GPT-5 nano vs Llama 3.3 70B
GPT-5 nano vs Llama 3.3 70B: GPT-5 nano is cheaper for input-heavy usage ($0.05/M vs $0.88/M input tokens), while Llama 3.3 70B is better for long-context tasks (131,072 tokens).
Direct answer: choose GPT-5 nano for lower token spend and choose Llama 3.3 70B when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
GPT-5 nano
Llama 3.3 70B
Cost Differences
Llama 3.3 70B costs more than GPT-5 nano
Quick Recommendation
Winner for direct API pricing: GPT-5 nano. At the default workload, GPT-5 nano saves about $3.21/month ($39.055/year) versus Llama 3.3 70B.
Feature Comparison
| Feature | GPT-5 nano | Llama 3.3 70B |
|---|---|---|
| Provider | OpenAI | Meta (via Together AI) |
| Input Price | $0.05/1M tokens | $0.88/1M tokens |
| Output Price | $0.40/1M tokens | $0.88/1M tokens |
| Context Window | 128,000 tokens | 131,072 tokens |
| Max Output | 8,192 tokens | 4,096 tokens |
| Category | efficient | standard |
| Capabilities | text | textcode |
| Release Date | 8/7/2025 | 12/6/2024 |
GPT-5 nano vs Llama 3.3 70B: Which Should You Choose?
Choosing between GPT-5 nano and Llama 3.3 70B depends on your priorities: cost efficiency, context length, or raw capability. GPT-5 nano is the more affordable option at $0.05/1M input tokens — 94% cheaper than Llama 3.3 70B. Meanwhile, Llama 3.3 70B offers a significantly larger context window at 131,072 tokens vs 128,000 for GPT-5 nano.
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.
These models target different tiers: GPT-5 nano is a efficient model while Llama 3.3 70B is standard. This means they're optimized for different workloads. Llama 3.3 70B targets more demanding workloads, while GPT-5 nano provides a cost-effective option for everyday tasks.
Output costs matter too. GPT-5 nano charges $0.40/1M output tokens vs $0.88 for Llama 3.3 70B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. GPT-5 nano has the edge here at $0.40/1M output tokens.
Best Use Cases
Choose GPT-5 nano when:
- • Budget is a primary concern
- • You need longer outputs (up to 8,192 tokens)
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose Llama 3.3 70B when:
- • You need a larger context window (131,072 tokens)
- • You need more capabilities (code)
- • You're already using Meta (via Together AI)'s API ecosystem
Pros and Caveats at a Glance
GPT-5 nano
- • Input pricing: $0.05/M tokens
- • Output pricing: $0.40/M tokens
- • Context window: 128,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Smaller context window than Llama 3.3 70B
Llama 3.3 70B
- • Input pricing: $0.88/M tokens
- • Output pricing: $0.88/M tokens
- • Context window: 131,072 tokens
- • Max output: 4,096 tokens
Watch out for
- • Higher input cost than GPT-5 nano
- • Higher output cost than GPT-5 nano
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
GPT-5 nano (OpenAI)
Llama 3.3 70B (Meta (via Together AI))
Start using GPT-5 nano today
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Sign Up for Meta (via Together AI) →Frequently Asked Questions
Which is cheaper, GPT-5 nano or Llama 3.3 70B?▼
What is the context window difference between GPT-5 nano and Llama 3.3 70B?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare OpenAI and Meta (via Together AI) API pricing beyond this model matchup?▼
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