Llama 3 70B Instruct vs o4-mini
Llama 3 70B Instruct (2024) and o4-mini (2025) are frontier reasoning models from AI at Meta and OpenAI. Llama 3 70B Instruct ships a 8K-token context window, while o4-mini ships a not-yet-sourced context window. On MMLU PRO, o4-mini leads by 25.8 pts. On pricing, Llama 3 70B Instruct costs $0.4/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
o4-mini is safer overall; choose Llama 3 70B Instruct when provider fit matters.
Specs
| Released | 2024-04-18 | 2025-04-16 |
| Context window | 8K | — |
| Parameters | 70B | — |
| Architecture | decoder only | decoder only |
| License | Open Source | Proprietary |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Llama 3 70B Instruct | o4-mini | |
|---|---|---|
| Input price | $0.4/1M tokens | $0.5/1M tokens |
| Output price | $0.4/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Llama 3 70B Instruct | o4-mini | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3 70B Instruct | o4-mini |
|---|---|---|
| MMLU PRO | 57.4 | 83.2 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3 70B Instruct at 57.4 and o4-mini at 83.2, with o4-mini ahead by 25.8 points. The largest visible gap is 25.8 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
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, and code execution: o4-mini. 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, Llama 3 70B Instruct lists $0.4/1M input and $0.4/1M 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 70B Instruct lower by about $0.55 per million blended tokens. Availability is 18 providers versus 4, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose o4-mini when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which is cheaper, Llama 3 70B Instruct or o4-mini?
Llama 3 70B Instruct is cheaper on tracked token pricing. Llama 3 70B Instruct costs $0.4/1M input and $0.4/1M 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 70B Instruct or o4-mini open source?
Llama 3 70B Instruct 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 70B Instruct 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 70B Instruct 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 70B Instruct 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 70B Instruct and o4-mini?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. 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.