Codex Mini vs Llama 3.1 8B
Compare OpenAI and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Codex Mini
Llama 3.1 8B
Cost Differences
Llama 3.1 8B costs less than Codex Mini
Feature Comparison
| Feature | Codex Mini | Llama 3.1 8B |
|---|---|---|
| Provider | OpenAI | Meta (via Together AI) |
| Input Price | $1.50/1M tokens | $0.18/1M tokens |
| Output Price | $6.00/1M tokens | $0.18/1M tokens |
| Context Window | 200,000 tokens | 128,000 tokens |
| Max Output | 32,768 tokens | 32,768 tokens |
| Category | efficient | efficient |
| Capabilities | textcodereasoning | textcode |
| Release Date | 2/2/2026 | 7/23/2024 |
Codex Mini vs Llama 3.1 8B: Which Should You Choose?
Choosing between Codex Mini and Llama 3.1 8B depends on your priorities: cost efficiency, context length, or raw capability. Llama 3.1 8B is the more affordable option at $0.18/1M input tokens — 88% cheaper than Codex Mini. Meanwhile, Codex Mini offers a significantly larger context window at 200,000 tokens vs 128,000 for Llama 3.1 8B.
These models come from different providers — OpenAI and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with OpenAI, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
Both models are in the efficient category, making this a direct head-to-head comparison. At scale — say 10,000 requests per day — the cost difference adds up: Llama 3.1 8B would save you roughly $1,269.00/month compared to Codex Mini. For startups and indie developers, that difference can be significant.
Output costs matter too. Codex Mini charges $6.00/1M output tokens vs $0.18 for Llama 3.1 8B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 3.1 8B has the edge here at $0.18/1M output tokens.
Best Use Cases
Choose Codex Mini when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (reasoning)
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose Llama 3.1 8B when:
- • Budget is a primary concern
- • You're already using Meta (via Together AI)'s API ecosystem
- • You're running high-volume, latency-sensitive workloads
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Codex Mini (OpenAI)
Llama 3.1 8B (Meta (via Together AI))
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