blended tokens. Availability is 1 providers versus 4, so concentration risk also matters.
Choose Llama 3.2 1B when provider fit and lower input-token cost are central to the workload. Choose o4-mini when coding workflow support 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.
FAQ
Which is cheaper, Llama 3.2 1B or o4-mini?
Llama 3.2 1B is cheaper on tracked token pricing. Llama 3.2 1B costs $0.1/1M input and $0.1/1M output tokens. o4-mini costs $0.5/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.2 1B or o4-mini open source?
Llama 3.2 1B is listed under Open Source. o4-mini is listed under Proprietary. 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 vision, Llama 3.2 1B or o4-mini?
o4-mini has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Llama 3.2 1B or o4-mini?
o4-mini 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.
Which is better for reasoning mode, Llama 3.2 1B or o4-mini?
o4-mini has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.2 1B and o4-mini?
Llama 3.2 1B is available on Fireworks AI. o4-mini is available on OpenAI API, OpenRouter, OpenAI Batch API, and Replicate API. 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.